Eyewitness to history: Landmarks in the development of computerized electrocardiography.
Rautaharju, Pentti M
2016-01-01
The use of digital computers for ECG processing was pioneered in the early 1960s by two immigrants to the US, Hubert Pipberger, who initiated a collaborative VA project to collect an ECG-independent Frank lead data base, and Cesar Caceres at NIH who selected for his ECAN program standard 12-lead ECGs processed as single leads. Ray Bonner in the early 1970s placed his IBM 5880 program in a cart to print ECGs with interpretation, and computer-ECG programs were developed by Telemed, Marquette, HP-Philips and Mortara. The "Common Standards for quantitative Electrocardiography (CSE)" directed by Jos Willems evaluated nine ECG programs and eight cardiologists in clinically-defined categories. The total accuracy by a representative "average" cardiologist (75.5%) was 5.8% higher than that of the average program (69.7, p<0.001). Future comparisons of computer-based and expert reader performance are likely to show evolving results with continuing improvement of computer-ECG algorithms and changing expertise of ECG interpreters. Copyright © 2016 Elsevier Inc. All rights reserved.
Burke, J F; Gnall, E; Umrudden, Z; Kyaw, M; Schick, P K
2008-01-01
We developed a computer-based tutorial and a posttest on ECG interpretation for training residents and determining competency. Forty residents, 6 cardiology fellows, and 4 experienced physicians participated. The tutorial emphasized recognition and understanding of abnormal ECG features. Active learning was promoted by asking questions prior to the discussion of ECGs. Interactivity was facilitated by providing rapid and in-depth rationale for correct answers. Responses to questions were recorded and extensively analyzed to determine the quality of questions, baseline knowledge at different levels of training and improvement of grades in posttest. Posttest grades were used to assess improvement and to determine competency. The questions were found to be challenging, fair, appropriate and discriminative. This was important since the quality of Socratic questions is critical for the success of interactive programs. The information on strengths and weakness in baseline knowledge at different levels of training were used to adapt our training program to the needs of residents. The posttest revealed that the tutorial contributed to marked improvement in feature recognition. Competency testing distinguished between residents with outstanding grades and those who needed remediation. The strategy for critical evaluation of our computer program could be applied to any computer-based educational program, regardless of topic.
Fent, Graham; Gosai, Jivendra; Purva, Makani
2016-01-01
Accurate interpretation of the electrocardiogram (ECG) remains an essential skill for medical students and junior doctors. While many techniques for teaching ECG interpretation are described, no single method has been shown to be superior. This randomized control trial is the first to investigate whether teaching ECG interpretation using a computer simulator program or traditional teaching leads to improved scores in a test of ECG interpretation among medical students and postgraduate doctors immediately after and 3months following teaching. Participants' opinions of the program were assessed using a questionnaire. There were no differences in ECG interpretation test scores immediately after or 3months after teaching in the lecture or simulator groups. At present therefore, there is insufficient evidence to suggest that ECG simulator programs are superior to traditional teaching. Copyright © 2016 Elsevier Inc. All rights reserved.
Microprocessor-based cardiotachometer
NASA Technical Reports Server (NTRS)
Crosier, W. G.; Donaldson, J. A.
1981-01-01
Instrument operates reliably even with stress-test electrocardiogram (ECG) signals subject to noise, baseline wandering, and amplitude change. It records heart rate from preamplified, single-lead ECG input signal and produces digital and analog heart-rate outputs which are fed elsewhere. Analog hardware processes ECG input signal, producing 10-ms pulse for each heartbeat. Microprocessor analyzes resulting pulse train, identifying irregular heartbeats and maintaining stable output during lead switching. Easily modified computer program provides analysis.
Application of computerized exercise ECG digitization. Interpretation in large clinical trials.
Caralis, D G; Shaw, L; Bilgere, B; Younis, L; Stocke, K; Wiens, R D; Chaitman, B R
1992-04-01
The authors report on a semiautomated program that incorporates both visual identification of fiducial points and digital determination of the ST-segment at 60 ms and 80 ms from the J point, ST slope, changes in R wave, and baseline drift. The off-line program can enhance the accuracy of detecting electrocardiographic (ECG) changes, as well as reproducibility of the exercise and postexercise ECG, as a marker of myocardial ischemia. The analysis program is written in Microsoft QuickBASIC 2.0 for an IBM personal computer interfaced to a Summagraphics mm1201 microgrid II digitizer. The program consists of the following components: (1) alphanumeric data entry, (2) ECG wave form digitization, (2) calculation of test results, (4) physician overread, and (5) editor function for remeasurements. This computerized exercise ECG digitization-interpretation program is accurate and reproducible for the quantitative assessment of ST changes and requires minimal time allotment for physician overread. The program is suitable for analysis and interpretation of large volumes of exercise tests in multicenter clinical trials and is currently utilized in the TIMI II, TIMI III, and BARI studies sponsored by the National Institutes of Health.
NASA Technical Reports Server (NTRS)
Schlegel, Todd T.; Kulecz, Walter B.; DePalma, Jude L.; Feiveson, Alan H.; Wilson, John S.; Rahman, M. Atiar; Bungo, Michael W.
2004-01-01
Several studies have shown that diminution of the high-frequency (HF; 150-250 Hz) components present within the central portion of the QRS complex of an electrocardiogram (ECG) is a more sensitive indicator for the presence of myocardial ischemia than are changes in the ST segments of the conventional low-frequency ECG. However, until now, no device has been capable of displaying, in real time on a beat-to-beat basis, changes in these HF QRS ECG components in a continuously monitored patient. Although several software programs have been designed to acquire the HF components over the entire QRS interval, such programs have involved laborious off-line calculations and postprocessing, limiting their clinical utility. We describe a personal computer-based ECG software program developed recently at the National Aeronautics and Space Administration (NASA) that acquires, analyzes, and displays HF QRS components in each of the 12 conventional ECG leads in real time. The system also updates these signals and their related derived parameters in real time on a beat-to-beat basis for any chosen monitoring period and simultaneously displays the diagnostic information from the conventional (low-frequency) 12-lead ECG. The real-time NASA HF QRS ECG software is being evaluated currently in multiple clinical settings in North America. We describe its potential usefulness in the diagnosis of myocardial ischemia and coronary artery disease.
Fayn, J; Rubel, P
1988-01-01
The authors present a new computer program for serial ECG analysis that allows a direct comparison of any couple of three-dimensional ECGs and quantitatively assesses the degree of evolution of the spatial loops as well as of their initial, central, or terminal sectors. Loops and sectors are superposed as best as possible, with the aim of overcoming tracing variability of nonpathological origin. As a result, optimal measures of evolution are computed and a tabular summary of measurements is dynamically configured with respect to the patient's history and is then printed. A multivariate classifier assigns each couple of tracings to one of four classes of evolution. Color graphic displays corresponding to several modes of representation may also be plotted.
Computer analysis of Holter electrocardiogram.
Yanaga, T; Adachi, M; Sato, Y; Ichimaru, Y; Otsuka, K
1994-10-01
Computer analysis is indispensable for the interpretation of Holter ECG, because it includes a large quantity of data. Computer analysis of Holter ECG is similar to that of conventional ECG, however, in computer analysis of Holter ECG, there are some difficulties such as many noise, limited analyzing time and voluminous data. The main topics in computer analysis of Holter ECG will be arrhythmias, ST-T changes, heart rate variability, QT interval, late potential and construction of database. Although many papers have been published on the computer analysis of Holter ECG, some of the papers was reviewed briefly in the present paper. We have studied on computer analysis of VPCs, ST-T changes, heart rate variability, QT interval and Cheyne-Stokes respiration during 24-hour ambulatory ECG monitoring. Further, we have studied on ambulatory palmar sweating for the evaluation of mental stress during a day. In future, the development of "the integrated Holter system", which enables the evaluation of ventricular vulnerability and modulating factor such as psychoneural hypersensitivity may be important.
Talebi, Soheila; Azhir, Alaleh; Zuber, Sam; Soman, Sandeep; Visco, Ferdinand; Totouom-Tangho, Holly; Kalantar, Hossein; Worku Hassen, Getaw
2015-04-01
Recognition of prolonged corrected QT (QTc) interval is of particular importance, especially when using medications known to prolong QTc interval. Methadone can prolong the QTc interval and has the potential to induce torsades de pointes. The objective of this study is to investigate the accuracy of computerized ECG analysis in correctly identifying and reporting QTc interval in patients on methadone. We conducted a retrospective review of ECGs in the Muse electronic database of patients on methadone who are above 18 years old between January 2012 and December 2013 at an urban community hospital. ECGs were analyzed by the Marquette 12SL ECG Analysis Program (GE'Healthcare) reviewed by a cardiologist. A total of 826 ECGs of patients on methadone were examined manually for the QTc interval, of which 625 (75.7%) had QTc less than 470 ms, 149 (18%) had QTc between 470-499 ms and 52 (6.3%) had QTc more than 499 ms. QTc between 470-499 ms was underestimated by machine in 19 (12.8%) ECGs and QTc more than 499 ms was underestimated in 10 (19.6%) when compared to manually calculated QTc. QTc prolongation was underreported in 63 ECGs (48.5%) of those whose QTc between 470-499 ms and in 1 ECG (2.4%) of those whose QTc was more than 499 ms. QTc can be underestimated or unreported by the computer analysis. Physicians not only should calculate QTc manually but also examine the actual QTc value displayed on the report before concluding that this parameter is normal, especially in patients who are at risk of QTc prolongation.
Effect of gender on computerized electrocardiogram measurements in college athletes.
Mandic, Sandra; Fonda, Holly; Dewey, Frederick; Le, Vy-van; Stein, Ricardo; Wheeler, Matt; Ashley, Euan A; Myers, Jonathan; Froelicher, Victor F
2010-06-01
Broad criteria for classifying an electrocardiogram (ECG) as abnormal and requiring additional testing prior to participating in competitive athletics have been recommended for the preparticipation examination (PPE) of athletes. Because these criteria have not considered gender differences, we examined the effect of gender on the computerized ECG measurements obtained on Stanford student athletes. Currently available computer programs require a basis for "normal" in athletes of both genders to provide reliable interpretation. During the 2007 PPE, computerized ECGs were recorded and analyzed on 658 athletes (54% male; mean age, 19 +/- 1 years) representing 22 sports. Electrocardiogram measurements included intervals and durations in all 12 leads to calculate 12-lead voltage sums, QRS amplitude and QRS area, spatial vector length (SVL), and the sum of the R wave in V5 and S wave in V2 (RSsum). By computer analysis, male athletes had significantly greater QRS duration, PR interval, Q-wave duration, J-point amplitude, and T-wave amplitude, and shorter QTc interval compared with female athletes (all P < 0.05). All ECG indicators of left ventricular electrical activity were significantly greater in males. Although gender was consistently associated with indices of atrial and ventricular electrical activity in multivariable analysis, ECG measurements correlated poorly with body dimensions. Significant gender differences exist in ECG measurements of college athletes that are not explained by differences in body size. Our tables of "normal" computerized gender-specific measurements can facilitate the development of automated ECG interpretation for screening young athletes.
A remote access ecg monitoring system - biomed 2009.
Ogawa, Hidekuni; Yonezawa, Yoshiharu; Maki, Hiromichi; Iwamoto, Junichi; Hahn, Allen W; Caldwell, W Morton
2009-01-01
We have developed a remotely accessible telemedicine system for monitoring a patient's electrocardiogram (ECG). The system consists of an ECG recorder mounted on chest electrodes and a physician's laptop personal computer. This ECG recorder is designed with a variable gain instrumentation amplifier; a low power 8-bit single-chip microcomputer; two 128KB EEPROMs and 2.4 GHz low transmit power mobile telephone. When the physician wants to monitor the patient's ECG, he/she calls directly from the laptop PC to the ECG recorder's phone and the recorder sends the ECG to the computer. The electrode-mounted recorder continuously samples the ECG. Additionally, when the patient feels a heart discomfort, he/she pushes a data transmission switch on the recorder and the recorder sends the recorded ECG waveforms of the two prior minutes, and for two minutes after the switch is pressed. The physician can display and monitor the data on the computer's liquid crystal display.
Mincholé, Ana; Martínez, Juan Pablo; Laguna, Pablo; Rodriguez, Blanca
2018-01-01
Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first step to help diagnose, understand and predict cardiovascular disorders responsible for 30% of deaths worldwide. Computational techniques, and more specifically machine learning techniques and computational modelling are powerful tools for classification, clustering and simulation, and they have recently been applied to address the analysis of medical data, especially ECG data. This review describes the computational methods in use for ECG analysis, with a focus on machine learning and 3D computer simulations, as well as their accuracy, clinical implications and contributions to medical advances. The first section focuses on heartbeat classification and the techniques developed to extract and classify abnormal from regular beats. The second section focuses on patient diagnosis from whole recordings, applied to different diseases. The third section presents real-time diagnosis and applications to wearable devices. The fourth section highlights the recent field of personalized ECG computer simulations and their interpretation. Finally, the discussion section outlines the challenges of ECG analysis and provides a critical assessment of the methods presented. The computational methods reported in this review are a strong asset for medical discoveries and their translation to the clinical world may lead to promising advances. PMID:29321268
Experimental evaluations of wearable ECG monitor.
Ha, Kiryong; Kim, Youngsung; Jung, Junyoung; Lee, Jeunwoo
2008-01-01
Healthcare industry is changing with ubiquitous computing environment and wearable ECG measurement is one of the most popular approaches in this healthcare industry. Reliability and performance of healthcare device is fundamental issue for widespread adoptions, and interdisciplinary perspectives of wearable ECG monitor make this more difficult. In this paper, we propose evaluation criteria considering characteristic of both ECG measurement and ubiquitous computing. With our wearable ECG monitors, various levels of experimental analysis are performed based on evaluation strategy.
A cloud computing based 12-lead ECG telemedicine service
2012-01-01
Background Due to the great variability of 12-lead ECG instruments and medical specialists’ interpretation skills, it remains a challenge to deliver rapid and accurate 12-lead ECG reports with senior cardiologists’ decision making support in emergency telecardiology. Methods We create a new cloud and pervasive computing based 12-lead Electrocardiography (ECG) service to realize ubiquitous 12-lead ECG tele-diagnosis. Results This developed service enables ECG to be transmitted and interpreted via mobile phones. That is, tele-consultation can take place while the patient is on the ambulance, between the onsite clinicians and the off-site senior cardiologists, or among hospitals. Most importantly, this developed service is convenient, efficient, and inexpensive. Conclusions This cloud computing based ECG tele-consultation service expands the traditional 12-lead ECG applications onto the collaboration of clinicians at different locations or among hospitals. In short, this service can greatly improve medical service quality and efficiency, especially for patients in rural areas. This service has been evaluated and proved to be useful by cardiologists in Taiwan. PMID:22838382
A cloud computing based 12-lead ECG telemedicine service.
Hsieh, Jui-Chien; Hsu, Meng-Wei
2012-07-28
Due to the great variability of 12-lead ECG instruments and medical specialists' interpretation skills, it remains a challenge to deliver rapid and accurate 12-lead ECG reports with senior cardiologists' decision making support in emergency telecardiology. We create a new cloud and pervasive computing based 12-lead Electrocardiography (ECG) service to realize ubiquitous 12-lead ECG tele-diagnosis. This developed service enables ECG to be transmitted and interpreted via mobile phones. That is, tele-consultation can take place while the patient is on the ambulance, between the onsite clinicians and the off-site senior cardiologists, or among hospitals. Most importantly, this developed service is convenient, efficient, and inexpensive. This cloud computing based ECG tele-consultation service expands the traditional 12-lead ECG applications onto the collaboration of clinicians at different locations or among hospitals. In short, this service can greatly improve medical service quality and efficiency, especially for patients in rural areas. This service has been evaluated and proved to be useful by cardiologists in Taiwan.
Daluwatte, C; Johannesen, L; Galeotti, L; Vicente, J; Strauss, D G; Scully, C G
2016-08-01
False and non-actionable alarms in critical care can be reduced by developing algorithms which assess the trueness of an arrhythmia alarm from a bedside monitor. Computational approaches that automatically identify artefacts in ECG signals are an important branch of physiological signal processing which tries to address this issue. Signal quality indices (SQIs) derived considering differences between artefacts which occur in ECG signals and normal QRS morphology have the potential to discriminate pathologically different arrhythmic ECG segments as artefacts. Using ECG signals from the PhysioNet/Computing in Cardiology Challenge 2015 training set, we studied previously reported ECG SQIs in the scientific literature to differentiate ECG segments with artefacts from arrhythmic ECG segments. We found that the ability of SQIs to discriminate between ECG artefacts and arrhythmic ECG varies based on arrhythmia type since the pathology of each arrhythmic ECG waveform is different. Therefore, to reduce the risk of SQIs classifying arrhythmic events as noise it is important to validate and test SQIs with databases that include arrhythmias. Arrhythmia specific SQIs may also minimize the risk of misclassifying arrhythmic events as noise.
Hsieh, Jui-Chien; Li, Ai-Hsien; Yang, Chung-Chi
2013-01-01
Many studies have indicated that computing technology can enable off-site cardiologists to read patients’ electrocardiograph (ECG), echocardiography (ECHO), and relevant images via smart phones during pre-hospital, in-hospital, and post-hospital teleconsultation, which not only identifies emergency cases in need of immediate treatment, but also prevents the unnecessary re-hospitalizations. Meanwhile, several studies have combined cloud computing and mobile computing to facilitate better storage, delivery, retrieval, and management of medical files for telecardiology. In the future, the aggregated ECG and images from hospitals worldwide will become big data, which should be used to develop an e-consultation program helping on-site practitioners deliver appropriate treatment. With information technology, real-time tele-consultation and tele-diagnosis of ECG and images can be practiced via an e-platform for clinical, research, and educational purposes. While being devoted to promote the application of information technology onto telecardiology, we need to resolve several issues: (1) data confidentiality in the cloud, (2) data interoperability among hospitals, and (3) network latency and accessibility. If these challenges are overcome, tele-consultation will be ubiquitous, easy to perform, inexpensive, and beneficial. Most importantly, these services will increase global collaboration and advance clinical practice, education, and scientific research in cardiology. PMID:24232290
Hsieh, Jui-Chien; Li, Ai-Hsien; Yang, Chung-Chi
2013-11-13
Many studies have indicated that computing technology can enable off-site cardiologists to read patients' electrocardiograph (ECG), echocardiography (ECHO), and relevant images via smart phones during pre-hospital, in-hospital, and post-hospital teleconsultation, which not only identifies emergency cases in need of immediate treatment, but also prevents the unnecessary re-hospitalizations. Meanwhile, several studies have combined cloud computing and mobile computing to facilitate better storage, delivery, retrieval, and management of medical files for telecardiology. In the future, the aggregated ECG and images from hospitals worldwide will become big data, which should be used to develop an e-consultation program helping on-site practitioners deliver appropriate treatment. With information technology, real-time tele-consultation and tele-diagnosis of ECG and images can be practiced via an e-platform for clinical, research, and educational purposes. While being devoted to promote the application of information technology onto telecardiology, we need to resolve several issues: (1) data confidentiality in the cloud, (2) data interoperability among hospitals, and (3) network latency and accessibility. If these challenges are overcome, tele-consultation will be ubiquitous, easy to perform, inexpensive, and beneficial. Most importantly, these services will increase global collaboration and advance clinical practice, education, and scientific research in cardiology.
Zhu, Hao; Sun, Yan; Rajagopal, Gunaretnam; Mondry, Adrian; Dhar, Pawan
2004-01-01
Background Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. Methods We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. Results We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. Conclusions Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described. PMID:15339335
Panigrahy, D; Sahu, P K
2017-03-01
This paper proposes a five-stage based methodology to extract the fetal electrocardiogram (FECG) from the single channel abdominal ECG using differential evolution (DE) algorithm, extended Kalman smoother (EKS) and adaptive neuro fuzzy inference system (ANFIS) framework. The heart rate of the fetus can easily be detected after estimation of the fetal ECG signal. The abdominal ECG signal contains fetal ECG signal, maternal ECG component, and noise. To estimate the fetal ECG signal from the abdominal ECG signal, removal of the noise and the maternal ECG component presented in it is necessary. The pre-processing stage is used to remove the noise from the abdominal ECG signal. The EKS framework is used to estimate the maternal ECG signal from the abdominal ECG signal. The optimized parameters of the maternal ECG components are required to develop the state and measurement equation of the EKS framework. These optimized maternal ECG parameters are selected by the differential evolution algorithm. The relationship between the maternal ECG signal and the available maternal ECG component in the abdominal ECG signal is nonlinear. To estimate the actual maternal ECG component present in the abdominal ECG signal and also to recognize this nonlinear relationship the ANFIS is used. Inputs to the ANFIS framework are the output of EKS and the pre-processed abdominal ECG signal. The fetal ECG signal is computed by subtracting the output of ANFIS from the pre-processed abdominal ECG signal. Non-invasive fetal ECG database and set A of 2013 physionet/computing in cardiology challenge database (PCDB) are used for validation of the proposed methodology. The proposed methodology shows a sensitivity of 94.21%, accuracy of 90.66%, and positive predictive value of 96.05% from the non-invasive fetal ECG database. The proposed methodology also shows a sensitivity of 91.47%, accuracy of 84.89%, and positive predictive value of 92.18% from the set A of PCDB.
NASA Astrophysics Data System (ADS)
Kwon, Hyeokjun; Oh, Sechang; Kumar, Prashanth S.; Varadan, Vijay K.
2012-10-01
CardioVascular Disease(CVD)s lead the sudden cardiac death due to irregular phenomenon of the cardiac signal by the abnormal case of blood vessel and cardiac structure. For last two decades, cardiac disease research for man is under active discussion. As a result, the death rate by cardiac disease in men has been falling gradually compared with relatively increasing the women death rate due to CVD[2]. The main reason of this phenomenon causes the lack a sense of the seriousness to female CVD and different symptom of female CVD compared with the symptoms of male CVD. Usually, because the women CVD accompanies with ordinary symptoms unrecognizing the heart abnormality signal such as unusual fatigue, sleep disturbances, shortness of breath, anxiety, chest discomfort, and indigestion dyspepsia, most women CVD patients do not realize that these symptoms are related to the CVD symptoms. Therefore, periodic ECG signal observation is required for women cardiac disease patients. ElectroCardioGram(ECG) detection, treadmill test/exercise ECG, nuclear scan, coronary angiography, and intracoronary ultrasound are used to diagnose abnormality of heart. Among the medical checkup methods for CVDs checkup, it is very effective method for the diagnosis of cardiac disease and the early detection of heart abnormality to monitor ECG periodically. This paper suggests the effective ECG monitoring system for woman by attaching the system on woman's brassiere by using augmented chest lead attachment method. The suggested system in this paper consists of ECG signal transmission system and a server program to display and analyze the transmitted ECG. The ECG signal transmission system consists of three parts such as ECG physical signal detection part with two electrodes made by gold nanowire structure, data acquisition with AD converter, and data transmission part with GPRS(General Packet Radio Service) communication. Usually, to detect human bio signal, Ag/AgCl or gold cup electrodes are used with conductive gel. However, the gel can be dried when taking long time monitoring. The gold nanowire structure electrodes without consideration of uncomfortable usage of gel are attached on beneath the chest position of a brassiere, and the electrodes convert the physical ECG signal to voltage potential signal. The voltage potential ECG signal is converted to digital signal by AD converter included in microprocessor. The converted ECG signal by AD converter is saved on every 1 sec period in the internal RAM in microprocessor. For transmission of the saved data in the internal RAM to a server computer locating at remote area, the system uses the GPRS communication technology, which can develop the wide area network(WAP) without any gateway and repeater. In addition, the transmission system is operated on client mode of GPRS communication. The remote server is installed a program including the functions of displaying and analyzing the transmitted ECG. To display the ECG data, the program is operated with TCP/IP server mode and static IP address, and to analyze the ECG data, the paper suggests motion artifact remove algorithm including adaptive filter with LMS(least mean square), baseline detection algorithm using predictability estimation theory, a filter with moving weighted factor, low pass filter, peak to peak detection, and interpolation.
Yang, Shu; Qiu, Yuyan; Shi, Bo
2016-09-01
This paper explores the methods of building the internet of things of a regional ECG monitoring, focused on the implementation of ECG monitoring center based on cloud computing platform. It analyzes implementation principles of automatic identifi cation in the types of arrhythmia. It also studies the system architecture and key techniques of cloud computing platform, including server load balancing technology, reliable storage of massive smalfi les and the implications of quick search function.
Software design of a remote real-time ECG monitoring system
NASA Astrophysics Data System (ADS)
Yu, Chengbo; Tao, Hongyan
2005-12-01
Heart disease is one of the main diseases that threaten the health and lives of human beings. At present, the normal remote ECG monitoring system has the disadvantages of a short testing distance and limitation of monitoring lines. Because of accident and paroxysmal disease, ECG monitoring has extended from the hospital to the family. Therefore, remote ECG monitoring through the Internet has the actual value and significance. The principle and design method of software of the remote dynamic ECG monitor was presented and discussed. The monitoring software is programmed with Delphi software based on client-sever interactive mode. The application program of the system, which makes use of multithreading technology, is shown to perform in an excellent manner. The program includes remote link users and ECG processing, i.e. ECG data's receiving, real-time displaying, recording and replaying. The system can connect many clients simultaneously and perform real-time monitoring to patients.
Cardiac Computed Tomography (Multidetector CT, or MDCT)
... other tests, such as chest X-rays , electrocardiograms (ECG) , echocardiograms (echocardiography) , or stress tests , don’t give ... be attached to your chest to monitor your ECG. The ECG is also needed to help the ...
QRS detection based ECG quality assessment.
Hayn, Dieter; Jammerbund, Bernhard; Schreier, Günter
2012-09-01
Although immediate feedback concerning ECG signal quality during recording is useful, up to now not much literature describing quality measures is available. We have implemented and evaluated four ECG quality measures. Empty lead criterion (A), spike detection criterion (B) and lead crossing point criterion (C) were calculated from basic signal properties. Measure D quantified the robustness of QRS detection when applied to the signal. An advanced Matlab-based algorithm combining all four measures and a simplified algorithm for Android platforms, excluding measure D, were developed. Both algorithms were evaluated by taking part in the Computing in Cardiology Challenge 2011. Each measure's accuracy and computing time was evaluated separately. During the challenge, the advanced algorithm correctly classified 93.3% of the ECGs in the training-set and 91.6 % in the test-set. Scores for the simplified algorithm were 0.834 in event 2 and 0.873 in event 3. Computing time for measure D was almost five times higher than for other measures. Required accuracy levels depend on the application and are related to computing time. While our simplified algorithm may be accurate for real-time feedback during ECG self-recordings, QRS detection based measures can further increase the performance if sufficient computing power is available.
Exploring the Relationship Between Eye Movements and Electrocardiogram Interpretation Accuracy
NASA Astrophysics Data System (ADS)
Davies, Alan; Brown, Gavin; Vigo, Markel; Harper, Simon; Horseman, Laura; Splendiani, Bruno; Hill, Elspeth; Jay, Caroline
2016-12-01
Interpretation of electrocardiograms (ECGs) is a complex task involving visual inspection. This paper aims to improve understanding of how practitioners perceive ECGs, and determine whether visual behaviour can indicate differences in interpretation accuracy. A group of healthcare practitioners (n = 31) who interpret ECGs as part of their clinical role were shown 11 commonly encountered ECGs on a computer screen. The participants’ eye movement data were recorded as they viewed the ECGs and attempted interpretation. The Jensen-Shannon distance was computed for the distance between two Markov chains, constructed from the transition matrices (visual shifts from and to ECG leads) of the correct and incorrect interpretation groups for each ECG. A permutation test was then used to compare this distance against 10,000 randomly shuffled groups made up of the same participants. The results demonstrated a statistically significant (α 0.05) result in 5 of the 11 stimuli demonstrating that the gaze shift between the ECG leads is different between the groups making correct and incorrect interpretations and therefore a factor in interpretation accuracy. The results shed further light on the relationship between visual behaviour and ECG interpretation accuracy, providing information that can be used to improve both human and automated interpretation approaches.
Ramkumar, Barathram; Sabarimalai Manikandan, M.
2017-01-01
Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal. PMID:28529758
Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M
2017-02-01
Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.
Mobile GPU-based implementation of automatic analysis method for long-term ECG.
Fan, Xiaomao; Yao, Qihang; Li, Ye; Chen, Runge; Cai, Yunpeng
2018-05-03
Long-term electrocardiogram (ECG) is one of the important diagnostic assistant approaches in capturing intermittent cardiac arrhythmias. Combination of miniaturized wearable holters and healthcare platforms enable people to have their cardiac condition monitored at home. The high computational burden created by concurrent processing of numerous holter data poses a serious challenge to the healthcare platform. An alternative solution is to shift the analysis tasks from healthcare platforms to the mobile computing devices. However, long-term ECG data processing is quite time consuming due to the limited computation power of the mobile central unit processor (CPU). This paper aimed to propose a novel parallel automatic ECG analysis algorithm which exploited the mobile graphics processing unit (GPU) to reduce the response time for processing long-term ECG data. By studying the architecture of the sequential automatic ECG analysis algorithm, we parallelized the time-consuming parts and reorganized the entire pipeline in the parallel algorithm to fully utilize the heterogeneous computing resources of CPU and GPU. The experimental results showed that the average executing time of the proposed algorithm on a clinical long-term ECG dataset (duration 23.0 ± 1.0 h per signal) is 1.215 ± 0.140 s, which achieved an average speedup of 5.81 ± 0.39× without compromising analysis accuracy, comparing with the sequential algorithm. Meanwhile, the battery energy consumption of the automatic ECG analysis algorithm was reduced by 64.16%. Excluding energy consumption from data loading, 79.44% of the energy consumption could be saved, which alleviated the problem of limited battery working hours for mobile devices. The reduction of response time and battery energy consumption in ECG analysis not only bring better quality of experience to holter users, but also make it possible to use mobile devices as ECG terminals for healthcare professions such as physicians and health advisers, enabling them to inspect patient ECG recordings onsite efficiently without the need of a high-quality wide-area network environment.
Electrocardiograms with pacemakers: accuracy of computer reading.
Guglin, Maya E; Datwani, Neeta
2007-04-01
We analyzed the accuracy with which a computer algorithm reads electrocardiograms (ECGs) with electronic pacemakers (PMs). Electrocardiograms were screened for the presence of electronic pacing spikes. Computer-derived interpretations were compared with cardiologists' readings. Computer-drawn interpretations required revision by cardiologists in 61.3% of cases. In 18.4% of cases, the ECG reading algorithm failed to recognize the presence of a PM. The misinterpretation of paced beats as intrinsic beats led to multiple secondary errors, including myocardial infarctions in varying localization. The most common error in computer reading was the failure to identify an underlying rhythm. This error caused frequent misidentification of the PM type, especially when the presence of normal sinus rhythm was not recognized in a tracing with a DDD PM tracking the atrial activity. The increasing number of pacing devices, and the resulting number of ECGs with pacing spikes, mandates the refining of ECG reading algorithms. Improvement is especially needed in the recognition of the underlying rhythm, pacing spikes, and mode of pacing.
Computational Electrocardiography: Revisiting Holter ECG Monitoring.
Deserno, Thomas M; Marx, Nikolaus
2016-08-05
Since 1942, when Goldberger introduced the 12-lead electrocardiography (ECG), this diagnostic method has not been changed. After 70 years of technologic developments, we revisit Holter ECG from recording to understanding. A fundamental change is fore-seen towards "computational ECG" (CECG), where continuous monitoring is producing big data volumes that are impossible to be inspected conventionally but require efficient computational methods. We draw parallels between CECG and computational biology, in particular with respect to computed tomography, computed radiology, and computed photography. From that, we identify technology and methodology needed for CECG. Real-time transfer of raw data into meaningful parameters that are tracked over time will allow prediction of serious events, such as sudden cardiac death. Evolved from Holter's technology, portable smartphones with Bluetooth-connected textile-embedded sensors will capture noisy raw data (recording), process meaningful parameters over time (analysis), and transfer them to cloud services for sharing (handling), predicting serious events, and alarming (understanding). To make this happen, the following fields need more research: i) signal processing, ii) cycle decomposition; iii) cycle normalization, iv) cycle modeling, v) clinical parameter computation, vi) physiological modeling, and vii) event prediction. We shall start immediately developing methodology for CECG analysis and understanding.
[Study for portable dynamic ECG monitor and recorder].
Yang, Pengcheng; Li, Yongqin; Chen, Bihua
2012-09-01
This Paper presents a portable dynamic ECG monitor system based on MSP430F149 microcontroller. The electrocardiogram detecting system consists of ECG detecting circuit, man-machine interaction module, MSP430F149 and upper computer software. The ECG detecting circuit including a preamplifier, second-order Butterworth low-pass filter, high-pass filter, and 50Hz trap circuit to detects electrocardiogram and depresses various kinds of interference effectively. A microcontroller is used to collect three channel analog signals which can be displayed on TFT LCD. A SD card is used to record real-time data continuously and implement the FTA16 file system. In the end, a host computer system interface is also designed to analyze the ECG signal and the analysis results can provide diagnosis references to clinical doctors.
A PC-based generator of surface ECG potentials for computer electrocardiograph testing.
Franchi, D; Palagi, G; Bedini, R
1994-02-01
The system is composed of an electronic circuit, connected to a PC, whose outputs, starting from ECGs digitally collected by commercial interpretative electrocardiographs, simulate virtual patients' limb and chest electrode potentials. Appropriate software manages the D/A conversion and lines up the original short-term signal in a ring buffer to generate continuous ECG traces. The device also permits the addition of artifacts and/or baseline wanders/shifts on each lead separately. The system has been accurately tested and statistical indexes have been computed to quantify the reproduction accuracy analyzing, in the generated signal, both the errors induced on the fiducial point measurements and the capability to retain the diagnostic significance. The device integrated with an annotated ECG data base constitutes a reliable and powerful system to be used in the quality assurance testing of computer electrocardiographs.
Kligfield, Paul; Gettes, Leonard S; Bailey, James J; Childers, Rory; Deal, Barbara J; Hancock, E William; van Herpen, Gerard; Kors, Jan A; Macfarlane, Peter; Mirvis, David M; Pahlm, Olle; Rautaharju, Pentti; Wagner, Galen S
2007-03-01
This statement examines the relation of the resting ECG to its technology. Its purpose is to foster understanding of how the modern ECG is derived and displayed and to establish standards that will improve the accuracy and usefulness of the ECG in practice. Derivation of representative waveforms and measurements based on global intervals are described. Special emphasis is placed on digital signal acquisition and computer-based signal processing, which provide automated measurements that lead to computer-generated diagnostic statements. Lead placement, recording methods, and waveform presentation are reviewed. Throughout the statement, recommendations for ECG standards are placed in context of the clinical implications of evolving ECG technology.
A mobile phone-based ECG monitoring system.
Iwamoto, Junichi; Yonezawa, Yoshiharu; Maki, Hiromichi; Ogawa, Hidekuni; Ninomiya, Ishio; Sada, Kouji; Hamada, Shingo; Hahn, Allen W; Caldwell, W Morton
2006-01-01
We have developed a telemedicine system for monitoring a patient's electrocardiogram during daily activities. The recording system consists of three ECG chest electrodes, a variable gain instrumentation amplifier, a low power 8-bit single-chip microcomputer, a 256 KB EEPROM and a 2.4 GHz low transmitting power mobile phone (PHS). The complete system is mounted on a single, lightweight, chest electrode array. When a heart discomfort is felt, the patient pushes the data transmission switch on the recording system. The system sends the recorded ECG waveforms of the two prior minutes and ECG waveforms of the two minutes after the switch is pressed, directly in the hospital server computer via the PHS. The server computer sends the data to the physician on call. The data is displayed on the doctor's Java mobile phone LCD (Liquid Crystal Display), so he or she can monitor the ECG regardless of their location. The developed ECG monitoring system is not only applicable to at-home patients, but should also be useful for monitoring hospital patients.
Gender differences in the electrocardiogram screening of athletes.
Bessem, Bram B; de Bruijn, Matthijs M C; Nieuwland, Wybe W
2017-02-01
Gender-related differences are frequently used in medicine. Electrocardiograms are also subject to such differences. This study evaluated gender differences in ECG parameters of young athletes, discussing the possible implications of these differences for ECG criteria used in the cardiovascular screening of young athletes. Observational cross-sectional study. In 2013 and 2014 all the ECGs from the cardiovascular screenings performed at University Sports Medical Centre in Groningen of the student athletes who wanted to participate in a college sports program were collected. The ECG characteristics were scored using computer-based measurements and the Seattle ECG criteria. The study population included 1436 athletes, of which 72% were male. Male athletes were older (19.3 years vs. 18.6 years), participated in sports more frequently (4.0/week vs. 3.8/week) and spent more hours per week practising sports (6.4h/week vs. 5.8h/week) than female athletes. Male athletes had significantly higher PR intervals (149ms vs. 141ms), lead voltages and QRS duration (98ms vs. 88ms). Female athletes had significantly higher resting heart rates (69/min vs. 64/min) and QTc intervals (407ms vs. 400ms). Male athletes also had significantly higher amounts of sinus bradycardia (38.3% vs. 23.0%), incomplete RBBB (15.0% vs. 3.7%), early repolarisation (4.5% vs. 1.0%) and isolated QRS voltage criteria for LVH (26.3% vs. 4.6%). All P-values were ≤0.001. ECGs of young athletes demonstrate gender-related differences. These differences could be considered in their cardiovascular screening. For the Seattle ECG criteria we advise additional research into the clinical implications of using gender-based cut-off values for the QRS duration in the intraventricular conduction delay criterion. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Advanced ECG in 2016: is there more than just a tracing?
Reichlin, Tobias; Abächerli, Roger; Twerenbold, Raphael; Kühne, Michael; Schaer, Beat; Müller, Christian; Sticherling, Christian; Osswald, Stefan
2016-01-01
The 12-lead electrocardiogram (ECG) is the most frequently used technology in clinical cardiology. It is critical for evidence-based management of patients with most cardiovascular conditions, including patients with acute myocardial infarction, suspected chronic cardiac ischaemia, cardiac arrhythmias, heart failure and implantable cardiac devices. In contrast to many other techniques in cardiology, the ECG is simple, small, mobile, universally available and cheap, and therefore particularly attractive. Standard ECG interpretation mainly relies on direct visual assessment. The progress in biomedical computing and signal processing, and the available computational power offer fascinating new options for ECG analysis relevant to all fields of cardiology. Several digital ECG markers and advanced ECG technologies have shown promise in preliminary studies. This article reviews promising novel surface ECG technologies in three different fields. (1) For the detection of myocardial ischaemia and infarction, QRS morphology feature analysis, the analysis of high frequency QRS components (HF-QRS) and methods using vectorcardiography as well as ECG imaging are discussed. (2) For the identification and management of patients with cardiac arrhythmias, methods of advanced P-wave analysis are discussed and the concept of ECG imaging for noninvasive localisation of cardiac arrhythmias is presented. (3) For risk stratification of sudden cardiac death and the selection of patients for medical device therapy, several novel markers including an automated QRS-score for scar quantification, the QRS-T angle or the T-wave peak-to-end-interval are discussed. Despite the existing preliminary data, none of the advanced ECG markers and technologies has yet accomplished the transition into clinical practice. Further refinement of these technologies and broader validation in large unselected patient cohorts are the critical next step needed to facilitate translation of advanced ECG technologies into clinical cardiology.
Matched Filtering for Heart Rate Estimation on Compressive Sensing ECG Measurements.
Da Poian, Giulia; Rozell, Christopher J; Bernardini, Riccardo; Rinaldo, Roberto; Clifford, Gari D
2017-09-14
Compressive Sensing (CS) has recently been applied as a low complexity compression framework for long-term monitoring of electrocardiogram signals using Wireless Body Sensor Networks. Long-term recording of ECG signals can be useful for diagnostic purposes and to monitor the evolution of several widespread diseases. In particular, beat to beat intervals provide important clinical information, and these can be derived from the ECG signal by computing the distance between QRS complexes (R-peaks). Numerous methods for R-peak detection are available for uncompressed ECG. However, in case of compressed sensed data, signal reconstruction can be performed with relatively complex optimisation algorithms, which may require significant energy consumption. This article addresses the problem of hearth rate estimation from compressive sensing electrocardiogram (ECG) recordings, avoiding the reconstruction of the entire signal. We consider a framework where the ECG signals are represented under the form of CS linear measurements. The QRS locations are estimated in the compressed domain by computing the correlation of the compressed ECG and a known QRS template. Experiments on actual ECG signals show that our novel solution is competitive with methods applied to the reconstructed signals. Avoiding the reconstruction procedure, the proposed method proves to be very convenient for real-time, low-power applications.
Kligfield, Paul; Gettes, Leonard S; Bailey, James J; Childers, Rory; Deal, Barbara J; Hancock, E William; van Herpen, Gerard; Kors, Jan A; Macfarlane, Peter; Mirvis, David M; Pahlm, Olle; Rautaharju, Pentti; Wagner, Galen S; Josephson, Mark; Mason, Jay W; Okin, Peter; Surawicz, Borys; Wellens, Hein
2007-03-13
This statement examines the relation of the resting ECG to its technology. Its purpose is to foster understanding of how the modern ECG is derived and displayed and to establish standards that will improve the accuracy and usefulness of the ECG in practice. Derivation of representative waveforms and measurements based on global intervals are described. Special emphasis is placed on digital signal acquisition and computer-based signal processing, which provide automated measurements that lead to computer-generated diagnostic statements. Lead placement, recording methods, and waveform presentation are reviewed. Throughout the statement, recommendations for ECG standards are placed in context of the clinical implications of evolving ECG technology.
Kligfield, Paul; Gettes, Leonard S; Bailey, James J; Childers, Rory; Deal, Barbara J; Hancock, E William; van Herpen, Gerard; Kors, Jan A; Macfarlane, Peter; Mirvis, David M; Pahlm, Olle; Rautaharju, Pentti; Wagner, Galen S; Josephson, Mark; Mason, Jay W; Okin, Peter; Surawicz, Borys; Wellens, Hein
2007-03-13
This statement examines the relation of the resting ECG to its technology. Its purpose is to foster understanding of how the modern ECG is derived and displayed and to establish standards that will improve the accuracy and usefulness of the ECG in practice. Derivation of representative waveforms and measurements based on global intervals are described. Special emphasis is placed on digital signal acquisition and computer-based signal processing, which provide automated measurements that lead to computer-generated diagnostic statements. Lead placement, recording methods, and waveform presentation are reviewed. Throughout the statement, recommendations for ECG standards are placed in context of the clinical implications of evolving ECG technology.
Helical prospective ECG-gating in cardiac computed tomography: radiation dose and image quality.
DeFrance, Tony; Dubois, Eric; Gebow, Dan; Ramirez, Alex; Wolf, Florian; Feuchtner, Gudrun M
2010-01-01
Helical prospective ECG-gating (pECG) may reduce radiation dose while maintaining the advantages of helical image acquisition for coronary computed tomography angiography (CCTA). Aim of this study was to evaluate helical pECG-gating in CCTA in regards to radiation dose and image quality. 86 patients undergoing 64-multislice CCTA were enrolled. pECG-gating was performed in patients with regular heart rates (HR) < 65 bpm; with the gating window set at 70-85% of the cardiac cycle. All patients received oral and some received additional IV beta-blockers to achieve HR < 65 bpm. In patients with higher or irregular HR, or for functional evaluation, retrospective ECG-gating (rECG) was performed. The average X-ray dose was estimated from the dose length product. Each arterial segment (modified AHA/ACC 17-segment-model) was evaluated on a 4-point image quality scale (4 = excellent; 3 = good, mild artefact; 2 = acceptable, some artefact, 1 = uninterpretable). pECG-gating was applied in 57 patients, rECG-gating in 29 patients. There was no difference in age, gender, body mass index, scan length or tube output settings between both groups. HR in the pECG-group was 54.7 bpm (range, 43-64). The effective radiation dose was significantly lower for patients scanned with pECG-gating with mean 6.9 mSv +/- 1.9 (range, 2.9-10.7) compared to rECG with 16.9 mSv +/- 4.1 (P < 0.001), resulting in a mean dose reduction of 59.2%. For pECG-gating, out of 969 coronary segments, 99.3% were interpretable. Image quality was excellent in 90.2%, good in 7.8%, acceptable in 1.3% and non-interpretable in 0.7% (n = 7 segments). For patients with steady heart rates <65 bpm, helical prospective ECG-gating can significantly lower the radiation dose while maintaining high image quality.
McClennen, Seth; Nathanson, Larry A; Safran, Charles; Goldberger, Ary L
2003-12-01
To create a multimedia internet-based ECG teaching tool, with the ability to rapidly incorporate new clinical cases. We created ECG Wave-Maven ( http://ecg.bidmc.harvard.edu ), a novel teaching tool with a direct link to an institution-wide clinical repository. We analyzed usage data from the web between December, 2000 and May 2002. In 17 months, there have been 4105 distinct uses of the program. A majority of users are physicians or medical students (2605, 63%), and almost half report use as an educational tool. The internet offers an opportunity to provide easily-expandable, open access resources for ECG pedagogy which may be used to complement traditional methods of instruction.
A new mobile phone-based ECG monitoring system.
Iwamoto, Junichi; Yonezawa, Yoshiharu; Ogawa, Hiromichi Maki Hidekuni; Ninomiya, Ishio; Sada, Kouji; Hamada, Shingo; Hahn, Allen W; Caldwell, W Morton
2007-01-01
We have developed a system for monitoring a patient's electrocardiogram (ECG) and movement during daily activities. The complete system is mounted on chest electrodes and continuously samples the ECG and three axis accelerations. When the patient feels a heart discomfort, he or she pushes the data transmission switch on the recording system and the system sends the recorded ECG waveforms and three axis accelerations of the two prior minutes, and for two minutes after the switch is pressed. The data goes directly to a hospital server computer via a 2.4 GHz low power mobile phone. These data are stored on a server computer and downloaded to the physician's Java mobile phone. The physician can display the data on the phone's liquid crystal display.
Cairns, Andrew W; Bond, Raymond R; Finlay, Dewar D; Breen, Cathal; Guldenring, Daniel; Gaffney, Robert; Gallagher, Anthony G; Peace, Aaron J; Henn, Pat
2016-12-01
The 12-lead Electrocardiogram (ECG) presents a plethora of information and demands extensive knowledge and a high cognitive workload to interpret. Whilst the ECG is an important clinical tool, it is frequently incorrectly interpreted. Even expert clinicians are known to impulsively provide a diagnosis based on their first impression and often miss co-abnormalities. Given it is widely reported that there is a lack of competency in ECG interpretation, it is imperative to optimise the interpretation process. Predominantly the ECG interpretation process remains a paper based approach and whilst computer algorithms are used to assist interpreters by providing printed computerised diagnoses, there are a lack of interactive human-computer interfaces to guide and assist the interpreter. An interactive computing system was developed to guide the decision making process of a clinician when interpreting the ECG. The system decomposes the interpretation process into a series of interactive sub-tasks and encourages the clinician to systematically interpret the ECG. We have named this model 'Interactive Progressive based Interpretation' (IPI) as the user cannot 'progress' unless they complete each sub-task. Using this model, the ECG is segmented into five parts and presented over five user interfaces (1: Rhythm interpretation, 2: Interpretation of the P-wave morphology, 3: Limb lead interpretation, 4: QRS morphology interpretation with chest lead and rhythm strip presentation and 5: Final review of 12-lead ECG). The IPI model was implemented using emerging web technologies (i.e. HTML5, CSS3, AJAX, PHP and MySQL). It was hypothesised that this system would reduce the number of interpretation errors and increase diagnostic accuracy in ECG interpreters. To test this, we compared the diagnostic accuracy of clinicians when they used the standard approach (control cohort) with clinicians who interpreted the same ECGs using the IPI approach (IPI cohort). For the control cohort, the (mean; standard deviation; confidence interval) of the ECG interpretation accuracy was (45.45%; SD=18.1%; CI=42.07, 48.83). The mean ECG interpretation accuracy rate for the IPI cohort was 58.85% (SD=42.4%; CI=49.12, 68.58), which indicates a positive mean difference of 13.4%. (CI=4.45, 22.35) An N-1 Chi-square test of independence indicated a 92% chance that the IPI cohort will have a higher accuracy rate. Interpreter self-rated confidence also increased between cohorts from a mean of 4.9/10 in the control cohort to 6.8/10 in the IPI cohort (p=0.06). Whilst the IPI cohort had greater diagnostic accuracy, the duration of ECG interpretation was six times longer when compared to the control cohort. We have developed a system that segments and presents the ECG across five graphical user interfaces. Results indicate that this approach improves diagnostic accuracy but with the expense of time, which is a valuable resource in medical practice. Copyright © 2016 Elsevier Inc. All rights reserved.
[Monitor of ECG signal and heart rate using a mobile phone with Bluetooth communication protocol].
Becerra-Luna, Brayans; Dávila-García, Rodrigo; Salgado-Rodríguez, Paola; Martínez-Memije, Raúl; Infante-Vázquez, Oscar
2012-01-01
To develop a portable signal monitoring equipment for electrocardiography (ECG) and heart rate (HR), communicated with a mobile phone using the Bluetooth (BT) communication protocol for display of the signal on screen. A monitoring system was designed in which the electronic section performs the ECG signal acquisition, as well as amplification, filtering, analog to digital conversion and transmission of the ECG and HR using BT. Two programs were developed for the system. The first one calculates HR through QRS identification and sends the ECG signals and HR to the mobile, and the second program is an application to acquire and display them on the mobile screen. We developed a portable electronic system powered by a 9 volt battery, with amplification and bandwidth meeting the international standards for ECG monitoring. The QRS complex identification was performed using the second derivative algorithm, while the programs allow sending and receiving information from the ECG and HR via BT, and viewing it on the mobile screen. The monitoring is feasible within distances of 15 m and it has been tested in various mobiles telephones of brands Nokia®, Sony Ericsson® and Samsung®. This system shows an alternative for mobile monitoring using BT and Java 2 Micro Edition (J2ME) programming. It allows the register of the ECG trace and HR, and it can be implemented in different phones. Copyright © 2011 Instituto Nacional de Cardiología Ignacio Chávez. Published by Masson Doyma México S.A. All rights reserved.
Rooijakkers, Michiel; Rabotti, Chiara; Bennebroek, Martijn; van Meerbergen, Jef; Mischi, Massimo
2011-01-01
Non-invasive fetal health monitoring during pregnancy has become increasingly important. Recent advances in signal processing technology have enabled fetal monitoring during pregnancy, using abdominal ECG recordings. Ubiquitous ambulatory monitoring for continuous fetal health measurement is however still unfeasible due to the computational complexity of noise robust solutions. In this paper an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, while increasing the R-peak detection quality compared to existing R-peak detection schemes. Validation of the algorithm is performed on two manually annotated datasets, the MIT/BIH Arrhythmia database and an in-house abdominal database. Both R-peak detection quality and computational complexity are compared to state-of-the-art algorithms as described in the literature. With a detection error rate of 0.22% and 0.12% on the MIT/BIH Arrhythmia and in-house databases, respectively, the quality of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.
Chen, Ying-Hsien; Hung, Chi-Sheng; Huang, Ching-Chang; Hung, Yu-Chien
2017-01-01
Background Atrial fibrillation (AF) is a common form of arrhythmia that is associated with increased risk of stroke and mortality. Detecting AF before the first complication occurs is a recognized priority. No previous studies have examined the feasibility of undertaking AF screening using a telehealth surveillance system with an embedded cloud-computing algorithm; we address this issue in this study. Objective The objective of this study was to evaluate the feasibility of AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm. Methods We conducted a prospective AF screening study in a nonmetropolitan area using a single-lead electrocardiogram (ECG) recorder. All ECG measurements were reviewed on the telehealth surveillance system and interpreted by the cloud-computing algorithm and a cardiologist. The process of AF screening was evaluated with a satisfaction questionnaire. Results Between March 11, 2016 and August 31, 2016, 967 ECGs were recorded from 922 residents in nonmetropolitan areas. A total of 22 (2.4%, 22/922) residents with AF were identified by the physician’s ECG interpretation, and only 0.2% (2/967) of ECGs contained significant artifacts. The novel cloud-computing algorithm for AF detection had a sensitivity of 95.5% (95% CI 77.2%-99.9%) and specificity of 97.7% (95% CI 96.5%-98.5%). The overall satisfaction score for the process of AF screening was 92.1%. Conclusions AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm is feasible. PMID:28951384
Computerized classification of proximal occlusion in the left anterior descending coronary artery.
Gregg, Richard E; Nikus, Kjell C; Zhou, Sophia H; Startt Selvester, Ronald H; Barbara, Victoria
2010-01-01
Proximal occlusion within the left anterior descending (LAD) coronary artery in patients with acute myocardial infarction leads to higher mortality than does nonproximal occlusion. We evaluated an automated program to detect proximal LAD occlusion. All patients with suspected acute coronary syndrome (n = 7,710) presenting consecutively to the emergency department of a local hospital with a coronary angiogram–confirmed flow-limiting lesion and notation of occlusion site were included in the study (n = 711). Electrocardiograms (ECGs) that met ST-segment elevation myocardial infarction (STEMI) criteria were included in the training set (n = 183). Paired angiographic location of proximal LAD and ECGs with ST elevation in the anterolateral region were used for the computer program development (n = 36). The test set was based on ECG criteria for anterolateral STEMI only without angiographic reports (n = 162). Tested against 2 expert cardiologists' agreed reading of proximal LAD occlusion, the algorithm has a sensitivity of 95% and a specificity of 82%. The algorithm is designed to have high sensitivity rather than high specificity for the purpose of not missing any proximal LAD in the STEMI population. Our preliminary evaluation suggests that the algorithm can detect proximal LAD occlusion as an additional interpretation to STEMI detection with similar accuracy as cardiologist readers.
Freeware eLearning Flash-ECG for learning electrocardiography.
Romanov, Kalle; Kuusi, Timo
2009-06-01
Electrocardiographic (ECG) analysis can be taught in eLearning programmes with suitable software that permits the effective use of basic tools such as a ruler and a magnifier, required for measurements. The Flash-ECG (Research & Development Unit for Medical Education, University of Helsinki, Finland) was developed to enable teachers and students to use scanned and archived ECGs on computer screens and classroom projectors. The software requires only a standard web browser with a Flash plug-in and can be integrated with learning environments (Blackboard/WebCT, Moodle). The Flash-ECG is freeware and is available to medical teachers worldwide.
NASA Astrophysics Data System (ADS)
Yan, Hua-Wen; Huang, Xiao-Lin; Zhao, Ying; Si, Jun-Feng; Liu, Tie-Bing; Liu, Hong-Xing
2014-11-01
A series of experiments are conducted to confirm whether the vectors calculated for an early section of a continuous non-invasive fetal electrocardiogram (fECG) recording can be directly applied to subsequent sections in order to reduce the computation required for real-time monitoring. Our results suggest that it is generally feasible to apply the initial optimal maternal and fetal ECG combination vectors to extract the fECG and maternal ECG in subsequent recorded sections.
Viljoen, Charle André; Scott Millar, Rob; Engel, Mark E; Shelton, Mary; Burch, Vanessa
2017-12-26
Although ECG interpretation is an essential skill in clinical medicine, medical students and residents often lack ECG competence. Novel teaching methods are increasingly being implemented and investigated to improve ECG training. Computer-assisted instruction is one such method under investigation; however, its efficacy in achieving better ECG competence among medical students and residents remains uncertain. This article describes the protocol for a systematic review and meta-analysis that will compare the effectiveness of computer-assisted instruction with other teaching methods used for the ECG training of medical students and residents. Only studies with a comparative research design will be considered. Articles will be searched for in electronic databases (PubMed, Scopus, Web of Science, Academic Search Premier, CINAHL, PsycINFO, Education Resources Information Center, Africa-Wide Information and Teacher Reference Center). In addition, we will review citation indexes and conduct a grey literature search. Data extraction will be done on articles that met the predefined eligibility criteria. A descriptive analysis of the different teaching modalities will be provided and their educational impact will be assessed in terms of effect size and the modified version of Kirkpatrick framework for the evaluation of educational interventions. This systematic review aims to provide evidence as to whether computer-assisted instruction is an effective teaching modality for ECG training. It is hoped that the information garnered from this systematic review will assist in future curricular development and improve ECG training. As this research is a systematic review of published literature, ethical approval is not required. The results will be reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis statement and will be submitted to a peer-reviewed journal. The protocol and systematic review will be included in a PhD dissertation. CRD42017067054; Pre-results. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
The Abnormal vs. Normal ECG Classification Based on Key Features and Statistical Learning
NASA Astrophysics Data System (ADS)
Dong, Jun; Tong, Jia-Fei; Liu, Xia
As cardiovascular diseases appear frequently in modern society, the medicine and health system should be adjusted to meet the new requirements. Chinese government has planned to establish basic community medical insurance system (BCMIS) before 2020, where remote medical service is one of core issues. Therefore, we have developed the "remote network hospital system" which includes data server and diagnosis terminal by the aid of wireless detector to sample ECG. To improve the efficiency of ECG processing, in this paper, abnormal vs. normal ECG classification approach based on key features and statistical learning is presented, and the results are analyzed. Large amount of normal ECG could be filtered by computer automatically and abnormal ECG is left to be diagnosed specially by physicians.
Chen, Ying-Hsien; Hung, Chi-Sheng; Huang, Ching-Chang; Hung, Yu-Chien; Hwang, Juey-Jen; Ho, Yi-Lwun
2017-09-26
Atrial fibrillation (AF) is a common form of arrhythmia that is associated with increased risk of stroke and mortality. Detecting AF before the first complication occurs is a recognized priority. No previous studies have examined the feasibility of undertaking AF screening using a telehealth surveillance system with an embedded cloud-computing algorithm; we address this issue in this study. The objective of this study was to evaluate the feasibility of AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm. We conducted a prospective AF screening study in a nonmetropolitan area using a single-lead electrocardiogram (ECG) recorder. All ECG measurements were reviewed on the telehealth surveillance system and interpreted by the cloud-computing algorithm and a cardiologist. The process of AF screening was evaluated with a satisfaction questionnaire. Between March 11, 2016 and August 31, 2016, 967 ECGs were recorded from 922 residents in nonmetropolitan areas. A total of 22 (2.4%, 22/922) residents with AF were identified by the physician's ECG interpretation, and only 0.2% (2/967) of ECGs contained significant artifacts. The novel cloud-computing algorithm for AF detection had a sensitivity of 95.5% (95% CI 77.2%-99.9%) and specificity of 97.7% (95% CI 96.5%-98.5%). The overall satisfaction score for the process of AF screening was 92.1%. AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm is feasible. ©Ying-Hsien Chen, Chi-Sheng Hung, Ching-Chang Huang, Yu-Chien Hung, Juey-Jen Hwang, Yi-Lwun Ho. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 26.09.2017.
ECG Electrocardiogram (For Parents)
... presented in a standard sequence. Now the ECG tracings are stored as computer files that can be ... of Use Notice of Nondiscrimination Visit the Nemours Web site. Note: All information on KidsHealth® is for ...
An Analysis for Capital Expenditure Decisions at a Naval Regional Medical Center.
1981-12-01
Service Equipment Review Committee 1. Portable defibrilator Computed tomographic scanner and cardioscope 2. ECG cart Automated blood cell counter 3. Gas...system sterilizer Gas system sterilizer 4. Automated blood cell Portable defibrilator and counter cardioscope 5. Computed tomographic ECG cart scanner...dictating and automated typing) systems. e. Filing equipment f. Automatic data processing equipment including data communications equipment. g
De Pooter, Jan; El Haddad, Milad; Stroobandt, Roland; De Buyzere, Marc; Timmermans, Frank
2017-06-01
QRS duration (QRSD) plays a key role in the field of cardiac resynchronization therapy (CRT). Computer-calculated QRSD assessments are widely used, however inter-manufacturer differences have not been investigated in CRT candidates. QRSD was assessed in 377 digitally stored ECGs: 139 narrow QRS, 140 LBBB and 98 ventricular paced ECGs. Manual QRSD was measured as global QRSD, using digital calipers, by two independent observers. Computer-calculated QRSD was assessed by Marquette 12SL (GE Healthcare, Waukesha, WI, USA) and SEMA3 (Schiller, Baar, Switzerland). Inter-manufacturer differences of computer-calculated QRSD assessments vary among different QRS morphologies: narrow QRSD: 4 [2-9] ms (median [IQR]), p=0.010; LBBB QRSD: 7 [2-10] ms, p=0.003 and paced QRSD: 13 [6-18] ms, p=0.007. Interobserver differences of manual QRSD assessments measured: narrow QRSD: 4 [2-6] ms, p=non-significant; LBBB QRSD: 6 [3-12] ms, p=0.006; paced QRSD: 8 [4-18] ms, p=0.001. In LBBB ECGs, intraclass correlation coefficients (ICCs) were comparable for inter-manufacturer and interobserver agreement (ICC 0.830 versus 0.837). When assessing paced QRSD, manual measurements showed higher ICC compared to inter-manufacturer agreement (ICC 0.902 versus 0.776). Using guideline cutoffs of 130ms, up to 15% of the LBBB ECGs would be misclassified as <130ms or ≥130ms by at least one method. Using a cutoff of 150ms, this number increases to 33% of ECGs being misclassified. However, by combining LBBB-morphology and QRSD, the number of misclassified ECGs can be decreased by half. Inter-manufacturer differences in computer-calculated QRSD assessments are significant and may compromise adequate selection of individual CRT candidates when using QRSD as sole parameter. Paced QRSD should preferentially be assessed by manual QRSD measurements. Copyright © 2017 Elsevier B.V. All rights reserved.
Implementation of a portable device for real-time ECG signal analysis.
Jeon, Taegyun; Kim, Byoungho; Jeon, Moongu; Lee, Byung-Geun
2014-12-10
Cardiac disease is one of the main causes of catastrophic mortality. Therefore, detecting the symptoms of cardiac disease as early as possible is important for increasing the patient's survival. In this study, a compact and effective architecture for detecting atrial fibrillation (AFib) and myocardial ischemia is proposed. We developed a portable device using this architecture, which allows real-time electrocardiogram (ECG) signal acquisition and analysis for cardiac diseases. A noisy ECG signal was preprocessed by an analog front-end consisting of analog filters and amplifiers before it was converted into digital data. The analog front-end was minimized to reduce the size of the device and power consumption by implementing some of its functions with digital filters realized in software. With the ECG data, we detected QRS complexes based on wavelet analysis and feature extraction for morphological shape and regularity using an ARM processor. A classifier for cardiac disease was constructed based on features extracted from a training dataset using support vector machines. The classifier then categorized the ECG data into normal beats, AFib, and myocardial ischemia. A portable ECG device was implemented, and successfully acquired and processed ECG signals. The performance of this device was also verified by comparing the processed ECG data with high-quality ECG data from a public cardiac database. Because of reduced computational complexity, the ARM processor was able to process up to a thousand samples per second, and this allowed real-time acquisition and diagnosis of heart disease. Experimental results for detection of heart disease showed that the device classified AFib and ischemia with a sensitivity of 95.1% and a specificity of 95.9%. Current home care and telemedicine systems have a separate device and diagnostic service system, which results in additional time and cost. Our proposed portable ECG device provides captured ECG data and suspected waveform to identify sporadic and chronic events of heart diseases. This device has been built and evaluated for high quality of signals, low computational complexity, and accurate detection.
Cloud-ECG for real time ECG monitoring and analysis.
Xia, Henian; Asif, Irfan; Zhao, Xiaopeng
2013-06-01
Recent advances in mobile technology and cloud computing have inspired numerous designs of cloud-based health care services and devices. Within the cloud system, medical data can be collected and transmitted automatically to medical professionals from anywhere and feedback can be returned to patients through the network. In this article, we developed a cloud-based system for clients with mobile devices or web browsers. Specially, we aim to address the issues regarding the usefulness of the ECG data collected from patients themselves. Algorithms for ECG enhancement, ECG quality evaluation and ECG parameters extraction were implemented in the system. The system was demonstrated by a use case, in which ECG data was uploaded to the web server from a mobile phone at a certain frequency and analysis was performed in real time using the server. The system has been proven to be functional, accurate and efficient. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Computer-Interpreted Electrocardiograms: Benefits and Limitations.
Schläpfer, Jürg; Wellens, Hein J
2017-08-29
Computerized interpretation of the electrocardiogram (CIE) was introduced to improve the correct interpretation of the electrocardiogram (ECG), facilitating health care decision making and reducing costs. Worldwide, millions of ECGs are recorded annually, with the majority automatically analyzed, followed by an immediate interpretation. Limitations in the diagnostic accuracy of CIE were soon recognized and still persist, despite ongoing improvement in ECG algorithms. Unfortunately, inexperienced physicians ordering the ECG may fail to recognize interpretation mistakes and accept the automated diagnosis without criticism. Clinical mismanagement may result, with the risk of exposing patients to useless investigations or potentially dangerous treatment. Consequently, CIE over-reading and confirmation by an experienced ECG reader are essential and are repeatedly recommended in published reports. Implementation of new ECG knowledge is also important. The current status of automated ECG interpretation is reviewed, with suggestions for improvement. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Variable threshold method for ECG R-peak detection.
Kew, Hsein-Ping; Jeong, Do-Un
2011-10-01
In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.
Discussion of "Computational Electrocardiography: Revisiting Holter ECG Monitoring".
Baumgartner, Christian; Caiani, Enrico G; Dickhaus, Hartmut; Kulikowski, Casimir A; Schiecke, Karin; van Bemmel, Jan H; Witte, Herbert
2016-08-05
This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Computational Electrocardiography: Revisiting Holter ECG Monitoring" written by Thomas M. Deserno and Nikolaus Marx. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the paper of Deserno and Marx. In subsequent issues the discussion can continue through letters to the editor.
Trigo, Jesús Daniel; Martínez, Ignacio; Alesanco, Alvaro; Kollmann, Alexander; Escayola, Javier; Hayn, Dieter; Schreier, Günter; García, José
2012-07-01
This paper investigates the application of the enterprise information system (EIS) paradigm to standardized cardiovascular condition monitoring. There are many specifications in cardiology, particularly in the ECG standardization arena. The existence of ECG formats, however, does not guarantee the implementation of homogeneous, standardized solutions for ECG management. In fact, hospital management services need to cope with various ECG formats and, moreover, several different visualization applications. This heterogeneity hampers the normalization of integrated, standardized healthcare information systems, hence the need for finding an appropriate combination of ECG formats and a suitable EIS-based software architecture that enables standardized exchange and homogeneous management of ECG formats. Determining such a combination is one objective of this paper. The second aim is to design and develop the integrated healthcare information system that satisfies the requirements posed by the previous determination. The ECG formats selected include ISO/IEEE11073, Standard Communications Protocol for Computer-Assisted Electrocardiography, and an ECG ontology. The EIS-enabling techniques and technologies selected include web services, simple object access protocol, extensible markup language, or business process execution language. Such a selection ensures the standardized exchange of ECGs within, or across, healthcare information systems while providing modularity and accessibility.
NASA Technical Reports Server (NTRS)
Montogomery, Leslie D.; Ku, Yu-Tsuan E.; Webbon, Bruce W. (Technical Monitor)
1995-01-01
We have prepared a computer program (RHEOSYS:RHEOencephalographic impedance trace scanning SyStem) that can be used to automate the analysis of segmental impedance blood flow waveforms. This program was developed to assist in the post test analysis of recorded impedance traces from multiple segments of the body. It incorporates many of the blood flow, segmental volume, and vascular state indices reported in the world literature. As it is currently programmed, seven points are selected from each blood flow pulse and associated ECG waveforrn: 1. peak of the first ECG QRS complex, 2. start of systolic slope on the blood flow trace, 3. maximum amplitude of the impedance pulse, 4. position of the dicrotic notch, 5. maximum amplitude of the postdicrotic segment, 6. peak of the second ECG QRS complex, and 7. start of the next blood flow pulse. These points we used to calculate various geometric, area, and time-related values associated with the impedance pulse morphology. RHEOSYS then calculates a series of 34 impedance and cardiac cycle parameters which include pulse amplitudes; areas; pulse propagation times; cardiac cycle times; and various measures of arterial and various tone, contractility, and pulse volume. We used this program to calculate the scalp and intracranial blood flow responses to head and neck cooling as it may be applied to lower the body temperatures of multiple sclerosis patients. Twelve women and twelve men were tested using a commercially available head and neck cooling system operated at its maximum cooling capacity for a period of 30 minutes. Head and neck cooling produced a transient change in scalp blood flow and a significant, (P<0.05) decrease of approx. 30% in intracranial blood flow. Results of this experiment will illustrate how REG and RHEOSYS can be used in biomedical applications.
ECG R-R peak detection on mobile phones.
Sufi, F; Fang, Q; Cosic, I
2007-01-01
Mobile phones have become an integral part of modern life. Due to the ever increasing processing power, mobile phones are rapidly expanding its arena from a sole device of telecommunication to organizer, calculator, gaming device, web browser, music player, audio/video recording device, navigator etc. The processing power of modern mobile phones has been utilized by many innovative purposes. In this paper, we are proposing the utilization of mobile phones for monitoring and analysis of biosignal. The computation performed inside the mobile phone's processor will now be exploited for healthcare delivery. We performed literature review on RR interval detection from ECG and selected few PC based algorithms. Then, three of those existing RR interval detection algorithms were programmed on Java platform. Performance monitoring and comparison studies were carried out on three different mobile devices to determine their application on a realtime telemonitoring scenario.
Usefulness of Maintaining a Normal Electrocardiogram Over Time for Predicting Cardiovascular Health.
Soliman, Elsayed Z; Zhang, Zhu-Ming; Chen, Lin Y; Tereshchenko, Larisa G; Arking, Dan; Alonso, Alvaro
2017-01-15
We hypothesized that maintaining a normal electrocardiogram (ECG) status over time is associated with low cardiovascular (CV) disease in a dose-response fashion and subsequently could be used to monitor programs aimed at promoting CV health. This analysis included 4,856 CV disease-free participants from the Atherosclerosis Risk in Communities study who had a normal ECG at baseline (1987 to 1989) and complete electrocardiographic data in subsequent 3 visits (1990 to 1992, 1993 to 1995, and 1996 to 1998). Participants were classified based on maintaining their normal ECG status during these 4 visits into "maintained," "not maintained," or "inconsistent" normal ECG status as defined by the Minnesota ECG classification. CV disease events (coronary heart disease, heart failure, and stroke) were adjudicated from Atherosclerosis Risk in Communities visit-4 through 2010. Over a median follow-up of 13.2 years, 885 CV disease events occurred. The incidence rate of CV disease events was lowest among study participants who maintained a normal ECG status, followed by those with an inconsistent pattern, and then those who did not maintain their normal ECG status (trend p value <0.001). Similarly, the greater the number of visits with a normal ECG status, the lower was the incidence rate of CV disease events (trend p value <0.001). Maintaining (vs not maintaining) a normal ECG status was associated with a lower risk of CV disease, which was lower than that observed in those with inconsistent normal ECG pattern (trend p value <0.01). In conclusion, maintaining a normal ECG status over time is associated with low risk of CV disease in a dose-response fashion, suggesting its potential use as a monitoring tool for programs promoting CV health. Copyright © 2016 Elsevier Inc. All rights reserved.
Brunetti, Natale Daniele; De Gennaro, Luisa; Dellegrottaglie, Giulia; Amoruso, Daniele; Antonelli, Gianfranco; Di Biase, Matteo
2011-11-01
In patients with a major cardiac event, the first priority is to minimize time-to-treatment. For many patients, the first and fastest contact with the health system is through emergency medical services (EMS). However, delay to treatment is still significant in developed countries, and international guidelines therefore recommend that EMS use prehospital electrocardiogram (ECG). Many communities are implementing prehospital ECG programs, with different technical solutions. We report on a region-wide prehospital ECG telecardiology program that involved 233,657 patients from all over Apulia (4 million inhabitants), Italy, who called the public regional free EMS telephone number "118." Prehospital ECG was transmitted by mobile phone to a single regional telecardiology "hub" where a cardiologist available 24/7 promptly reported the ECG, having a briefing with on-scene EMS personnel and EMS district central; patients were then directed to fibrinolysis or primary percutaneous coronary intervention (PCI) as appropriate. Patients were >70 years in 51% of cases, and 55% of prehospital ECGs were unremarkable; the remaining 45% showed signs suggesting acute coronary syndrome (ACS) in 18%, arrhythmias in 20%, and minor findings in 62%. In cases of suspected ACS (chest pain), ECG findings were normal in 77% of patients; 74% of subjects with suspected ACS were screened within 30' from the onset of symptoms. A regional single telecardiology hub providing prehospital ECG for a sole regional public EMS provides an example of a prehospital ECG network optimizing quality of ECG report and uniformity of EMS assistance in a large region-wide network.
An Approach to Noise Reduction in Human Skin Admittance Measurements
2001-10-25
1966, 4, 439-449. [ 4] D. H. Gordon, "Triboelectric interference in the ECG", IEEE Trans., 1975, BME -22, 252-255. [ 5] J. C. Huhta and J. G...Webster, -Hz interference in electrocardiography", IEEE Trans., 1973, BME -20, 91-101. [ 6] S. Grimnes, "Electrovibration, cutaneous sensation of...this period he has published two textbooks about UNIX and Shell Programming, and concentrated at computer simulation and digital signal processing
Mobile cloud-computing-based healthcare service by noncontact ECG monitoring.
Fong, Ee-May; Chung, Wan-Young
2013-12-02
Noncontact electrocardiogram (ECG) measurement technique has gained popularity these days owing to its noninvasive features and convenience in daily life use. This paper presents mobile cloud computing for a healthcare system where a noncontact ECG measurement method is employed to capture biomedical signals from users. Healthcare service is provided to continuously collect biomedical signals from multiple locations. To observe and analyze the ECG signals in real time, a mobile device is used as a mobile monitoring terminal. In addition, a personalized healthcare assistant is installed on the mobile device; several healthcare features such as health status summaries, medication QR code scanning, and reminders are integrated into the mobile application. Health data are being synchronized into the healthcare cloud computing service (Web server system and Web server dataset) to ensure a seamless healthcare monitoring system and anytime and anywhere coverage of network connection is available. Together with a Web page application, medical data are easily accessed by medical professionals or family members. Web page performance evaluation was conducted to ensure minimal Web server latency. The system demonstrates better availability of off-site and up-to-the-minute patient data, which can help detect health problems early and keep elderly patients out of the emergency room, thus providing a better and more comprehensive healthcare cloud computing service.
Mobile Cloud-Computing-Based Healthcare Service by Noncontact ECG Monitoring
Fong, Ee-May; Chung, Wan-Young
2013-01-01
Noncontact electrocardiogram (ECG) measurement technique has gained popularity these days owing to its noninvasive features and convenience in daily life use. This paper presents mobile cloud computing for a healthcare system where a noncontact ECG measurement method is employed to capture biomedical signals from users. Healthcare service is provided to continuously collect biomedical signals from multiple locations. To observe and analyze the ECG signals in real time, a mobile device is used as a mobile monitoring terminal. In addition, a personalized healthcare assistant is installed on the mobile device; several healthcare features such as health status summaries, medication QR code scanning, and reminders are integrated into the mobile application. Health data are being synchronized into the healthcare cloud computing service (Web server system and Web server dataset) to ensure a seamless healthcare monitoring system and anytime and anywhere coverage of network connection is available. Together with a Web page application, medical data are easily accessed by medical professionals or family members. Web page performance evaluation was conducted to ensure minimal Web server latency. The system demonstrates better availability of off-site and up-to-the-minute patient data, which can help detect health problems early and keep elderly patients out of the emergency room, thus providing a better and more comprehensive healthcare cloud computing service. PMID:24316562
A lightweight QRS detector for single lead ECG signals using a max-min difference algorithm.
Pandit, Diptangshu; Zhang, Li; Liu, Chengyu; Chattopadhyay, Samiran; Aslam, Nauman; Lim, Chee Peng
2017-06-01
Detection of the R-peak pertaining to the QRS complex of an ECG signal plays an important role for the diagnosis of a patient's heart condition. To accurately identify the QRS locations from the acquired raw ECG signals, we need to handle a number of challenges, which include noise, baseline wander, varying peak amplitudes, and signal abnormality. This research aims to address these challenges by developing an efficient lightweight algorithm for QRS (i.e., R-peak) detection from raw ECG signals. A lightweight real-time sliding window-based Max-Min Difference (MMD) algorithm for QRS detection from Lead II ECG signals is proposed. Targeting to achieve the best trade-off between computational efficiency and detection accuracy, the proposed algorithm consists of five key steps for QRS detection, namely, baseline correction, MMD curve generation, dynamic threshold computation, R-peak detection, and error correction. Five annotated databases from Physionet are used for evaluating the proposed algorithm in R-peak detection. Integrated with a feature extraction technique and a neural network classifier, the proposed ORS detection algorithm has also been extended to undertake normal and abnormal heartbeat detection from ECG signals. The proposed algorithm exhibits a high degree of robustness in QRS detection and achieves an average sensitivity of 99.62% and an average positive predictivity of 99.67%. Its performance compares favorably with those from the existing state-of-the-art models reported in the literature. In regards to normal and abnormal heartbeat detection, the proposed QRS detection algorithm in combination with the feature extraction technique and neural network classifier achieves an overall accuracy rate of 93.44% based on an empirical evaluation using the MIT-BIH Arrhythmia data set with 10-fold cross validation. In comparison with other related studies, the proposed algorithm offers a lightweight adaptive alternative for R-peak detection with good computational efficiency. The empirical results indicate that it not only yields a high accuracy rate in QRS detection, but also exhibits efficient computational complexity at the order of O(n), where n is the length of an ECG signal. Copyright © 2017 Elsevier B.V. All rights reserved.
A compact ECG R-R interval, respiration and activity recording system.
Yoshimura, Takahiro; Yonezawa, Yoshiharu; Maki, Hiromichi; Ogawa, Hidekuni; Hahn, Allen W; Thayer, Julian F; Caldwell, W Morton
2003-01-01
An ECG R-R interval, respiration and activity recording system has been developed for monitoring variability of heart rate and respiratory frequency during daily life. The recording system employs a variable gain instrumentation amplifier, an accelerometer, a low power 8-bit single-chip microcomputer and a 1024 KB EEPROM. It is constructed on three ECG chest electrodes. The R-R interval and respiration are detected from the ECG. Activity during walking and running is calculated from an accelerator. The detected data are stored in an EEPROM and after recording, are downloaded to a desktop computer for analysis.
Fetal ECG extraction using independent component analysis by Jade approach
NASA Astrophysics Data System (ADS)
Giraldo-Guzmán, Jader; Contreras-Ortiz, Sonia H.; Lasprilla, Gloria Isabel Bautista; Kotas, Marian
2017-11-01
Fetal ECG monitoring is a useful method to assess the fetus health and detect abnormal conditions. In this paper we propose an approach to extract fetal ECG from abdomen and chest signals using independent component analysis based on the joint approximate diagonalization of eigenmatrices approach. The JADE approach avoids redundancy, what reduces matrix dimension and computational costs. Signals were filtered with a high pass filter to eliminate low frequency noise. Several levels of decomposition were tested until the fetal ECG was recognized in one of the separated sources output. The proposed method shows fast and good performance.
Cai, Zhipeng; Luo, Kan; Liu, Chengyu; Li, Jianqing
2017-08-09
A smart electrocardiogram (ECG) garment system was designed for continuous, non-invasive and comfortable ECG monitoring, which mainly consists of four components: Conductive textile electrode, garment, flexible printed circuit board (FPCB)-based ECG processing module and android application program. Conductive textile electrode and FPCB-based ECG processing module (6.8 g, 55 mm × 53 mm × 5 mm) are identified as two key techniques to improve the system's comfort and flexibility. Preliminary experimental results verified that the textile electrodes with circle shape, 40 mm size in diameter, and 5 mm thickness sponge are best suited for the long-term ECG monitoring application. The tests on the whole system confirmed that the designed smart garment can obtain long-term ECG recordings with high signal quality.
Electrocardiographic anxiety profiles improve speech anxiety.
Kim, Pyoung Won; Kim, Seung Ae; Jung, Keun-Hwa
2012-12-01
The present study was to set out in efforts to determine the effect of electrocardiographic (ECG) feedback on the performance in speech anxiety. Forty-six high school students participated in a speech performance educational program. They were randomly divided into two groups, an experimental group with ECG feedback (N = 21) and a control group (N = 25). Feedback was given with video recording in the control, whereas in the experimental group, an additional ECG feedback was provided. Speech performance was evaluated by the Korean Broadcasting System (KBS) speech ability test, which determines the 10 different speaking categories. ECG was recorded during rest and speech, together with a video recording of the speech performance. Changes in R-R intervals were used to reflect anxiety profiles. Three trials were performed for 3-week program. Results showed that the subjects with ECG feedback revealed a significant improvement in speech performance and anxiety states, which compared to those in the control group. These findings suggest that visualization of the anxiety profile feedback with ECG can be a better cognitive therapeutic strategy in speech anxiety.
Chung, Seungmin; Yi, Joohee
2013-01-01
Electromagnetic interference (EMI) can affect various medical devices. Herein, we report the case of EMI from wireless local area network (WLAN) on an electrocardiogram (ECG) monitoring system. A patient who had a prior myocardial infarction participated in the cardiac rehabilitation program in the sports medicine center of our hospital under the wireless ECG monitoring system. After WLAN was installed, wireless ECG monitoring system failed to show a proper ECG signal. ECG signal was distorted when WLAN was turned on, but it was normalized after turning off the WLAN. PMID:23613696
Low-cost compact ECG with graphic LCD and phonocardiogram system design.
Kara, Sadik; Kemaloğlu, Semra; Kirbaş, Samil
2006-06-01
Till today, many different ECG devices are made in developing countries. In this study, low cost, small size, portable LCD screen ECG device, and phonocardiograph were designed. With designed system, heart sounds that take synchronously with ECG signal are heard as sensitive. Improved system consist three units; Unit 1, ECG circuit, filter and amplifier structure. Unit 2, heart sound acquisition circuit. Unit 3, microcontroller, graphic LCD and ECG signal sending unit to computer. Our system can be used easily in different departments of the hospital, health institution and clinics, village clinic and also in houses because of its small size structure and other benefits. In this way, it is possible that to see ECG signal and hear heart sounds as synchronously and sensitively. In conclusion, heart sounds are heard on the part of both doctor and patient because sounds are given to environment with a tiny speaker. Thus, the patient knows and hears heart sounds him/herself and is acquainted by doctor about healthy condition.
Yin, Xinxin; Wang, Jiali; Zheng, Wen; Ma, Jingjing; Hao, Panpan; Chen, Yuguo
2016-07-01
Both coronary computed tomography angiography (CCTA) and exercise electrocardiography (ExECG) are non-invasive testing methods for the evaluation of coronary artery disease (CAD). However, there was controversy on the diagnostic performance of these methods due to the limited data in each single study. Therefore, we performed a meta-analysis to address these issues. We searched PubMed and Embase databases up to May 22, 2015. Two authors identified eligible studies, extracted data and accessed quality. Pooled estimation of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), summary receiver-operating characteristic curve (SROC) and the area under curve (AUC) of CCTA and ExECG for the diagnosis of CAD were calculated using Stata, Meta-Disc and Review Manager statistical software. Seven articles were included. Pooled sensitivity of CCTA and ExECG were 0.98 [95% confidence intervals (CIs): 0.95-0.99] and 0.66 (95% CIs: 0.59-0.72); pooled specificity of CCTA and ExECG were 0.84 (95% CIs: 0.81-0.87) and 0.75 (95% CIs: 0.71-0.79); pooled DOR of CCTA and ExECG were 110.24 (95% CIs: 35.07-346.55) and 6.28 (95% CIs: 2.06-19.13); and AUC of CCTA and ExECG were 0.9950±0.0046 and 0.7727±0.0638, respectively. There is no heterogeneity caused by threshold effect in CCTA or ExECG analysis. The Deeks' test showed no potential publication bias (P=0.17). CCTA has better diagnostic performance than ExECG in the evaluation of CAD, which can provide a better solution for the clinical problem of the diagnosis for CAD.
Rowe, Matthew K; Moore, Peter; Pratap, Jit; Coucher, John; Gould, Paul A; Kaye, Gerald C
2017-05-01
Controversy exists regarding the optimal lead position for chronic right ventricular (RV) pacing. Placing a lead at the RV septum relies upon fluoroscopy assisted by a surface 12-lead electrocardiogram (ECG). We compared the postimplant lead position determined by ECG-gated multidetector contrast-enhanced computed tomography (MDCT) with the position derived from the surface 12-lead ECG. Eighteen patients with permanent RV leads were prospectively enrolled. Leads were placed in the RV septum (RVS) in 10 and the RV apex (RVA) in eight using fluoroscopy with anteroposterior and left anterior oblique 30° views. All patients underwent MDCT imaging and paced ECG analysis. ECG criteria were: QRS duration; QRS axis; positive or negative net QRS amplitude in leads I, aVL, V1, and V6; presence of notching in the inferior leads; and transition point in precordial leads at or after V4. Of the 10 leads implanted in the RVS, computed tomography (CT) imaging revealed seven to be at the anterior RV wall, two at the anteroseptal junction, and one in the true septum. For the eight RVA leads, four were anterior, two septal, and two anteroseptal. All leads implanted in the RVS met at least one ECG criteria (median 3, range 1-6). However, no criteria were specific for septal position as judged by MDCT. Mean QRS duration was 160 ± 24 ms in the RVS group compared with 168 ± 14 ms for RVA pacing (P = 0.38). We conclude that the surface ECG is not sufficiently accurate to determine RV septal lead tip position compared to cardiac CT. © 2017 Wiley Periodicals, Inc.
A Novel Approach to ECG Classification Based upon Two-Layered HMMs in Body Sensor Networks
Liang, Wei; Zhang, Yinlong; Tan, Jindong; Li, Yang
2014-01-01
This paper presents a novel approach to ECG signal filtering and classification. Unlike the traditional techniques which aim at collecting and processing the ECG signals with the patient being still, lying in bed in hospitals, our proposed algorithm is intentionally designed for monitoring and classifying the patient's ECG signals in the free-living environment. The patients are equipped with wearable ambulatory devices the whole day, which facilitates the real-time heart attack detection. In ECG preprocessing, an integral-coefficient-band-stop (ICBS) filter is applied, which omits time-consuming floating-point computations. In addition, two-layered Hidden Markov Models (HMMs) are applied to achieve ECG feature extraction and classification. The periodic ECG waveforms are segmented into ISO intervals, P subwave, QRS complex and T subwave respectively in the first HMM layer where expert-annotation assisted Baum-Welch algorithm is utilized in HMM modeling. Then the corresponding interval features are selected and applied to categorize the ECG into normal type or abnormal type (PVC, APC) in the second HMM layer. For verifying the effectiveness of our algorithm on abnormal signal detection, we have developed an ECG body sensor network (BSN) platform, whereby real-time ECG signals are collected, transmitted, displayed and the corresponding classification outcomes are deduced and shown on the BSN screen. PMID:24681668
Shadows, signals, and stability in Einsteinian cubic gravity
NASA Astrophysics Data System (ADS)
Hennigar, Robie A.; Jahani Poshteh, Mohammad Bagher; Mann, Robert B.
2018-03-01
We conduct a preliminary investigation into the phenomenological implications of Einsteinian cubic gravity (ECG), a four-dimensional theory of gravity cubic in curvature of interest for its unique formulation and properties. We find an analytic approximation for a spherically symmetric black hole solution to this theory using a continued fraction ansatz. This approximate solution is valid everywhere outside of the horizon and we use it to study the orbit of massive test bodies near a black hole, specifically computing the innermost stable circular orbit. We compute constraints on the ECG coupling parameter imposed by Shapiro time delay. We then compute the shadow of an ECG black hole and find it to be larger than its Einsteinian counterpart in general relativity for the same value of the mass. Applying our results to Sgr A*, we find that departures from general relativity are small but in principle distinguishable.
VLSI implementation of a new LMS-based algorithm for noise removal in ECG signal
NASA Astrophysics Data System (ADS)
Satheeskumaran, S.; Sabrigiriraj, M.
2016-06-01
Least mean square (LMS)-based adaptive filters are widely deployed for removing artefacts in electrocardiogram (ECG) due to less number of computations. But they posses high mean square error (MSE) under noisy environment. The transform domain variable step-size LMS algorithm reduces the MSE at the cost of computational complexity. In this paper, a variable step-size delayed LMS adaptive filter is used to remove the artefacts from the ECG signal for improved feature extraction. The dedicated digital Signal processors provide fast processing, but they are not flexible. By using field programmable gate arrays, the pipelined architectures can be used to enhance the system performance. The pipelined architecture can enhance the operation efficiency of the adaptive filter and save the power consumption. This technique provides high signal-to-noise ratio and low MSE with reduced computational complexity; hence, it is a useful method for monitoring patients with heart-related problem.
NASA Technical Reports Server (NTRS)
Cowings, Patricia S.; Naifeh, Karen; Thrasher, Chet
1988-01-01
This report contains the source code and documentation for a computer program used to process impedance cardiography data. The cardiodynamic measures derived from impedance cardiography are ventricular stroke column, cardiac output, cardiac index and Heather index. The program digitizes data collected from the Minnesota Impedance Cardiograph, Electrocardiography (ECG), and respiratory cycles and then stores these data on hard disk. It computes the cardiodynamic functions using interactive graphics and stores the means and standard deviations of each 15-sec data epoch on floppy disk. This software was designed on a Digital PRO380 microcomputer and used version 2.0 of P/OS, with (minimally) a 4-channel 16-bit analog/digital (A/D) converter. Applications software is written in FORTRAN 77, and uses Digital's Pro-Tool Kit Real Time Interface Library, CORE Graphic Library, and laboratory routines. Source code can be readily modified to accommodate alternative detection, A/D conversion and interactive graphics. The object code utilizing overlays and multitasking has a maximum of 50 Kbytes.
Zarzoso, Vicente; Latcu, Decebal G; Hidalgo-Muñoz, Antonio R; Meo, Marianna; Meste, Olivier; Popescu, Irina; Saoudi, Nadir
2016-12-01
Catheter ablation (CA) of persistent atrial fibrillation (AF) is challenging, and reported results are capable of improvement. A better patient selection for the procedure could enhance its success rate while avoiding the risks associated with ablation, especially for patients with low odds of favorable outcome. CA outcome can be predicted non-invasively by atrial fibrillatory wave (f-wave) amplitude, but previous works focused mostly on manual measures in single electrocardiogram (ECG) leads only. To assess the long-term prediction ability of f-wave amplitude when computed in multiple ECG leads. Sixty-two patients with persistent AF (52 men; mean age 61.5±10.4years) referred for CA were enrolled. A standard 1-minute 12-lead ECG was acquired before the ablation procedure for each patient. F-wave amplitudes in different ECG leads were computed by a non-invasive signal processing algorithm, and combined into a mutivariate prediction model based on logistic regression. During an average follow-up of 13.9±8.3months, 47 patients had no AF recurrence after ablation. A lead selection approach relying on the Wald index pointed to I, V1, V2 and V5 as the most relevant ECG leads to predict jointly CA outcome using f-wave amplitudes, reaching an area under the curve of 0.854, and improving on single-lead amplitude-based predictors. Analysing the f-wave amplitude in several ECG leads simultaneously can significantly improve CA long-term outcome prediction in persistent AF compared with predictors based on single-lead measures. Copyright © 2016 Elsevier Masson SAS. All rights reserved.
Tobón, Diana P.; Jayaraman, Srinivasan
2017-01-01
The last few years has seen a proliferation of wearable electrocardiogram (ECG) devices in the market with applications in fitness tracking, patient monitoring, athletic performance assessment, stress and fatigue detection, and biometrics, to name a few. The majority of these applications rely on the computation of the heart rate (HR) and the so-called heart rate variability (HRV) index via time-, frequency-, or non-linear-domain approaches. Wearable/portable devices, however, are highly susceptible to artifacts, particularly those resultant from movement. These artifacts can hamper HR/HRV measurement, thus pose a serious threat to cardiac monitoring applications. While current solutions rely on ECG enhancement as a pre-processing step prior to HR/HRV calculation, existing artifact removal algorithms still perform poorly under extremely noisy scenarios. To overcome this limitation, we take an alternate approach and propose the use of a spectro-temporal ECG signal representation that we show separates cardiac components from artifacts. More specifically, by quantifying the rate-of-change of ECG spectral components over time, we show that heart rate estimates can be reliably obtained even in extremely noisy signals, thus bypassing the need for ECG enhancement. With such HR measurements in hands, we then propose a new noise-robust HRV index termed MD-HRV (modulation-domain HRV) computed as the standard deviation of the obtained HR values. Experiments with synthetic ECG signals corrupted at various different signal-to-noise levels, as well as recorded noisy signals show the proposed measure outperforming several HRV benchmark parameters computed post wavelet-based enhancement. These findings suggest that the proposed HR measures and derived MD-HRV metric are well-suited for ambulant cardiac monitoring applications, particularly those involving intense movement (e.g., elite athletic training). PMID:29255653
Bashir, Mohamed Ezzeldin A; Lee, Dong Gyu; Li, Meijing; Bae, Jang-Whan; Shon, Ho Sun; Cho, Myung Chan; Ryu, Keun Ho
2012-07-01
Coronary heart disease is being identified as the largest single cause of death along the world. The aim of a cardiac clinical information system is to achieve the best possible diagnosis of cardiac arrhythmias by electronic data processing. Cardiac information system that is designed to offer remote monitoring of patient who needed continues follow up is demanding. However, intra- and interpatient electrocardiogram (ECG) morphological descriptors are varying through the time as well as the computational limits pose significant challenges for practical implementations. The former requires that the classification model be adjusted continuously, and the latter requires a reduction in the number and types of ECG features, and thus, the computational burden, necessary to classify different arrhythmias. We propose the use of adaptive learning to automatically train the classifier on up-to-date ECG data, and employ adaptive feature selection to define unique feature subsets pertinent to different types of arrhythmia. Experimental results show that this hybrid technique outperforms conventional approaches and is, therefore, a promising new intelligent diagnostic tool.
Design and Development of Intelligent Electrodes for Future Digital Health Monitoring: A Review
NASA Astrophysics Data System (ADS)
Khairuddin, A. M.; Azir, K. N. F. Ku; Kan, P. Eh
2018-03-01
Electrodes are sensors used in electrocardiography (ECG) monitoring system to diagnose heart diseases. Over the years, diverse types of electrodes have been designed and developed to improve ECG monitoring system. However, more recently, with the technological advances and capabilities from the Internet of Things (IoT), cloud computing and data analytics in personalized healthcare, researchers are attempting to design and develop more effective as well as flexible ECG devices by using intelligent electrodes. This paper reviews previous works on electrodes used in electrocardiography (ECG) monitoring devices to identify the key ftures for designing and developing intelligent electrodes in digital health monitoring devices.
Software design for analysis of multichannel intracardial and body surface electrocardiograms.
Potse, Mark; Linnenbank, André C; Grimbergen, Cornelis A
2002-11-01
Analysis of multichannel ECG recordings (body surface maps (BSMs) and intracardial maps) requires special software. We created a software package and a user interface on top of a commercial data analysis package (MATLAB) by a combination of high-level and low-level programming. Our software was created to satisfy the needs of a diverse group of researchers. It can handle a large variety of recording configurations. It allows for interactive usage through a fast and robust user interface, and batch processing for the analysis of large amounts of data. The package is user-extensible, includes routines for both common and experimental data processing tasks, and works on several computer platforms. The source code is made intelligible using software for structured documentation and is available to the users. The package is currently used by more than ten research groups analysing ECG data worldwide.
Tarantini, Luigi; Cioffi, Giovanni; Di Lenarda, Andrea; Valle, Roberto; Pulignano, Giovanni; Del Sindaco, Donatella; Frigo, Gianfranco; Soravia, Giorgio; Tessier, Renato; Catania, Giuseppe
2008-12-01
Patients with asymptomatic left ventricular systolic dysfunction (ALVSD) have an increased risk of heart failure (HF) and a worse life expectancy. Since valuable therapies may prevent such dismal evolution, screening programs for ALVSD have recently been advocated to detect as early as possible such ominous condition. Echocardiography represents the gold standard for the assessment of ALVSD but its indiscriminate use in screening programs is impractical. Clinical multivariate risk assessment associated with ECG and serum brain natriuretic peptide (BNP) may be a feasible strategy to screen ALVSD. We prospectively sought to investigate the feasibility and effectiveness of a screening program for ALVSD based on ECG and BNP used in a hierarchical sequence in patients at high risk for HF. Patients > or =55 years old with > or =2 risk factors for HF or > or =70 years old with > or =1 risk factor for HF entered the study performing sequentially ECG, BNP and echocardiographic evaluation. ALVSD was defined as a left ventricular ejection fraction < or =50%. Thirty-three of 122 enrolled patients (27%) had ALVSD. They were older, presented more frequently a history of chemotherapy exposure, had often bundle branch block and higher BNP levels. No patient without any major abnormalities (atrial fibrillation, left ventricular hypertrophy, STT alterations of ischemic/strain origin, pathologic Q wave, bundle branch block) on ECG (n=31, 24.4%) had ALVSD. Among the 91 patients with abnormal ECG, ALVSD was observed in 33 (36%). The area under the receiver operating characteristic curve to detect ALVSD by BNP was 0.86 (confidence interval 0.79-0.94, p<0.0001) and BNP values of > or =43 pg/ml showed a sensitivity and a specificity of 94% and 57%, respectively. The proposed screening program was able to identify 95% (31/33) of patients with ALVSD saving 53% of echocardiographic examinations with a substantial reduction of the costs to diagnose ALVSD. Our prospective investigation confirms that ECG and BNP may be useful in detecting ALVSD in high-risk patients. A cost-effective screening program based on such simple and low-cost diagnostic tests might be employed for the prevention of HF in primary and secondary prevention programs in high-risk patients.
Classification of cardiac arrhythmias using competitive networks.
Leite, Cicilia R M; Martin, Daniel L; Sizilio, Glaucia R A; Dos Santos, Keylly E A; de Araujo, Bruno G; Valentim, Ricardo A M; Neto, Adriao D D; de Melo, Jorge D; Guerreiro, Ana M G
2010-01-01
Information generated by sensors that collect a patient's vital signals are continuous and unlimited data sequences. Traditionally, this information requires special equipment and programs to monitor them. These programs process and react to the continuous entry of data from different origins. Thus, the purpose of this study is to analyze the data produced by these biomedical devices, in this case the electrocardiogram (ECG). Processing uses a neural classifier, Kohonen competitive neural networks, detecting if the ECG shows any cardiac arrhythmia. In fact, it is possible to classify an ECG signal and thereby detect if it is exhibiting or not any alteration, according to normality.
Influence of ECG measurement accuracy on ECG diagnostic statements.
Zywietz, C; Celikag, D; Joseph, G
1996-01-01
Computer analysis of electrocardiograms (ECGs) provides a large amount of ECG measurement data, which may be used for diagnostic classification and storage in ECG databases. Until now, neither error limits for ECG measurements have been specified nor has their influence on diagnostic statements been systematically investigated. An analytical method is presented to estimate the influence of measurement errors on the accuracy of diagnostic ECG statements. Systematic (offset) errors will usually result in an increase of false positive or false negative statements since they cause a shift of the working point on the receiver operating characteristics curve. Measurement error dispersion broadens the distribution function of discriminative measurement parameters and, therefore, usually increases the overlap between discriminative parameters. This results in a flattening of the receiver operating characteristics curve and an increase of false positive and false negative classifications. The method developed has been applied to ECG conduction defect diagnoses by using the proposed International Electrotechnical Commission's interval measurement tolerance limits. These limits appear too large because more than 30% of false positive atrial conduction defect statements and 10-18% of false intraventricular conduction defect statements could be expected due to tolerated measurement errors. To assure long-term usability of ECG measurement databases, it is recommended that systems provide its error tolerance limits obtained on a defined test set.
MS-QI: A Modulation Spectrum-Based ECG Quality Index for Telehealth Applications.
Tobon V, Diana P; Falk, Tiago H; Maier, Martin
2016-08-01
As telehealth applications emerge, the need for accurate and reliable biosignal quality indices has increased. One typical modality used in remote patient monitoring is the electrocardiogram (ECG), which is inherently susceptible to several different noise sources, including environmental (e.g., powerline interference), experimental (e.g., movement artifacts), and physiological (e.g., muscle and breathing artifacts). Accurate measurement of ECG quality can allow for automated decision support systems to make intelligent decisions about patient conditions. This is particularly true for in-home monitoring applications, where the patient is mobile and the ECG signal can be severely corrupted by movement artifacts. In this paper, we propose an innovative ECG quality index based on the so-called modulation spectral signal representation. The representation quantifies the rate of change of ECG spectral components, which are shown to be different from the rate of change of typical ECG noise sources. The proposed modulation spectral-based quality index, MS-QI, was tested on 1) synthetic ECG signals corrupted by varying levels of noise, 2) single-lead recorded data using the Hexoskin garment during three activity levels (sitting, walking, running), 3) 12-lead recorded data using conventional ECG machines (Computing in Cardiology 2011 dataset), and 4) two-lead ambulatory ECG recorded from arrhythmia patients (MIT-BIH Arrhythmia Database). Experimental results showed the proposed index outperforming two conventional benchmark quality measures, particularly in the scenarios involving recorded data in real-world environments.
Novel technical solutions for wireless ECG transmission & analysis in the age of the internet cloud.
Al-Zaiti, Salah S; Shusterman, Vladimir; Carey, Mary G
2013-01-01
Current guidelines recommend early reperfusion therapy for ST-elevation myocardial infarction (STEMI) within 90 min of first medical encounter. Telecardiology entails the use of advanced communication technologies to transmit the prehospital 12-lead electrocardiogram (ECG) to offsite cardiologists for early triage to the cath lab; which has been shown to dramatically reduce door-to-balloon time and total mortality. However, hospitals often find adopting ECG transmission technologies very challenging. The current review identifies seven major technical challenges of prehospital ECG transmission, including: paramedics inconvenience and transport delay; signal noise and interpretation errors; equipment malfunction and transmission failure; reliability of mobile phone networks; lack of compliance with the standards of digital ECG formats; poor integration with electronic medical records; and costly hardware and software pre-requisite installation. Current and potential solutions to address each of these technical challenges are discussed in details and include: automated ECG transmission protocols; annotatable waveform-based ECGs; optimal routing solutions; and the use of cloud computing systems rather than vendor-specific processing stations. Nevertheless, strategies to monitor transmission effectiveness and patient outcomes are essential to sustain initial gains of implementing ECG transmission technologies. © 2013.
A Precise Drunk Driving Detection Using Weighted Kernel Based on Electrocardiogram.
Wu, Chung Kit; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei
2016-05-09
Globally, 1.2 million people die and 50 million people are injured annually due to traffic accidents. These traffic accidents cost $500 billion dollars. Drunk drivers are found in 40% of the traffic crashes. Existing drunk driving detection (DDD) systems do not provide accurate detection and pre-warning concurrently. Electrocardiogram (ECG) is a proven biosignal that accurately and simultaneously reflects human's biological status. In this letter, a classifier for DDD based on ECG is investigated in an attempt to reduce traffic accidents caused by drunk drivers. At this point, it appears that there is no known research or literature found on ECG classifier for DDD. To identify drunk syndromes, the ECG signals from drunk drivers are studied and analyzed. As such, a precise ECG-based DDD (ECG-DDD) using a weighted kernel is developed. From the measurements, 10 key features of ECG signals were identified. To incorporate the important features, the feature vectors are weighted in the customization of kernel functions. Four commonly adopted kernel functions are studied. Results reveal that weighted feature vectors improve the accuracy by 11% compared to the computation using the prime kernel. Evaluation shows that ECG-DDD improved the accuracy by 8% to 18% compared to prevailing methods.
Rautaharju, Pentti M; Zhang, Zhu-ming; Gregg, Richard E; Haisty, Wesley K; Z Vitolins, Mara; Curtis, Anne B; Warren, James; Horaĉek, Milan B; Zhou, Sophia H; Soliman, Elsayed Z
2013-01-01
Substantial new information has emerged recently about the prognostic value for a variety of new ECG variables. The objective of the present study was to establish reference standards for these novel risk predictors in a large, ethnically diverse cohort of healthy women from the Women's Health Initiative (WHI) study. The study population consisted of 36,299 healthy women. Racial differences in rate-adjusted QT end (QT(ea)) and QT peak (QT(pa)) intervals as linear functions of RR were small, leading to the conclusion that 450 and 390 ms are applicable as thresholds for prolonged and shortened QT(ea) and similarly, 365 and 295 ms for prolonged and shortened QT(pa), respectively. As a threshold for increased dispersion of global repolarization (T(peak)T(end) interval), 110 ms was established for white and Hispanic women and 120 ms for African-American and Asian women. ST elevation and depression values for the monitoring leads of each person with limb electrodes at Mason-Likar positions and chest leads at level of V1 and V2 were first computed from standard leads using lead transformation coefficients derived from 892 body surface maps, and subsequently normal standards were determined for the monitoring leads, including vessel-specific bipolar left anterior descending, left circumflex artery and right coronary artery leads. The results support the choice 150 μV as a tentative threshold for abnormal ST-onset elevation for all monitoring leads. Body mass index (BMI) had a profound effect on Cornell voltage and Sokolow-Lyon voltage in all racial groups and their utility for left ventricular hypertrophy classification remains open. Common thresholds for all racial groups are applicable for QT(ea), and QT(pa) intervals and ST elevation. Race-specific normal standards are required for many other ECG parameters. Copyright © 2013 Elsevier Inc. All rights reserved.
Ozawa, Yoshiyuki; Hara, Masaki; Nakagawa, Motoo; Shibamoto, Yuta
2016-01-01
Preoperative evaluation of invasion to the adjacent organs is important for the thymic epithelial tumors on CT. The purpose of our study was to evaluate the utility of electrocardiography (ECG)-gated CT for assessing thymic epithelial tumors with regard to the motion artifacts produced and the preoperative diagnostic accuracy of the technique. Forty thymic epithelial tumors (36 thymomas and 4 thymic carcinomas) were examined with ECG-gated contrast-enhanced CT using a dual source scanner. The scan delay after the contrast media injection was 30 s for the non-ECG-gated CT and 100 s for the ECG-gated CT. Two radiologists blindly evaluated both the non-ECG-gated and ECG-gated CT images for motion artifacts and determined whether the tumors had invaded adjacent structures (mediastinal fat, superior vena cava, brachiocephalic veins, aorta, pulmonary artery, pericardium, or lungs) on each image. Motion artifacts were evaluated using a 3-grade scale. Surgical and pathological findings were used as a reference standard for tumor invasion. Motion artifacts were significantly reduced for all structures by ECG gating ( p =0.0089 for the lungs and p <0.0001 for the other structures). Non-ECG-gated CT and ECG-gated CT demonstrated 79% and 95% accuracy, respectively, during assessments of pericardial invasion ( p =0.03). ECG-gated CT reduced the severity of motion artifacts and might be useful for preoperative assessment whether thymic epithelial tumors have invaded adjacent structures.
Ozawa, Yoshiyuki; Hara, Masaki; Nakagawa, Motoo; Shibamoto, Yuta
2016-01-01
Summary Background Preoperative evaluation of invasion to the adjacent organs is important for the thymic epithelial tumors on CT. The purpose of our study was to evaluate the utility of electrocardiography (ECG)-gated CT for assessing thymic epithelial tumors with regard to the motion artifacts produced and the preoperative diagnostic accuracy of the technique. Material/Methods Forty thymic epithelial tumors (36 thymomas and 4 thymic carcinomas) were examined with ECG-gated contrast-enhanced CT using a dual source scanner. The scan delay after the contrast media injection was 30 s for the non-ECG-gated CT and 100 s for the ECG-gated CT. Two radiologists blindly evaluated both the non-ECG-gated and ECG-gated CT images for motion artifacts and determined whether the tumors had invaded adjacent structures (mediastinal fat, superior vena cava, brachiocephalic veins, aorta, pulmonary artery, pericardium, or lungs) on each image. Motion artifacts were evaluated using a 3-grade scale. Surgical and pathological findings were used as a reference standard for tumor invasion. Results Motion artifacts were significantly reduced for all structures by ECG gating (p=0.0089 for the lungs and p<0.0001 for the other structures). Non-ECG-gated CT and ECG-gated CT demonstrated 79% and 95% accuracy, respectively, during assessments of pericardial invasion (p=0.03). Conclusions ECG-gated CT reduced the severity of motion artifacts and might be useful for preoperative assessment whether thymic epithelial tumors have invaded adjacent structures. PMID:27920842
Antiperovitch, Pavel; Zareba, Wojciech; Steinberg, Jonathan S; Bacharova, Ljuba; Tereshchenko, Larisa G; Farre, Jeronimo; Nikus, Kjell; Ikeda, Takanori; Baranchuk, Adrian
2018-03-01
Despite its importance in everyday clinical practice, the ability of physicians to interpret electrocardiograms (ECGs) is highly variable. ECG patterns are often misdiagnosed, and electrocardiographic emergencies are frequently missed, leading to adverse patient outcomes. Currently, many medical education programs lack an organized curriculum and competency assessment to ensure trainees master this essential skill. ECG patterns that were previously mentioned in literature were organized into groups from A to D based on their clinical importance and distributed among levels of training. Incremental versions of this organization were circulated among members of the International Society of Electrocardiology and the International Society of Holter and Noninvasive Electrocardiology until complete consensus was reached. We present reasonably attainable ECG interpretation competencies for undergraduate and postgraduate trainees. Previous literature suggests that methods of teaching ECG interpretation are less important and can be selected based on the available resources of each education program and student preference. The evidence clearly favors summative trainee evaluation methods, which would facilitate learning and ensure that appropriate competencies are acquired. Resources should be allocated to ensure that every trainee reaches their training milestones and should ensure that no electrocardiographic emergency (class A condition) is ever missed. We hope that these guidelines will inform medical education programs and encourage them to allocate sufficient resources and develop organized curricula. Assessments must be in place to ensure trainees acquire the level-appropriate ECG interpretation skills that are required for safe clinical practice. © 2017 Society of Hospital Medicine.
A harmonic linear dynamical system for prominent ECG feature extraction.
Thi, Ngoc Anh Nguyen; Yang, Hyung-Jeong; Kim, SunHee; Do, Luu Ngoc
2014-01-01
Unsupervised mining of electrocardiography (ECG) time series is a crucial task in biomedical applications. To have efficiency of the clustering results, the prominent features extracted from preprocessing analysis on multiple ECG time series need to be investigated. In this paper, a Harmonic Linear Dynamical System is applied to discover vital prominent features via mining the evolving hidden dynamics and correlations in ECG time series. The discovery of the comprehensible and interpretable features of the proposed feature extraction methodology effectively represents the accuracy and the reliability of clustering results. Particularly, the empirical evaluation results of the proposed method demonstrate the improved performance of clustering compared to the previous main stream feature extraction approaches for ECG time series clustering tasks. Furthermore, the experimental results on real-world datasets show scalability with linear computation time to the duration of the time series.
Amer, Hamid; Niaz, Khalid; Hatazawa, Jun; Gasmelseed, Ahmed; Samiri, Hussain Al; Al Othman, Maram; Hammad, Mai Al
2017-11-01
We sought to determine the prognostic importance of adenosine-induced ischemic ECG changes in patients with normal single-photon emission computed tomography myocardial perfusion images (MPI). We carried out a retrospective analysis of 765 patients undergoing adenosine MPI between January 2013 and January 2015. Patients with baseline ECG abnormalities and/or abnormal scan were excluded. Overall, 67 (8.7%) patients had ischemic ECG changes during adenosine infusion in the form of ST depression of 1 mm or more. Of these, 29 [43% (3.8% of all patients)] had normal MPI (positive ECG group). An age-matched and sex-matched group of 108 patients with normal MPI without ECG changes served as control participants (negative ECG group). During a mean follow-up duration of 33.3±6.1 months, patients in the positive ECG group did not have significantly more adverse cardiac events than those in the negative ECG group. One (0.9%) patient in the negative ECG group had a nonfatal myocardial infarction (0.7% annual event rate after a negative MPI). Also in this group, two (1.8%) patients admitted with a diagnosis of CAD where they have been ruled out by angiography. A fourth case in this, in the negative ECG group, was admitted because of heart failure that proved to be secondary to a pulmonary cause and not CAD. A case only in the positive ECG group was admitted as a CAD that was ruled out by coronary angiography. Patients with normal myocardial perfusion scintigraphy in whom ST-segment depression develops during adenosine stress test appear to have no increased risk for future cardiac events compared with similar patients without ECG evidence of ischemia.
Pilot study analyzing automated ECG screening of hypertrophic cardiomyopathy.
Campbell, Matthew J; Zhou, Xuefu; Han, Chia; Abrishami, Hedayat; Webster, Gregory; Miyake, Christina Y; Sower, Christopher T; Anderson, Jeffrey B; Knilans, Timothy K; Czosek, Richard J
2017-06-01
Hypertrophic cardiomyopathy (HCM) is one of the leading causes of sudden cardiac death in athletes. However, preparticipation ECG screening has often been criticized for failing to meet cost-effectiveness thresholds, in part because of high false-positive rates and the cost of ECG screening itself. The purpose of this study was to assess the testing characteristics of an automated ECG algorithm designed to screen for HCM in a multi-institutional pediatric cohort. ECGs from patients with HCM aged 12 to 20 years from 3 pediatric institutions were screened for ECG criteria for HCM using a previously described automated computer algorithm developed specifically for HCM ECG screening. The results were compared to a known healthy pediatric cohort. The studies then were read by trained electrophysiologists using standard ECG criteria and compared to the results of automated screening. One hundred twenty-eight ECGs from unique patients with phenotypic HCM were obtained and compared with 256 studies from healthy control patients matched in 2:1 fashion. When presented with the ECGs, the non-voltage-based algorithm resulted in 81.2% sensitivity and 90.7% specificity. A trained electrophysiologist read the same data according to the Seattle Criteria, with 71% sensitivity with 95.7% specificity. The sensitivity of screening as well as the components of the ECG screening itself varied by institution. This pilot study demonstrates a potential for automated ECG screening algorithms to detect HCM with testing characteristics similar to that of a trained electrophysiologist. In addition, there appear to be differences in ECG characteristics between patient populations, which may account for the difficulties in universal screening. Copyright © 2017 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.
Chakraborty, Amit; von Herrmann, Paul F; Embertson, Ryan E; Landwehr, Kevin P; Winkler, Michael A
2016-01-01
A case of a tornado victim with a delayed presentation of injury to the aortic isthmus is discussed. Tornado forces resemble the forces of high energy explosions, and the injuries that can occur as a result of these forces can be bizarre. The patient presented with the unique computed tomography (CT) findings of isolated pseudoaneurysm of the thoracic aorta in the absence of other traumatic injury to the thorax. Equivocal results of the initial CT aortogram (CTA) were confirmed with ECG-synchronized CTA (ECG-CTA), demonstrating the superiority of ECG-CTA as compared to standard CTA. Copyright © 2016 Elsevier Inc. All rights reserved.
Novel Tool for Complete Digitization of Paper Electrocardiography Data.
Ravichandran, Lakshminarayan; Harless, Chris; Shah, Amit J; Wick, Carson A; Mcclellan, James H; Tridandapani, Srini
We present a Matlab-based tool to convert electrocardiography (ECG) information from paper charts into digital ECG signals. The tool can be used for long-term retrospective studies of cardiac patients to study the evolving features with prognostic value. To perform the conversion, we: 1) detect the graphical grid on ECG charts using grayscale thresholding; 2) digitize the ECG signal based on its contour using a column-wise pixel scan; and 3) use template-based optical character recognition to extract patient demographic information from the paper ECG in order to interface the data with the patients' medical record. To validate the digitization technique: 1) correlation between the digital signals and signals digitized from paper ECG are performed and 2) clinically significant ECG parameters are measured and compared from both the paper-based ECG signals and the digitized ECG. The validation demonstrates a correlation value of 0.85-0.9 between the digital ECG signal and the signal digitized from the paper ECG. There is a high correlation in the clinical parameters between the ECG information from the paper charts and digitized signal, with intra-observer and inter-observer correlations of 0.8-0.9 (p < 0.05), and kappa statistics ranging from 0.85 (inter-observer) to 1.00 (intra-observer). The important features of the ECG signal, especially the QRST complex and the associated intervals, are preserved by obtaining the contour from the paper ECG. The differences between the measures of clinically important features extracted from the original signal and the reconstructed signal are insignificant, thus highlighting the accuracy of this technique. Using this type of ECG digitization tool to carry out retrospective studies on large databases, which rely on paper ECG records, studies of emerging ECG features can be performed. In addition, this tool can be used to potentially integrate digitized ECG information with digital ECG analysis programs and with the patient's electronic medical record.
Low-complexity R-peak detection for ambulatory fetal monitoring.
Rooijakkers, Michael J; Rabotti, Chiara; Oei, S Guid; Mischi, Massimo
2012-07-01
Non-invasive fetal health monitoring during pregnancy is becoming increasingly important because of the increasing number of high-risk pregnancies. Despite recent advances in signal-processing technology, which have enabled fetal monitoring during pregnancy using abdominal electrocardiogram (ECG) recordings, ubiquitous fetal health monitoring is still unfeasible due to the computational complexity of noise-robust solutions. In this paper, an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, without reducing the R-peak detection performance compared to the existing R-peak detection schemes. Validation of the algorithm is performed on three manually annotated datasets. With a detection error rate of 0.23%, 1.32% and 9.42% on the MIT/BIH Arrhythmia and in-house maternal and fetal databases, respectively, the detection rate of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.
NASA Astrophysics Data System (ADS)
Yu, Huidan (Whitney); Chen, Xi; Chen, Rou; Wang, Zhiqiang; Lin, Chen; Kralik, Stephen; Zhao, Ye
2015-11-01
In this work, we demonstrate the validity of 4-D patient-specific computational hemodynamics (PSCH) based on 3-D time-of-flight (TOF) MR angiography (MRA) and 2-D electrocardiogram (ECG) gated phase contrast (PC) images. The mesoscale lattice Boltzmann method (LBM) is employed to segment morphological arterial geometry from TOF MRA, to extract velocity profiles from ECG PC images, and to simulate fluid dynamics on a unified GPU accelerated computational platform. Two healthy volunteers are recruited to participate in the study. For each volunteer, a 3-D high resolution TOF MRA image and 10 2-D ECG gated PC images are acquired to provide the morphological geometry and the time-varying flow velocity profiles for necessary inputs of the PSCH. Validation results will be presented through comparisons of LBM vs. 4D Flow Software for flow rates and LBM simulation vs. MRA measurement for blood flow velocity maps. Indiana University Health (IUH) Values Fund.
Iribarren, Carlos; Round, Alfred D; Lu, Meng; Okin, Peter M; McNulty, Edward J
2017-10-05
ECG left ventricular hypertrophy (LVH) is a well-known predictor of cardiovascular disease. However, no prior study has characterized patterns of presence/absence of ECG LVH ("ECG LVH trajectories") across the adult lifespan in both sexes and across ethnicities. We examined: (1) correlates of ECG LVH trajectories; (2) the association of ECG LVH trajectories with incident coronary heart disease, transient ischemic attack, ischemic stroke, hemorrhagic stroke, and heart failure; and (3) reclassification of cardiovascular disease risk using ECG LVH trajectories. We performed a cohort study among 75 412 men and 107 954 women in the Northern California Kaiser Permanente Medical Care Program who had available longitudinal exposures of ECG LVH and covariates, followed for a median of 4.8 (range <1-9.3) years. ECG LVH was measured by Cornell voltage-duration product. Adverse trajectories of ECG LVH (persistent, new development, or variable pattern) were more common among blacks and Native American men and were independently related to incident cardiovascular disease with hazard ratios ranging from 1.2 for ECG LVH variable pattern and transient ischemic attack in women to 2.8 for persistent ECG LVH and heart failure in men. ECG LVH trajectories reclassified 4% and 7% of men and women with intermediate coronary heart disease risk, respectively. ECG LVH trajectories were significant indicators of coronary heart disease, stroke, and heart failure risk, independently of level and change in cardiovascular disease risk factors, and may have clinical utility. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.
Yin, Xinxin; Zheng, Wen; Ma, Jingjing; Hao, Panpan
2016-01-01
Background Both coronary computed tomography angiography (CCTA) and exercise electrocardiography (ExECG) are non-invasive testing methods for the evaluation of coronary artery disease (CAD). However, there was controversy on the diagnostic performance of these methods due to the limited data in each single study. Therefore, we performed a meta-analysis to address these issues. Methods We searched PubMed and Embase databases up to May 22, 2015. Two authors identified eligible studies, extracted data and accessed quality. Pooled estimation of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), summary receiver-operating characteristic curve (SROC) and the area under curve (AUC) of CCTA and ExECG for the diagnosis of CAD were calculated using Stata, Meta-Disc and Review Manager statistical software. Results Seven articles were included. Pooled sensitivity of CCTA and ExECG were 0.98 [95% confidence intervals (CIs): 0.95–0.99] and 0.66 (95% CIs: 0.59–0.72); pooled specificity of CCTA and ExECG were 0.84 (95% CIs: 0.81–0.87) and 0.75 (95% CIs: 0.71–0.79); pooled DOR of CCTA and ExECG were 110.24 (95% CIs: 35.07–346.55) and 6.28 (95% CIs: 2.06–19.13); and AUC of CCTA and ExECG were 0.9950±0.0046 and 0.7727±0.0638, respectively. There is no heterogeneity caused by threshold effect in CCTA or ExECG analysis. The Deeks’ test showed no potential publication bias (P=0.17). Conclusions CCTA has better diagnostic performance than ExECG in the evaluation of CAD, which can provide a better solution for the clinical problem of the diagnosis for CAD. PMID:27499958
Miao, Fen; Cheng, Yayu; He, Yi; He, Qingyun; Li, Ye
2015-05-19
Continuously monitoring the ECG signals over hours combined with activity status is very important for preventing cardiovascular diseases. A traditional ECG holter is often inconvenient to carry because it has many electrodes attached to the chest and because it is heavy. This work proposes a wearable, low power context-aware ECG monitoring system integrated built-in kinetic sensors of the smartphone with a self-designed ECG sensor. The wearable ECG sensor is comprised of a fully integrated analog front-end (AFE), a commercial micro control unit (MCU), a secure digital (SD) card, and a Bluetooth module. The whole sensor is very small with a size of only 58 × 50 × 10 mm for wearable monitoring application due to the AFE design, and the total power dissipation in a full round of ECG acquisition is only 12.5 mW. With the help of built-in kinetic sensors of the smartphone, the proposed system can compute and recognize user's physical activity, and thus provide context-aware information for the continuous ECG monitoring. The experimental results demonstrated the performance of proposed system in improving diagnosis accuracy for arrhythmias and identifying the most common abnormal ECG patterns in different activities. In conclusion, we provide a wearable, accurate and energy-efficient system for long-term and context-aware ECG monitoring without any extra cost on kinetic sensor design but with the help of the widespread smartphone.
Unsupervised feature relevance analysis applied to improve ECG heartbeat clustering.
Rodríguez-Sotelo, J L; Peluffo-Ordoñez, D; Cuesta-Frau, D; Castellanos-Domínguez, G
2012-10-01
The computer-assisted analysis of biomedical records has become an essential tool in clinical settings. However, current devices provide a growing amount of data that often exceeds the processing capacity of normal computers. As this amount of information rises, new demands for more efficient data extracting methods appear. This paper addresses the task of data mining in physiological records using a feature selection scheme. An unsupervised method based on relevance analysis is described. This scheme uses a least-squares optimization of the input feature matrix in a single iteration. The output of the algorithm is a feature weighting vector. The performance of the method was assessed using a heartbeat clustering test on real ECG records. The quantitative cluster validity measures yielded a correctly classified heartbeat rate of 98.69% (specificity), 85.88% (sensitivity) and 95.04% (general clustering performance), which is even higher than the performance achieved by other similar ECG clustering studies. The number of features was reduced on average from 100 to 18, and the temporal cost was a 43% lower than in previous ECG clustering schemes. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Steganography in arrhythmic electrocardiogram signal.
Edward Jero, S; Ramu, Palaniappan; Ramakrishnan, S
2015-08-01
Security and privacy of patient data is a vital requirement during exchange/storage of medical information over communication network. Steganography method hides patient data into a cover signal to prevent unauthenticated accesses during data transfer. This study evaluates the performance of ECG steganography to ensure secured transmission of patient data where an abnormal ECG signal is used as cover signal. The novelty of this work is to hide patient data into two dimensional matrix of an abnormal ECG signal using Discrete Wavelet Transform and Singular Value Decomposition based steganography method. A 2D ECG is constructed according to Tompkins QRS detection algorithm. The missed R peaks are computed using RR interval during 2D conversion. The abnormal ECG signals are obtained from the MIT-BIH arrhythmia database. Metrics such as Peak Signal to Noise Ratio, Percentage Residual Difference, Kullback-Leibler distance and Bit Error Rate are used to evaluate the performance of the proposed approach.
Hesar, Hamed Danandeh; Mohebbi, Maryam
2017-05-01
In this paper, a model-based Bayesian filtering framework called the "marginalized particle-extended Kalman filter (MP-EKF) algorithm" is proposed for electrocardiogram (ECG) denoising. This algorithm does not have the extended Kalman filter (EKF) shortcoming in handling non-Gaussian nonstationary situations because of its nonlinear framework. In addition, it has less computational complexity compared with particle filter. This filter improves ECG denoising performance by implementing marginalized particle filter framework while reducing its computational complexity using EKF framework. An automatic particle weighting strategy is also proposed here that controls the reliance of our framework to the acquired measurements. We evaluated the proposed filter on several normal ECGs selected from MIT-BIH normal sinus rhythm database. To do so, artificial white Gaussian and colored noises as well as nonstationary real muscle artifact (MA) noise over a range of low SNRs from 10 to -5 dB were added to these normal ECG segments. The benchmark methods were the EKF and extended Kalman smoother (EKS) algorithms which are the first model-based Bayesian algorithms introduced in the field of ECG denoising. From SNR viewpoint, the experiments showed that in the presence of Gaussian white noise, the proposed framework outperforms the EKF and EKS algorithms in lower input SNRs where the measurements and state model are not reliable. Owing to its nonlinear framework and particle weighting strategy, the proposed algorithm attained better results at all input SNRs in non-Gaussian nonstationary situations (such as presence of pink noise, brown noise, and real MA). In addition, the impact of the proposed filtering method on the distortion of diagnostic features of the ECG was investigated and compared with EKF/EKS methods using an ECG diagnostic distortion measure called the "Multi-Scale Entropy Based Weighted Distortion Measure" or MSEWPRD. The results revealed that our proposed algorithm had the lowest MSEPWRD for all noise types at low input SNRs. Therefore, the morphology and diagnostic information of ECG signals were much better conserved compared with EKF/EKS frameworks, especially in non-Gaussian nonstationary situations.
III Lead ECG Pulse Measurement Sensor
NASA Astrophysics Data System (ADS)
Thangaraju, S. K.; Munisamy, K.
2015-09-01
Heart rate sensing is very important. Method of measuring heart pulse by using an electrocardiogram (ECG) technique is described. Electrocardiogram is a measurement of the potential difference (the electrical pulse) generated by a cardiac tissue, mainly the heart. This paper also reports the development of a three lead ECG hardware system that would be the basis of developing a more cost efficient, portable and easy to use ECG machine. Einthoven's Three Lead method [1] is used for ECG signal extraction. Using amplifiers such as the instrumentation amplifier AD620BN and the conventional operational amplifier Ua741 that would be used to amplify the ECG signal extracted develop this system. The signal would then be filtered from noise using Butterworth filter techniques to obtain optimum output. Also a right leg guard was implemented as a safety feature to this system. Simulation was carried out for development of the system using P-spice Program.
Systolic time interval data acquisition system. Specialized cardiovascular studies
NASA Technical Reports Server (NTRS)
Baker, J. T.
1976-01-01
The development of a data acquisition system for noninvasive measurement of systolic time intervals is described. R-R interval from the ECG determines instantaneous heart rate prior to the beat to be measured. Total electromechanical systole (Q-S2) is measured from the onset of the ECG Q-wave to the onset of the second heart sound (S2). Ejection time (ET or LVET) is measured from the onset of carotid upstroke to the incisure. Pre-ejection period (PEP) is computed by subtracting ET from Q-S2. PEP/ET ratio is computed directly.
A ECG Signal Gathering and Displaying System Based on AVR
NASA Astrophysics Data System (ADS)
Ning, Li; Ruilan, Zhang; Jian, Liu; Xiaochen, Wang; Shuying, Chen; Zhuolin, Lang
2017-12-01
This article introduces a kind of system which is based on the AVR to acquire the data of ECG. Such system using the A/D function of ATmega8 chip and the lattice graph LCD to design ECG heart acquisition satisfies the demands above. This design gives a composition of hardware and programming of software about the system in detail which has mainly realized the real-time gathering, the amplifier, the filter, the A/D transformation and the LCD display. Since the AVR includes A/D transformation function and support embedded C language programming, it reduces the peripheral circuit, further more it also decreases the time to design and debug this system.
Novel Tool for Complete Digitization of Paper Electrocardiography Data
Harless, Chris; Shah, Amit J.; Wick, Carson A.; Mcclellan, James H.
2013-01-01
Objective: We present a Matlab-based tool to convert electrocardiography (ECG) information from paper charts into digital ECG signals. The tool can be used for long-term retrospective studies of cardiac patients to study the evolving features with prognostic value. Methods and procedures: To perform the conversion, we: 1) detect the graphical grid on ECG charts using grayscale thresholding; 2) digitize the ECG signal based on its contour using a column-wise pixel scan; and 3) use template-based optical character recognition to extract patient demographic information from the paper ECG in order to interface the data with the patients' medical record. To validate the digitization technique: 1) correlation between the digital signals and signals digitized from paper ECG are performed and 2) clinically significant ECG parameters are measured and compared from both the paper-based ECG signals and the digitized ECG. Results: The validation demonstrates a correlation value of 0.85–0.9 between the digital ECG signal and the signal digitized from the paper ECG. There is a high correlation in the clinical parameters between the ECG information from the paper charts and digitized signal, with intra-observer and inter-observer correlations of 0.8–0.9 \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$({\\rm p}<{0.05})$\\end{document}, and kappa statistics ranging from 0.85 (inter-observer) to 1.00 (intra-observer). Conclusion: The important features of the ECG signal, especially the QRST complex and the associated intervals, are preserved by obtaining the contour from the paper ECG. The differences between the measures of clinically important features extracted from the original signal and the reconstructed signal are insignificant, thus highlighting the accuracy of this technique. Clinical impact: Using this type of ECG digitization tool to carry out retrospective studies on large databases, which rely on paper ECG records, studies of emerging ECG features can be performed. In addition, this tool can be used to potentially integrate digitized ECG information with digital ECG analysis programs and with the patient's electronic medical record. PMID:26594601
Schulze, Walther H. W.; Jiang, Yuan; Wilhelms, Mathias; Luik, Armin; Dössel, Olaf; Seemann, Gunnar
2015-01-01
In case of chest pain, immediate diagnosis of myocardial ischemia is required to respond with an appropriate treatment. The diagnostic capability of the electrocardiogram (ECG), however, is strongly limited for ischemic events that do not lead to ST elevation. This computational study investigates the potential of different electrode setups in detecting early ischemia at 10 minutes after onset: standard 3-channel and 12-lead ECG as well as body surface potential maps (BSPMs). Further, it was assessed if an additional ECG electrode with optimized position or the right-sided Wilson leads can improve sensitivity of the standard 12-lead ECG. To this end, a simulation study was performed for 765 different locations and sizes of ischemia in the left ventricle. Improvements by adding a single, subject specifically optimized electrode were similar to those of the BSPM: 2–11% increased detection rate depending on the desired specificity. Adding right-sided Wilson leads had negligible effect. Absence of ST deviation could not be related to specific locations of the ischemic region or its transmurality. As alternative to the ST time integral as a feature of ST deviation, the K point deviation was introduced: the baseline deviation at the minimum of the ST-segment envelope signal, which increased 12-lead detection rate by 7% for a reasonable threshold. PMID:26587538
Loewe, Axel; Schulze, Walther H W; Jiang, Yuan; Wilhelms, Mathias; Luik, Armin; Dössel, Olaf; Seemann, Gunnar
2015-01-01
In case of chest pain, immediate diagnosis of myocardial ischemia is required to respond with an appropriate treatment. The diagnostic capability of the electrocardiogram (ECG), however, is strongly limited for ischemic events that do not lead to ST elevation. This computational study investigates the potential of different electrode setups in detecting early ischemia at 10 minutes after onset: standard 3-channel and 12-lead ECG as well as body surface potential maps (BSPMs). Further, it was assessed if an additional ECG electrode with optimized position or the right-sided Wilson leads can improve sensitivity of the standard 12-lead ECG. To this end, a simulation study was performed for 765 different locations and sizes of ischemia in the left ventricle. Improvements by adding a single, subject specifically optimized electrode were similar to those of the BSPM: 2-11% increased detection rate depending on the desired specificity. Adding right-sided Wilson leads had negligible effect. Absence of ST deviation could not be related to specific locations of the ischemic region or its transmurality. As alternative to the ST time integral as a feature of ST deviation, the K point deviation was introduced: the baseline deviation at the minimum of the ST-segment envelope signal, which increased 12-lead detection rate by 7% for a reasonable threshold.
Detection of Cardiac Abnormalities from Multilead ECG using Multiscale Phase Alternation Features.
Tripathy, R K; Dandapat, S
2016-06-01
The cardiac activities such as the depolarization and the relaxation of atria and ventricles are observed in electrocardiogram (ECG). The changes in the morphological features of ECG are the symptoms of particular heart pathology. It is a cumbersome task for medical experts to visually identify any subtle changes in the morphological features during 24 hours of ECG recording. Therefore, the automated analysis of ECG signal is a need for accurate detection of cardiac abnormalities. In this paper, a novel method for automated detection of cardiac abnormalities from multilead ECG is proposed. The method uses multiscale phase alternation (PA) features of multilead ECG and two classifiers, k-nearest neighbor (KNN) and fuzzy KNN for classification of bundle branch block (BBB), myocardial infarction (MI), heart muscle defect (HMD) and healthy control (HC). The dual tree complex wavelet transform (DTCWT) is used to decompose the ECG signal of each lead into complex wavelet coefficients at different scales. The phase of the complex wavelet coefficients is computed and the PA values at each wavelet scale are used as features for detection and classification of cardiac abnormalities. A publicly available multilead ECG database (PTB database) is used for testing of the proposed method. The experimental results show that, the proposed multiscale PA features and the fuzzy KNN classifier have better performance for detection of cardiac abnormalities with sensitivity values of 78.12 %, 80.90 % and 94.31 % for BBB, HMD and MI classes. The sensitivity value of proposed method for MI class is compared with the state-of-art techniques from multilead ECG.
Gorodeski, Eiran Z.; Ishwaran, Hemant; Kogalur, Udaya B.; Blackstone, Eugene H.; Hsich, Eileen; Zhang, Zhu-ming; Vitolins, Mara Z.; Manson, JoAnn E.; Curb, J. David; Martin, Lisa W.; Prineas, Ronald J.; Lauer, Michael S.
2013-01-01
Background Simultaneous contribution of hundreds of electrocardiographic biomarkers to prediction of long-term mortality in post-menopausal women with clinically normal resting electrocardiograms (ECGs) is unknown. Methods and Results We analyzed ECGs and all-cause mortality in 33,144 women enrolled in Women’s Health Initiative trials, who were without baseline cardiovascular disease or cancer, and had normal ECGs by Minnesota and Novacode criteria. Four hundred and seventy seven ECG biomarkers, encompassing global and individual ECG findings, were measured using computer algorithms. During a median follow-up of 8.1 years (range for survivors 0.5–11.2 years), 1,229 women died. For analyses cohort was randomly split into derivation (n=22,096, deaths=819) and validation (n=11,048, deaths=410) subsets. ECG biomarkers, demographic, and clinical characteristics were simultaneously analyzed using both traditional Cox regression and Random Survival Forest (RSF), a novel algorithmic machine-learning approach. Regression modeling failed to converge. RSF variable selection yielded 20 variables that were independently predictive of long-term mortality, 14 of which were ECG biomarkers related to autonomic tone, atrial conduction, and ventricular depolarization and repolarization. Conclusions We identified 14 ECG biomarkers from amongst hundreds that were associated with long-term prognosis using a novel random forest variable selection methodology. These were related to autonomic tone, atrial conduction, ventricular depolarization, and ventricular repolarization. Quantitative ECG biomarkers have prognostic importance, and may be markers of subclinical disease in apparently healthy post-menopausal women. PMID:21862719
Interoperability in digital electrocardiography: harmonization of ISO/IEEE x73-PHD and SCP-ECG.
Trigo, Jesús D; Chiarugi, Franco; Alesanco, Alvaro; Martínez-Espronceda, Miguel; Serrano, Luis; Chronaki, Catherine E; Escayola, Javier; Martínez, Ignacio; García, José
2010-11-01
The ISO/IEEE 11073 (x73) family of standards is a reference frame for medical device interoperability. A draft for an ECG device specialization (ISO/IEEE 11073-10406-d02) has already been presented to the Personal Health Device (PHD) Working Group, and the Standard Communications Protocol for Computer-Assisted ElectroCardioGraphy (SCP-ECG) Standard for short-term diagnostic ECGs (EN1064:2005+A1:2007) has recently been approved as part of the x73 family (ISO 11073-91064:2009). These factors suggest the coordinated use of these two standards in foreseeable telecardiology environments, and hence the need to harmonize them. Such harmonization is the subject of this paper. Thus, a mapping of the mandatory attributes defined in the second draft of the ISO/IEEE 11073-10406-d02 and the minimum SCP-ECG fields is presented, and various other capabilities of the SCP-ECG Standard (such as the messaging part) are also analyzed from an x73-PHD point of view. As a result, this paper addresses and analyzes the implications of some inconsistencies in the coordinated use of these two standards. Finally, a proof-of-concept implementation of the draft x73-PHD ECG device specialization is presented, along with the conversion from x73-PHD to SCP-ECG. This paper, therefore, provides recommendations for future implementations of telecardiology systems that are compliant with both x73-PHD and SCP-ECG.
CAVIAR: a tool to improve serial analysis of the 12-lead electrocardiogram.
Berg, J; Fayn, J; Edenbrandt, L; Lundh, B; Malmström, P; Rubel, P
1995-09-01
An important part of an electrocardiogram (ECG) interpretation is the comparison between the present ECG and earlier recordings. The purpose of the present study was to evaluate a combination of two computer-based methods, synthesized vectorcardiogram (VCG) and CAVIAR, in this comparison. The methods were applied to a group of 38 normal subjects and to a group of 36 patients treated with anthracyclines. A fraction of these patients are likely to develop cardiac injury during or after the treatment, since anthracyclines are known to cause heart failure and cardiomyopathy. Two ECGs were recorded on each patient, one before and one after the treatment. On each normal subject, two ECGs were recorded with an interval of 8-9 years. A synthesized VCG was calculated from each ECG and the two synthesized VCGs from each subject were analysed with the CAVIAR method. The CAVIAR analysis is a quantitative method and normal limits for four measurements were established using the normal group. Values above these limits were more frequent in the patient group than in the normal group. The conventional ECGs were also analysed visually by an experience ECG interpreter without knowledge of the result of the CAVIAR analysis. No significant serial changes were found in 10 of the patients with high CAVIAR values. Changes in the ECGs were found in two patients with normal CAVIAR values. In summary, synthesized VCG and CAVIAR could be used to highlight small serial changes that are difficult to find in a visual analysis of ECGs.
Electrocardiographic interpretation skills of cardiology residents: are they competent?
Sibbald, Matthew; Davies, Edward G; Dorian, Paul; Yu, Eric H C
2014-12-01
Achieving competency at electrocardiogram (ECG) interpretation among cardiology subspecialty residents has traditionally focused on interpreting a target number of ECGs during training. However, there is little evidence to support this approach. Further, there are no data documenting the competency of ECG interpretation skills among cardiology residents, who become de facto the gold standard in their practice communities. We tested 29 Cardiology residents from all 3 years in a large training program using a set of 20 ECGs collected from a community cardiology practice over a 1-month period. Residents interpreted half of the ECGs using a standard analytic framework, and half using their own approach. Residents were scored on the number of correct and incorrect diagnoses listed. Overall diagnostic accuracy was 58%. Of 6 potentially life-threatening diagnoses, residents missed 36% (123 of 348) including hyperkalemia (81%), long QT (52%), complete heart block (35%), and ventricular tachycardia (19%). Residents provided additional inappropriate diagnoses on 238 ECGs (41%). Diagnostic accuracy was similar between ECGs interpreted using an analytic framework vs ECGs interpreted without an analytic framework (59% vs 58%; F(1,1333) = 0.26; P = 0.61). Cardiology resident proficiency at ECG interpretation is suboptimal. Despite the use of an analytic framework, there remain significant deficiencies in ECG interpretation among Cardiology residents. A more systematic method of addressing these important learning gaps is urgently needed. Copyright © 2014 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.
Barthelemy, Francois X; Segard, Julien; Fradin, Philippe; Hourdin, Nicolas; Batard, Eric; Pottier, Pierre; Potel, Gilles; Montassier, Emmanuel
2017-04-01
ECG interpretation is a pivotal skill to acquire during residency, especially for Emergency Department (ED) residents. Previous studies reported that ECG interpretation competency among residents was rather low. However, the optimal resource to improve ECG interpretation skills remains unclear. The aim of our study was to compare two teaching modalities to improve the ECG interpretation skills of ED residents: e-learning and lecture-based courses. The participants were first-year and second-year ED residents, assigned randomly to the two groups. The ED residents were evaluated by means of a precourse test at the beginning of the study and a postcourse test after the e-learning and lecture-based courses. These evaluations consisted of the interpretation of 10 different ECGs. We included 39 ED residents from four different hospitals. The precourse test showed that the overall average score of ECG interpretation was 40%. Nineteen participants were then assigned to the e-learning course and 20 to the lecture-based course. Globally, there was a significant improvement in ECG interpretation skills (accuracy score=55%, P=0.0002). However, this difference was not significant between the two groups (P=0.14). Our findings showed that the ECG interpretation was not optimal and that our e-learning program may be an effective tool for enhancing ECG interpretation skills among ED residents. A large European study should be carried out to evaluate ECG interpretation skills among ED residents before the implementation of ECG learning, including e-learning strategies, during ED residency.
Using ordinal partition transition networks to analyze ECG data
NASA Astrophysics Data System (ADS)
Kulp, Christopher W.; Chobot, Jeremy M.; Freitas, Helena R.; Sprechini, Gene D.
2016-07-01
Electrocardiogram (ECG) data from patients with a variety of heart conditions are studied using ordinal pattern partition networks. The ordinal pattern partition networks are formed from the ECG time series by symbolizing the data into ordinal patterns. The ordinal patterns form the nodes of the network and edges are defined through the time ordering of the ordinal patterns in the symbolized time series. A network measure, called the mean degree, is computed from each time series-generated network. In addition, the entropy and number of non-occurring ordinal patterns (NFP) is computed for each series. The distribution of mean degrees, entropies, and NFPs for each heart condition studied is compared. A statistically significant difference between healthy patients and several groups of unhealthy patients with varying heart conditions is found for the distributions of the mean degrees, unlike for any of the distributions of the entropies or NFPs.
Carrault, G; Cordier, M-O; Quiniou, R; Wang, F
2003-07-01
This paper proposes a novel approach to cardiac arrhythmia recognition from electrocardiograms (ECGs). ECGs record the electrical activity of the heart and are used to diagnose many heart disorders. The numerical ECG is first temporally abstracted into series of time-stamped events. Temporal abstraction makes use of artificial neural networks to extract interesting waves and their features from the input signals. A temporal reasoner called a chronicle recogniser processes such series in order to discover temporal patterns called chronicles which can be related to cardiac arrhythmias. Generally, it is difficult to elicit an accurate set of chronicles from a doctor. Thus, we propose to learn automatically from symbolic ECG examples the chronicles discriminating the arrhythmias belonging to some specific subset. Since temporal relationships are of major importance, inductive logic programming (ILP) is the tool of choice as it enables first-order relational learning. The approach has been evaluated on real ECGs taken from the MIT-BIH database. The performance of the different modules as well as the efficiency of the whole system is presented. The results are rather good and demonstrate that integrating numerical techniques for low level perception and symbolic techniques for high level classification is very valuable.
Sudarshan, Vidya K; Acharya, U Rajendra; Oh, Shu Lih; Adam, Muhammad; Tan, Jen Hong; Chua, Chua Kuang; Chua, Kok Poo; Tan, Ru San
2017-04-01
Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant for the prediction of congestive heart failure (CHF). ECG signal analysis carried out using computer-aided techniques can speed up the diagnosis process and aid in the proper management of CHF patients. Therefore, in this work, dual tree complex wavelets transform (DTCWT)-based methodology is proposed for an automated identification of ECG signals exhibiting CHF from normal. In the experiment, we have performed a DTCWT on ECG segments of 2s duration up to six levels to obtain the coefficients. From these DTCWT coefficients, statistical features are extracted and ranked using Bhattacharyya, entropy, minimum redundancy maximum relevance (mRMR), receiver-operating characteristics (ROC), Wilcoxon, t-test and reliefF methods. Ranked features are subjected to k-nearest neighbor (KNN) and decision tree (DT) classifiers for automated differentiation of CHF and normal ECG signals. We have achieved 99.86% accuracy, 99.78% sensitivity and 99.94% specificity in the identification of CHF affected ECG signals using 45 features. The proposed method is able to detect CHF patients accurately using only 2s of ECG signal length and hence providing sufficient time for the clinicians to further investigate on the severity of CHF and treatments. Copyright © 2017 Elsevier Ltd. All rights reserved.
Hartman, Nicholas D; Wheaton, Natasha B; Williamson, Kelly; Quattromani, Erin N; Branzetti, Jeremy B; Aldeen, Amer Z
2016-12-01
Reading emergent electrocardiograms (ECGs) is one of the emergency physician's most crucial tasks, yet no well-validated tool exists to measure resident competence in this skill. To assess validity of a novel tool measuring emergency medicine resident competency for interpreting, and responding to, critical ECGs. In addition, we aim to observe trends in this skill for resident physicians at different levels of training. This is a multi-center, prospective study of postgraduate year (PGY) 1-4 residents at five emergency medicine (EM) residency programs in the United States. An assessment tool was created that asks the physician to identify either the ECG diagnosis or the best immediate management. One hundred thirteen EM residents from five EM residency programs submitted completed assessment surveys, including 43 PGY-1s, 33 PGY-2s, and 37 PGY-3/4s. PGY-3/4s averaged 74.6% correct (95% confidence interval [CI] 70.9-78.4) and performed significantly better than PGY-1s, who averaged 63.2% correct (95% CI 58.0-68.3). PGY-2s averaged 69.0% (95% CI 62.2-73.7). Year-to-year differences were more pronounced in management than in diagnosis. Residency training in EM seems to be associated with improved ability to interpret "critical" ECGs as measured by our assessment tool. This lends validity evidence for the tool by correlating with a previously observed association between residency training and improved ECG interpretation. Resident skill in ECG interpretation remains less than ideal. Creation of this sort of tool may allow programs to assess resident performance as well as evaluate interventions designed to improve competency. Copyright © 2016 Elsevier Inc. All rights reserved.
Nallikuzhy, Jiss J; Dandapat, S
2017-06-01
In this work, a new patient-specific approach to enhance the spatial resolution of ECG is proposed and evaluated. The proposed model transforms a three-lead ECG into a standard twelve-lead ECG thereby enhancing its spatial resolution. The three leads used for prediction are obtained from the standard twelve-lead ECG. The proposed model takes advantage of the improved inter-lead correlation in wavelet domain. Since the model is patient-specific, it also selects the optimal predictor leads for a given patient using a lead selection algorithm. The lead selection algorithm is based on a new diagnostic similarity score which computes the diagnostic closeness between the original and the spatially enhanced leads. Standard closeness measures are used to assess the performance of the model. The similarity in diagnostic information between the original and the spatially enhanced leads are evaluated using various diagnostic measures. Repeatability and diagnosability are performed to quantify the applicability of the model. A comparison of the proposed model is performed with existing models that transform a subset of standard twelve-lead ECG into the standard twelve-lead ECG. From the analysis of the results, it is evident that the proposed model preserves diagnostic information better compared to other models. Copyright © 2017 Elsevier Ltd. All rights reserved.
Carel, R S
1982-04-01
The cost-effectiveness of a computerized ECG interpretation system in an ambulatory health care organization has been evaluated in comparison with a conventional (manual) system. The automated system was shown to be more cost-effective at a minimum load of 2,500 patients/month. At larger monthly loads an even greater cost-effectiveness was found, the average cost/ECG being about $2. In the manual system the cost/unit is practically independent of patient load. This is primarily due to the fact that 87% of the cost/ECG is attributable to wages and fees of highly trained personnel. In the automated system, on the other hand, the cost/ECG is heavily dependent on examinee load. This is due to the relatively large impact of equipment depreciation on fixed (and total) cost. Utilization of a computer-assisted system leads to marked reduction in cardiologists' interpretation time, substantially shorter turnaround time (of unconfirmed reports), and potential provision of simultaneous service at several remotely located "heart stations."
Pant, Jeevan K; Krishnan, Sridhar
2018-03-15
To present a new compressive sensing (CS)-based method for the acquisition of ECG signals and for robust estimation of heart-rate variability (HRV) parameters from compressively sensed measurements with high compression ratio. CS is used in the biosensor to compress the ECG signal. Estimation of the locations of QRS segments is carried out by applying two algorithms on the compressed measurements. The first algorithm reconstructs the ECG signal by enforcing a block-sparse structure on the first-order difference of the signal, so the transient QRS segments are significantly emphasized on the first-order difference of the signal. Multiple block-divisions of the signals are carried out with various block lengths, and multiple reconstructed signals are combined to enhance the robustness of the localization of the QRS segments. The second algorithm removes errors in the locations of QRS segments by applying low-pass filtering and morphological operations. The proposed CS-based method is found to be effective for the reconstruction of ECG signals by enforcing transient QRS structures on the first-order difference of the signal. It is demonstrated to be robust not only to high compression ratio but also to various artefacts present in ECG signals acquired by using on-body wireless sensors. HRV parameters computed by using the QRS locations estimated from the signals reconstructed with a compression ratio as high as 90% are comparable with that computed by using QRS locations estimated by using the Pan-Tompkins algorithm. The proposed method is useful for the realization of long-term HRV monitoring systems by using CS-based low-power wireless on-body biosensors.
Advanced computer techniques for inverse modeling of electric current in cardiac tissue
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hutchinson, S.A.; Romero, L.A.; Diegert, C.F.
1996-08-01
For many years, ECG`s and vector cardiograms have been the tools of choice for non-invasive diagnosis of cardiac conduction problems, such as found in reentrant tachycardia or Wolff-Parkinson-White (WPW) syndrome. Through skillful analysis of these skin-surface measurements of cardiac generated electric currents, a physician can deduce the general location of heart conduction irregularities. Using a combination of high-fidelity geometry modeling, advanced mathematical algorithms and massively parallel computing, Sandia`s approach would provide much more accurate information and thus allow the physician to pinpoint the source of an arrhythmia or abnormal conduction pathway.
PIC microcontroller-based RF wireless ECG monitoring system.
Oweis, R J; Barhoum, A
2007-01-01
This paper presents a radio-telemetry system that provides the possibility of ECG signal transmission from a patient detection circuit via an RF data link. A PC then receives the signal through the National Instrument data acquisition card (NIDAQ). The PC is equipped with software allowing the received ECG signals to be saved, analysed, and sent by email to another part of the world. The proposed telemetry system consists of a patient unit and a PC unit. The amplified and filtered ECG signal is sampled 360 times per second, and the A/D conversion is performed by a PIC16f877 microcontroller. The major contribution of the final proposed system is that it detects, processes and sends patients ECG data over a wireless RF link to a maximum distance of 200 m. Transmitted ECG data with different numbers of samples were received, decoded by means of another PIC microcontroller, and displayed using MATLAB program. The designed software is presented in a graphical user interface utility.
Park, Sung Min; Lee, Jin Hong; Choi, Seong Wook
2014-12-01
The ventricular electrocardiogram (v-ECG) was developed for long-term monitoring of heartbeats in patients with a left ventricular assist device (LVAD) and does not normally have the functionality necessary to detect additional heart irregularities that can progress to critical arrhythmias. Although the v-ECG has the benefits of physiological optimization and counterpulsation control, when abnormal heartbeats occur, the v-ECG does not show the distinct abnormal waveform that enables easy detection of an abnormal heartbeat among normal heartbeats on the conventional ECG. In this study, the v-ECGs of normal and abnormal heartbeats are compared with each other with respect to peak-to-peak voltage, area, and maximal slopes, and a new method to detect abnormal heartbeats is suggested. In a series of animal experiments with three porcine models (Yorkshire pigs weighing 30-40 kg), a v-ECG and conventional ECG were taken simultaneously during LVAD perfusion. Clinical experts found 104 abnormal heartbeats from the saved conventional ECG data and confirmed that the other 3159 heartbeats were normal. Almost all of the abnormal heartbeats were premature ventricular contractions (PVCs), and there was short-term tachycardia for 3 s. A personal computer was used to automatically detect abnormal heartbeats with the v-ECG according to the new method, and its results were compared with the clinicians' results. The new method found abnormal heartbeats with 90% accuracy, and less than 15% of the total PVCs were missed. Copyright © 2014 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.
Design intelligent wheelchair with ECG measurement and wireless transmission function.
Chou, Hsi-Chiang; Wang, Yi-Ming; Chang, Huai-Yuan
2015-01-01
The phenomenon of aging populations has produced widespread health awareness and magnified the need for improved medical quality and technologies. Statistics show that ischemic heart disease is the leading cause of death for older people and people with reduced mobility; therefore, wheelchairs have become their primary means of transport. Hence, an arrhythmia-detecting smart wheelchair was proposed in this study to provide real-time electrocardiography (ECG)-monitoring to patients with heart disease and reduced mobility. A self-developed, handheld ECG-sensing instrument was integrated with a wheelchair and a lab-written, arrhythmia-detecting program. The measured ECG data were transmitted through a Wi-Fi module and analyzed and diagnosed using the human-machine interface.
Pizzuti, A; Baralis, G; Bassignana, A; Antonielli, E; Di Leo, M
1997-01-01
The MS200 Cardioscope, from MRT Micro as., Norway, is a 12 channel ECG card to be directly inserted into a standard personal computer (PC). The standard ISA Bus compatible half length card comes with a set of 10 cables with electrodes and the software for recording, displaying and saving ECG signals. The system is supplied with DOS or Windows software. The goal of the present work was to evaluate the affordability and usability of the MS200 in a clinical setting. We tested the 1.5 DOS version of the software. In 30 patients with various cardiac diseases the ECG signal has been recorded with MS200 and with standard Hellige CardioSmart equipment. The saved ECGs were recalled and printed using an Epson Stylus 800 ink-jet printer. Two cardiologists reviewed the recordings for a looking at output quality, amplitude and speed precision, artifacts, etc. 1) Installation: the card has proven to be totally compatible with the hardware; no changes in default settings had to be made. 2) Usage: the screens are clear; the commands and menus are intuitive and easy to use. Due to the boot-strap and software loading procedures and, most important, off-line printing, the time needed to obtain a complete ECG printout has been longer than that of the reference machine. 3) Archiving and retrieval of ECG: the ECG curves can be saved in original or compressed form: selecting the latter, the noise and non-ECG information is filtered away and the space consumption on disk is reduced: on average, 20 Kb are needed for 10 seconds of signal. The MS200 can be run on a Local Area Network and is prepared for integrating with an existing informative system: we are currently testing the system in this scenery. 4) MS200 includes options for on-line diagnosis, a technology we have not tested in the present work. 5) The only setting allowed for printing full pages is letter size (A4): the quality of printouts is good, with a resolution of 180 DPI. In conclusion, the MS200 system seems reliable and safe. In the configuration we tested, it cannot substitute a dedicated ECG equipment: from this point of view, a smaller PCMCIA-type card with a battery-operated notebook PC will be more suitable for clinical uses. Nevertheless, the possibility to log and track ECG records, integrated into the department informative system, may provide a valuable tool for improving access to medical information.
Yao, Jingting; Tridandapani, Srini; Wick, Carson A; Bhatti, Pamela T
2017-01-01
To more accurately trigger cardiac computed tomography angiography (CTA) than electrocardiography (ECG) alone, a sub-system is proposed as an intermediate step toward fusing ECG with seismocardiography (SCG). Accurate prediction of quiescent phases is crucial to prospectively gating CTA, which is susceptible to cardiac motion and, thus, can affect the diagnostic quality of images. The key innovation of this sub-system is that it identifies the SCG waveform corresponding to heart sounds and determines their phases within the cardiac cycles. Furthermore, this relationship is modeled as a linear function with respect to heart rate. For this paper, B-mode echocardiography is used as the gold standard for identifying the quiescent phases. We analyzed synchronous ECG, SCG, and echocardiography data acquired from seven healthy subjects (mean age: 31; age range: 22-48; males: 4) and 11 cardiac patients (mean age: 56; age range: 31-78; males: 6). On average, the proposed algorithm was able to successfully identify 79% of the SCG waveforms in systole and 68% in diastole. The simulated results show that SCG-based prediction produced less average phase error than that of ECG. It was found that the accuracy of ECG-based gating is more susceptible to increases in heart rate variability, while SCG-based gating is susceptible to high cycle to cycle variability in morphology. This pilot work of prediction using SCG waveforms enriches the framework of a comprehensive system with multiple modalities that could potentially, in real time, improve the image quality of CTA.
Matsui, Takemi; Shinba, Toshikazu; Sun, Guanghao
2018-02-01
12.6% of major depressive disorder (MDD) patients have suicide intent, while it has been reported that 43% of patients did not consult their doctors for MDD, automated MDD screening is eagerly anticipated. Recently, in order to achieve automated screening of MDD, biomarkers such as multiplex DNA methylation profiles or physiological method using near infra-red spectroscopy (NIRS) have been studied, however, they require inspection using 96-well DNA ELIZA kit after blood sampling or significant cost. Using a single-lead electrocardiography (ECG), we developed a high-precision MDD screening system using transient autonomic responses induced by dual mental tasks. We developed a novel high precision MDD screening system which is composed of a single-lead ECG monitor, analogue to digital (AD) converter and a personal computer with measurement and analysis program written by LabView programming language. The system discriminates MDD patients from normal subjects using heat rate variability (HRV)-derived transient autonomic responses induced by dual mental tasks, i.e. verbal fluency task and random number generation task, via linear discriminant analysis (LDA) adopting HRV-related predictor variables (hear rate (HR), high frequency (HF), low frequency (LF)/HF). The proposed system was tested for 12 MDD patients (32 ± 15 years) under antidepressant treatment from Shizuoka Saiseikai General Hospital outpatient unit and 30 normal volunteers (37 ± 17 years) from Tokyo Metropolitan University. The proposed system achieved 100% sensitivity and 100% specificity in classifying 42 examinees into 12 MDD patients and 30 normal subjects. The proposed system appears promising for future HRV-based high-precision and low-cost screening of MDDs using only single-lead ECG.
Advanced Electrocardiography Can Identify Occult Cardiomyopathy in Doberman Pinschers
NASA Technical Reports Server (NTRS)
Spiljak, M.; Petric, A. Domanjko; Wilberg, M.; Olsen, L. H.; Stepancic, A.; Schlegel, T. T.; Starc, V.
2011-01-01
Recently, multiple advanced resting electrocardiographic (A-ECG) techniques have improved the diagnostic value of short-duration ECG in detection of dilated cardiomyopathy (DCM) in humans. This study investigated whether 12-lead A-ECG recordings could accurately identify the occult phase of DCM in dogs. Short-duration (3-5 min) high-fidelity 12-lead ECG recordings were obtained from 31 privately-owned, clinically healthy Doberman Pinschers (5.4 +/- 1.7 years, 11/20 males/females). Dogs were divided into 2 groups: 1) 19 healthy dogs with normal echocardiographic M-mode measurements: left ventricular internal diameter in diastole (LVIDd . 47mm) and in systole (LVIDs . 38mm) and normal 24-hour ECG recordings (<50 ventricular premature complexes, VPCs); and 2) 12 dogs with occult DCM: 11/12 dogs had increased M-mode measurements (LVIDd . 49mm and/or LVIDs . 40mm) and 5/11 dogs had also >100 VPCs/24h; 1/12 dogs had only abnormal 24-hour ECG recordings (>100 VPCs/24h). ECG recordings were evaluated via custom software programs to calculate multiple parameters of high-frequency (HF) QRS ECG, heart rate variability, QT variability, waveform complexity and 3-D ECG. Student's t-tests determined 19 ECG parameters that were significantly different (P < 0.05) between groups. Principal component factor analysis identified a 5-factor model with 81.4% explained variance. QRS dipolar and non-dipolar voltages, Cornell voltage criteria and QRS waveform residuum were increased significantly (P < 0.05), whereas mean HF QRS amplitude was decreased significantly (P < 0.05) in dogs with occult DCM. For the 5 selected parameters the prediction of occult DCM was performed using a binary logistic regression model with Chi-square tested significance (P < 0.01). ROC analyses showed that the five selected ECG parameters could identify occult ECG with sensitivity 89% and specificity 83%. Results suggest that 12-lead A-ECG might improve diagnostic value of short-duration ECG in earlier detection of canine DCM as five selected ECG parameters can with reasonable accuracy identify occult DCM in Doberman Pinschers. Future extensive clinical studies need to clarify if 12-lead A-ECG could be useful as an additional screening test for canine DCM.
Computer-based rhythm diagnosis and its possible influence on nonexpert electrocardiogram readers.
Hakacova, Nina; Trägårdh-Johansson, Elin; Wagner, Galen S; Maynard, Charles; Pahlm, Olle
2012-01-01
Systems providing computer-based analysis of the resting electrocardiogram (ECG) seek to improve the quality of health care by providing accurate and timely automatic diagnosis of, for example, cardiac rhythm to clinicians. The accuracy of these diagnoses, however, remains questionable. We tested the hypothesis that (a) 2 independent automated ECG systems have better accuracy in rhythm diagnosis than nonexpert clinicians and (b) both systems provide correct diagnostic suggestions in a large percentage of cases where the diagnosis of nonexpert clinicians is incorrect. Five hundred ECGs were manually analyzed by 2 senior experts, 3 nonexpert clinicians, and automatically by 2 automated systems. The accuracy of the nonexpert rhythm statements was compared with the accuracy of each system statement. The proportion of rhythm statements when the clinician's diagnoses were incorrect and the systems instead provided correct diagnosis was assessed. A total of 420 sinus rhythms and 156 rhythm disturbances were recognized by expert reading. Significance of the difference in accuracy between nonexperts and systems was P = .45 for system A and P = .11 for system B. The percentage of correct automated diagnoses in cases when the clinician was incorrect was 28% ± 10% for system A and 25% ± 11% for system B (P = .09). The rhythm diagnoses of automated systems did not reach better average accuracy than those of nonexpert readings. The computer diagnosis of rhythm can be incorrect in cases where the clinicians fail in reaching the correct ECG diagnosis. Copyright © 2012. Published by Elsevier Inc.
Decomposition of ECG by linear filtering.
Murthy, I S; Niranjan, U C
1992-01-01
A simple method is developed for the delineation of a given electrocardiogram (ECG) signal into its component waves. The properties of discrete cosine transform (DCT) are exploited for the purpose. The transformed signal is convolved with appropriate filters and the component waves are obtained by computing the inverse transform (IDCT) of the filtered signals. The filters are derived from the time signal itself. Analysis of continuous strips of ECG signals with various arrhythmias showed that the performance of the method is satisfactory both qualitatively and quantitatively. The small amplitude P wave usually had a high percentage rms difference (PRD) compared to the other large component waves.
Lucani, Daniel; Cataldo, Giancarlos; Cruz, Julio; Villegas, Guillermo; Wong, Sara
2006-01-01
A prototype of a portable ECG-monitoring device has been developed for clinical and non-clinical environments as part of a telemedicine system to provide remote and continuous surveillance of patients. The device can acquire, store and/or transmit ECG signals to computer-based platforms or specially configured access points (AP) with Intranet/Internet capabilities in order to reach remote monitoring stations. Acquired data can be stored in a flash memory card in FAT16 format for later recovery, or transmitted via Bluetooth or USB to a local station or AP. This data acquisition module (DAM) operates in two modes: Holter and on-line transmission.
ECG Monitoring in Cardiac Rehabilitation: Is It Needed?
ERIC Educational Resources Information Center
Greenland, Philip; Pomilla, Paul V.
1989-01-01
Discusses the controversial use of continuous electrocardiogram (ECG) monitoring as a safety measure in cardiac rehabilitation exercise programs. Little evidence substantiates its value for all patients during exercise. In the absence of empirical evidence documenting the worth of this expensive procedure, it is recommended for use with high-risk…
2013-01-01
Background Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) signals, being an activity of the autonomous nervous system (ANS), reflect the underlying true emotional state of a person. However, the performance of various methods developed so far lacks accuracy, and more robust methods need to be developed to identify the emotional pattern associated with ECG signals. Methods Emotional ECG data was obtained from sixty participants by inducing the six basic emotional states (happiness, sadness, fear, disgust, surprise and neutral) using audio-visual stimuli. The non-linear feature ‘Hurst’ was computed using Rescaled Range Statistics (RRS) and Finite Variance Scaling (FVS) methods. New Hurst features were proposed by combining the existing RRS and FVS methods with Higher Order Statistics (HOS). The features were then classified using four classifiers – Bayesian Classifier, Regression Tree, K- nearest neighbor and Fuzzy K-nearest neighbor. Seventy percent of the features were used for training and thirty percent for testing the algorithm. Results Analysis of Variance (ANOVA) conveyed that Hurst and the proposed features were statistically significant (p < 0.001). Hurst computed using RRS and FVS methods showed similar classification accuracy. The features obtained by combining FVS and HOS performed better with a maximum accuracy of 92.87% and 76.45% for classifying the six emotional states using random and subject independent validation respectively. Conclusions The results indicate that the combination of non-linear analysis and HOS tend to capture the finer emotional changes that can be seen in healthy ECG data. This work can be further fine tuned to develop a real time system. PMID:23680041
Paiva, Joana S.; Dias, Duarte
2017-01-01
In recent years, safer and more reliable biometric methods have been developed. Apart from the need for enhanced security, the media and entertainment sectors have also been applying biometrics in the emerging market of user-adaptable objects/systems to make these systems more user-friendly. However, the complexity of some state-of-the-art biometric systems (e.g., iris recognition) or their high false rejection rate (e.g., fingerprint recognition) is neither compatible with the simple hardware architecture required by reduced-size devices nor the new trend of implementing smart objects within the dynamic market of the Internet of Things (IoT). It was recently shown that an individual can be recognized by extracting features from their electrocardiogram (ECG). However, most current ECG-based biometric algorithms are computationally demanding and/or rely on relatively large (several seconds) ECG samples, which are incompatible with the aforementioned application fields. Here, we present a computationally low-cost method (patent pending), including simple mathematical operations, for identifying a person using only three ECG morphology-based characteristics from a single heartbeat. The algorithm was trained/tested using ECG signals of different duration from the Physionet database on more than 60 different training/test datasets. The proposed method achieved maximal averaged accuracy of 97.450% in distinguishing each subject from a ten-subject set and false acceptance and rejection rates (FAR and FRR) of 5.710±1.900% and 3.440±1.980%, respectively, placing Beat-ID in a very competitive position in terms of the FRR/FAR among state-of-the-art methods. Furthermore, the proposed method can identify a person using an average of 1.020 heartbeats. It therefore has FRR/FAR behavior similar to obtaining a fingerprint, yet it is simpler and requires less expensive hardware. This method targets low-computational/energy-cost scenarios, such as tiny wearable devices (e.g., a smart object that automatically adapts its configuration to the user). A hardware proof-of-concept implementation is presented as an annex to this paper. PMID:28719614
Paiva, Joana S; Dias, Duarte; Cunha, João P S
2017-01-01
In recent years, safer and more reliable biometric methods have been developed. Apart from the need for enhanced security, the media and entertainment sectors have also been applying biometrics in the emerging market of user-adaptable objects/systems to make these systems more user-friendly. However, the complexity of some state-of-the-art biometric systems (e.g., iris recognition) or their high false rejection rate (e.g., fingerprint recognition) is neither compatible with the simple hardware architecture required by reduced-size devices nor the new trend of implementing smart objects within the dynamic market of the Internet of Things (IoT). It was recently shown that an individual can be recognized by extracting features from their electrocardiogram (ECG). However, most current ECG-based biometric algorithms are computationally demanding and/or rely on relatively large (several seconds) ECG samples, which are incompatible with the aforementioned application fields. Here, we present a computationally low-cost method (patent pending), including simple mathematical operations, for identifying a person using only three ECG morphology-based characteristics from a single heartbeat. The algorithm was trained/tested using ECG signals of different duration from the Physionet database on more than 60 different training/test datasets. The proposed method achieved maximal averaged accuracy of 97.450% in distinguishing each subject from a ten-subject set and false acceptance and rejection rates (FAR and FRR) of 5.710±1.900% and 3.440±1.980%, respectively, placing Beat-ID in a very competitive position in terms of the FRR/FAR among state-of-the-art methods. Furthermore, the proposed method can identify a person using an average of 1.020 heartbeats. It therefore has FRR/FAR behavior similar to obtaining a fingerprint, yet it is simpler and requires less expensive hardware. This method targets low-computational/energy-cost scenarios, such as tiny wearable devices (e.g., a smart object that automatically adapts its configuration to the user). A hardware proof-of-concept implementation is presented as an annex to this paper.
Threshold-based system for noise detection in multilead ECG recordings.
Jekova, Irena; Krasteva, Vessela; Christov, Ivaylo; Abächerli, Roger
2012-09-01
This paper presents a system for detection of the most common noise types seen on the electrocardiogram (ECG) in order to evaluate whether an episode from 12-lead ECG is reliable for diagnosis. It implements criteria for estimation of the noise corruption level in specific frequency bands, aiming to identify the main sources of ECG quality disruption, such as missing signal or limited dynamics of the QRS components above 4 Hz; presence of high amplitude and steep artifacts seen above 1 Hz; baseline drift estimated at frequencies below 1 Hz; power-line interference in a band ±2 Hz around its central frequency; high-frequency and electromyographic noises above 20 Hz. All noise tests are designed to process the ECG series in the time domain, including 13 adjustable thresholds for amplitude and slope criteria which are evaluated in adjustable time intervals, as well as number of leads. The system allows flexible extension toward application-specific requirements for the noise levels in acceptable quality ECGs. Training of different thresholds' settings to determine different positive noise detection rates is performed with the annotated set of 1000 ECGs from the PhysioNet database created for the Computing in Cardiology Challenge 2011. Two implementations are highlighted on the receiver operating characteristic (area 0.968) to fit to different applications. The implementation with high sensitivity (Se = 98.7%, Sp = 80.9%) appears as a reliable alarm when there are any incidental problems with the ECG acquisition, while the implementation with high specificity (Sp = 97.8%, Se = 81.8%) is less susceptible to transient problems but rather validates noisy ECGs with acceptable quality during a small portion of the recording.
A QRS Detection and R Point Recognition Method for Wearable Single-Lead ECG Devices.
Chen, Chieh-Li; Chuang, Chun-Te
2017-08-26
In the new-generation wearable Electrocardiogram (ECG) system, signal processing with low power consumption is required to transmit data when detecting dangerous rhythms and to record signals when detecting abnormal rhythms. The QRS complex is a combination of three of the graphic deflection seen on a typical ECG. This study proposes a real-time QRS detection and R point recognition method with low computational complexity while maintaining a high accuracy. The enhancement of QRS segments and restraining of P and T waves are carried out by the proposed ECG signal transformation, which also leads to the elimination of baseline wandering. In this study, the QRS fiducial point is determined based on the detected crests and troughs of the transformed signal. Subsequently, the R point can be recognized based on four QRS waveform templates and preliminary heart rhythm classification can be also achieved at the same time. The performance of the proposed approach is demonstrated using the benchmark of the MIT-BIH Arrhythmia Database, where the QRS detected sensitivity (Se) and positive prediction (+P) are 99.82% and 99.81%, respectively. The result reveals the approach's advantage of low computational complexity, as well as the feasibility of the real-time application on a mobile phone and an embedded system.
A computer-aided ECG diagnostic tool.
Oweis, Rami; Hijazi, Lily
2006-03-01
Jordan lacks companies that provide local medical facilities with products that are of help in daily performed medical procedures. Because of this, the country imports most of these expensive products. Consequently, a local interest in producing such products has emerged and resulted in serious research efforts in this area. The main goal of this paper is to provide local (the north of Jordan) clinics with a computer-aided electrocardiogram (ECG) diagnostic tool in an attempt to reduce time and work demands for busy physicians especially in areas where only one general medicine doctor is employed and a bulk of cases are to be diagnosed. The tool was designed to help in detecting heart defects such as arrhythmias and heart blocks using ECG signal analysis depending on the time-domain representation, the frequency-domain spectrum, and the relationship between them. The application studied here represents a state of the art ECG diagnostic tool that was designed, implemented, and tested in Jordan to serve wide spectrum of population who are from poor families. The results of applying the tool on randomly selected representative sample showed about 99% matching with those results obtained at specialized medical facilities. Costs, ease of interface, and accuracy indicated the usefulness of the tool and its use as an assisting diagnostic tool.
Sharifahmadian, Ershad
2006-01-01
The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.
Signal processing using sparse derivatives with applications to chromatograms and ECG
NASA Astrophysics Data System (ADS)
Ning, Xiaoran
In this thesis, we investigate the sparsity exist in the derivative domain. Particularly, we focus on the type of signals which posses up to Mth (M > 0) order sparse derivatives. Efforts are put on formulating proper penalty functions and optimization problems to capture properties related to sparse derivatives, searching for fast, computationally efficient solvers. Also the effectiveness of these algorithms are applied to two real world applications. In the first application, we provide an algorithm which jointly addresses the problems of chromatogram baseline correction and noise reduction. The series of chromatogram peaks are modeled as sparse with sparse derivatives, and the baseline is modeled as a low-pass signal. A convex optimization problem is formulated so as to encapsulate these non-parametric models. To account for the positivity of chromatogram peaks, an asymmetric penalty function is also utilized with symmetric penalty functions. A robust, computationally efficient, iterative algorithm is developed that is guaranteed to converge to the unique optimal solution. The approach, termed Baseline Estimation And Denoising with Sparsity (BEADS), is evaluated and compared with two state-of-the-art methods using both simulated and real chromatogram data. Promising result is obtained. In the second application, a novel Electrocardiography (ECG) enhancement algorithm is designed also based on sparse derivatives. In the real medical environment, ECG signals are often contaminated by various kinds of noise or artifacts, for example, morphological changes due to motion artifact, non-stationary noise due to muscular contraction (EMG), etc. Some of these contaminations severely affect the usefulness of ECG signals, especially when computer aided algorithms are utilized. By solving the proposed convex l1 optimization problem, artifacts are reduced by modeling the clean ECG signal as a sum of two signals whose second and third-order derivatives (differences) are sparse respectively. At the end, the algorithm is applied to a QRS detection system and validated using the MIT-BIH Arrhythmia database (109452 anotations), resulting a sensitivity of Se = 99.87%$ and a positive prediction of +P = 99.88%.
Issues in implementing a knowledge-based ECG analyzer for personal mobile health monitoring.
Goh, K W; Kim, E; Lavanya, J; Kim, Y; Soh, C B
2006-01-01
Advances in sensor technology, personal mobile devices, and wireless broadband communications are enabling the development of an integrated personal mobile health monitoring system that can provide patients with a useful tool to assess their own health and manage their personal health information anytime and anywhere. Personal mobile devices, such as PDAs and mobile phones, are becoming more powerful integrated information management tools and play a major role in many people's lives. We focus on designing a health-monitoring system for people who suffer from cardiac arrhythmias. We have developed computer simulation models to evaluate the performance of appropriate electrocardiogram (ECG) analysis techniques that can be implemented on personal mobile devices. This paper describes an ECG analyzer to perform ECG beat and episode detection and classification. We have obtained promising preliminary results from our study. Also, we discuss several key considerations when implementing a mobile health monitoring solution. The mobile ECG analyzer would become a front-end patient health data acquisition module, which is connected to the Personal Health Information Management System (PHIMS) for data repository.
Yao, Jingting; Tridandapani, Srini; Wick, Carson A.
2017-01-01
To more accurately trigger cardiac computed tomography angiography (CTA) than electrocardiography (ECG) alone, a sub-system is proposed as an intermediate step toward fusing ECG with seismocardiography (SCG). Accurate prediction of quiescent phases is crucial to prospectively gating CTA, which is susceptible to cardiac motion and, thus, can affect the diagnostic quality of images. The key innovation of this sub-system is that it identifies the SCG waveform corresponding to heart sounds and determines their phases within the cardiac cycles. Furthermore, this relationship is modeled as a linear function with respect to heart rate. For this paper, B-mode echocardiography is used as the gold standard for identifying the quiescent phases. We analyzed synchronous ECG, SCG, and echocardiography data acquired from seven healthy subjects (mean age: 31; age range: 22–48; males: 4) and 11 cardiac patients (mean age: 56; age range: 31–78; males: 6). On average, the proposed algorithm was able to successfully identify 79% of the SCG waveforms in systole and 68% in diastole. The simulated results show that SCG-based prediction produced less average phase error than that of ECG. It was found that the accuracy of ECG-based gating is more susceptible to increases in heart rate variability, while SCG-based gating is susceptible to high cycle to cycle variability in morphology. This pilot work of prediction using SCG waveforms enriches the framework of a comprehensive system with multiple modalities that could potentially, in real time, improve the image quality of CTA. PMID:28845370
Krstacic, Goran; Krstacic, Antonija; Smalcelj, Anton; Milicic, Davor; Jembrek-Gostovic, Mirjana
2007-04-01
Dynamic analysis techniques may quantify abnormalities in heart rate variability (HRV) based on nonlinear and fractal analysis (chaos theory). The article emphasizes clinical and prognostic significance of dynamic changes in short-time series applied on patients with coronary heart disease (CHD) during the exercise electrocardiograph (ECG) test. The subjects were included in the series after complete cardiovascular diagnostic data. Series of R-R and ST-T intervals were obtained from exercise ECG data after sampling digitally. The range rescaled analysis method determined the fractal dimension of the intervals. To quantify fractal long-range correlation's properties of heart rate variability, the detrended fluctuation analysis technique was used. Approximate entropy (ApEn) was applied to quantify the regularity and complexity of time series, as well as unpredictability of fluctuations in time series. It was found that the short-term fractal scaling exponent (alpha(1)) is significantly lower in patients with CHD (0.93 +/- 0.07 vs 1.09 +/- 0.04; P < 0.001). The patients with CHD had higher fractal dimension in each exercise test program separately, as well as in exercise program at all. ApEn was significant lower in CHD group in both RR and ST-T ECG intervals (P < 0.001). The nonlinear dynamic methods could have clinical and prognostic applicability also in short-time ECG series. Dynamic analysis based on chaos theory during the exercise ECG test point out the multifractal time series in CHD patients who loss normal fractal characteristics and regularity in HRV. Nonlinear analysis technique may complement traditional ECG analysis.
Automated J wave detection from digital 12-lead electrocardiogram.
Wang, Yi Grace; Wu, Hau-Tieng; Daubechies, Ingrid; Li, Yabing; Estes, E Harvey; Soliman, Elsayed Z
2015-01-01
In this report we provide a method for automated detection of J wave, defined as a notch or slur in the descending slope of the terminal positive wave of the QRS complex, using signal processing and functional data analysis techniques. Two different sets of ECG tracings were selected from the EPICARE ECG core laboratory, Wake Forest School of Medicine, Winston Salem, NC. The first set was a training set comprised of 100 ECGs of which 50 ECGs had J-wave and the other 50 did not. The second set was a test set (n=116 ECGs) in which the J-wave status (present/absent) was only known by the ECG Center staff. All ECGs were recorded using GE MAC 1200 (GE Marquette, Milwaukee, Wisconsin) at 10mm/mV calibration, speed of 25mm/s and 500HZ sampling rate. All ECGs were initially inspected visually for technical errors and inadequate quality, and then automatically processed with the GE Marquette 12-SL program 2001 version (GE Marquette, Milwaukee, WI). We excluded ECG tracings with major abnormalities or rhythm disorder. Confirmation of the presence or absence of a J wave was done visually by the ECG Center staff and verified once again by three of the coauthors. There was no disagreement in the identification of the J wave state. The signal processing and functional data analysis techniques applied to the ECGs were conducted at Duke University and the University of Toronto. In the training set, the automated detection had sensitivity of 100% and specificity of 94%. For the test set, sensitivity was 89% and specificity was 86%. In conclusion, test results of the automated method we developed show a good J wave detection accuracy, suggesting possible utility of this approach for defining and detection of other complex ECG waveforms. Copyright © 2015 Elsevier Inc. All rights reserved.
Alday, Erick A. Perez; Colman, Michael A.; Langley, Philip; Butters, Timothy D.; Higham, Jonathan; Workman, Antony J.; Hancox, Jules C.; Zhang, Henggui
2015-01-01
Rapid atrial arrhythmias such as atrial fibrillation (AF) predispose to ventricular arrhythmias, sudden cardiac death and stroke. Identifying the origin of atrial ectopic activity from the electrocardiogram (ECG) can help to diagnose the early onset of AF in a cost-effective manner. The complex and rapid atrial electrical activity during AF makes it difficult to obtain detailed information on atrial activation using the standard 12-lead ECG alone. Compared to conventional 12-lead ECG, more detailed ECG lead configurations may provide further information about spatio-temporal dynamics of the body surface potential (BSP) during atrial excitation. We apply a recently developed 3D human atrial model to simulate electrical activity during normal sinus rhythm and ectopic pacing. The atrial model is placed into a newly developed torso model which considers the presence of the lungs, liver and spinal cord. A boundary element method is used to compute the BSP resulting from atrial excitation. Elements of the torso mesh corresponding to the locations of the placement of the electrodes in the standard 12-lead and a more detailed 64-lead ECG configuration were selected. The ectopic focal activity was simulated at various origins across all the different regions of the atria. Simulated BSP maps during normal atrial excitation (i.e. sinoatrial node excitation) were compared to those observed experimentally (obtained from the 64-lead ECG system), showing a strong agreement between the evolution in time of the simulated and experimental data in the P-wave morphology of the ECG and dipole evolution. An algorithm to obtain the location of the stimulus from a 64-lead ECG system was developed. The algorithm presented had a success rate of 93%, meaning that it correctly identified the origin of atrial focus in 75/80 simulations, and involved a general approach relevant to any multi-lead ECG system. This represents a significant improvement over previously developed algorithms. PMID:25611350
Sahoo, Satya S; Jayapandian, Catherine; Garg, Gaurav; Kaffashi, Farhad; Chung, Stephanie; Bozorgi, Alireza; Chen, Chien-Hun; Loparo, Kenneth; Lhatoo, Samden D; Zhang, Guo-Qiang
2014-01-01
Objective The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorithms and informatics approaches using new cloud computing technologies as well as ontologies for collaborative multicenter studies. Materials and methods We present the Cloudwave platform, which (a) defines parallelized algorithms for computing cardiac measures using the MapReduce parallel programming framework, (b) supports real-time interaction with large volumes of electrophysiological signals, and (c) features signal visualization and querying functionalities using an ontology-driven web-based interface. Cloudwave is currently used in the multicenter National Institute of Neurological Diseases and Stroke (NINDS)-funded Prevention and Risk Identification of SUDEP (sudden unexplained death in epilepsy) Mortality (PRISM) project to identify risk factors for sudden death in epilepsy. Results Comparative evaluations of Cloudwave with traditional desktop approaches to compute cardiac measures (eg, QRS complexes, RR intervals, and instantaneous heart rate) on epilepsy patient data show one order of magnitude improvement for single-channel ECG data and 20 times improvement for four-channel ECG data. This enables Cloudwave to support real-time user interaction with signal data, which is semantically annotated with a novel epilepsy and seizure ontology. Discussion Data privacy is a critical issue in using cloud infrastructure, and cloud platforms, such as Amazon Web Services, offer features to support Health Insurance Portability and Accountability Act standards. Conclusion The Cloudwave platform is a new approach to leverage of large-scale electrophysiological data for advancing multicenter clinical research. PMID:24326538
Sahoo, Satya S; Jayapandian, Catherine; Garg, Gaurav; Kaffashi, Farhad; Chung, Stephanie; Bozorgi, Alireza; Chen, Chien-Hun; Loparo, Kenneth; Lhatoo, Samden D; Zhang, Guo-Qiang
2014-01-01
The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorithms and informatics approaches using new cloud computing technologies as well as ontologies for collaborative multicenter studies. We present the Cloudwave platform, which (a) defines parallelized algorithms for computing cardiac measures using the MapReduce parallel programming framework, (b) supports real-time interaction with large volumes of electrophysiological signals, and (c) features signal visualization and querying functionalities using an ontology-driven web-based interface. Cloudwave is currently used in the multicenter National Institute of Neurological Diseases and Stroke (NINDS)-funded Prevention and Risk Identification of SUDEP (sudden unexplained death in epilepsy) Mortality (PRISM) project to identify risk factors for sudden death in epilepsy. Comparative evaluations of Cloudwave with traditional desktop approaches to compute cardiac measures (eg, QRS complexes, RR intervals, and instantaneous heart rate) on epilepsy patient data show one order of magnitude improvement for single-channel ECG data and 20 times improvement for four-channel ECG data. This enables Cloudwave to support real-time user interaction with signal data, which is semantically annotated with a novel epilepsy and seizure ontology. Data privacy is a critical issue in using cloud infrastructure, and cloud platforms, such as Amazon Web Services, offer features to support Health Insurance Portability and Accountability Act standards. The Cloudwave platform is a new approach to leverage of large-scale electrophysiological data for advancing multicenter clinical research.
Gimeno-Blanes, Francisco J.; Blanco-Velasco, Manuel; Barquero-Pérez, Óscar; García-Alberola, Arcadi; Rojo-Álvarez, José L.
2016-01-01
Great effort has been devoted in recent years to the development of sudden cardiac risk predictors as a function of electric cardiac signals, mainly obtained from the electrocardiogram (ECG) analysis. But these prediction techniques are still seldom used in clinical practice, partly due to its limited diagnostic accuracy and to the lack of consensus about the appropriate computational signal processing implementation. This paper addresses a three-fold approach, based on ECG indices, to structure this review on sudden cardiac risk stratification. First, throughout the computational techniques that had been widely proposed for obtaining these indices in technical literature. Second, over the scientific evidence, that although is supported by observational clinical studies, they are not always representative enough. And third, via the limited technology transfer of academy-accepted algorithms, requiring further meditation for future systems. We focus on three families of ECG derived indices which are tackled from the aforementioned viewpoints, namely, heart rate turbulence (HRT), heart rate variability (HRV), and T-wave alternans. In terms of computational algorithms, we still need clearer scientific evidence, standardizing, and benchmarking, siting on advanced algorithms applied over large and representative datasets. New scenarios like electronic health recordings, big data, long-term monitoring, and cloud databases, will eventually open new frameworks to foresee suitable new paradigms in the near future. PMID:27014083
Near Field Communication-based telemonitoring with integrated ECG recordings.
Morak, J; Kumpusch, H; Hayn, D; Leitner, M; Scherr, D; Fruhwald, F M; Schreier, G
2011-01-01
Telemonitoring of vital signs is an established option in treatment of patients with chronic heart failure (CHF). In order to allow for early detection of atrial fibrillation (AF) which is highly prevalent in the CHF population telemonitoring programs should include electrocardiogram (ECG) signals. It was therefore the aim to extend our current home monitoring system based on mobile phones and Near Field Communication technology (NFC) to enable patients acquiring their ECG signals autonomously in an easy-to-use way. We prototypically developed a sensing device for the concurrent acquisition of blood pressure and ECG signals. The design of the device equipped with NFC technology and Bluetooth allowed for intuitive interaction with a mobile phone based patient terminal. This ECG monitoring system was evaluated in the course of a clinical pilot trial to assess the system's technical feasibility, usability and patient's adherence to twice daily usage. 21 patients (4f, 54 ± 14 years) suffering from CHF were included in the study and were asked to transmit two ECG recordings per day via the telemonitoring system autonomously over a monitoring period of seven days. One patient dropped out from the study. 211 data sets were transmitted over a cumulative monitoring period of 140 days (overall adherence rate 82.2%). 55% and 8% of the transmitted ECG signals were sufficient for ventricular and atrial rhythm assessment, respectively. Although ECG signal quality has to be improved for better AF detection the developed communication design of joining Bluetooth and NFC technology in our telemonitoring system allows for ambulatory ECG acquisition with high adherence rates and system usability in heart failure patients.
Palhares, Daniel M F; Marcolino, Milena S; Santos, Thales M M; da Silva, José L P; Gomes, Paulo R; Ribeiro, Leonardo B; Macfarlane, Peter W; Ribeiro, Antonio L P
2017-06-13
Knowledge of the normal limits of the electrocardiogram (ECG) is mandatory for establishing which patients have abnormal ECGs. No studies have assessed the reference standards for a Latin American population. Our aim was to establish the normal ranges of the ECG for pediatric and adult Brazilian primary care patients. This retrospective observational study assessed all the consecutive 12-lead digital electrocardiograms of primary care patients at least 1 year old in Minas Gerais state, Brazil, recorded between 2010 and 2015. ECGs were excluded if there were technical problems, selected abnormalities were present or patients with selected self-declared comorbidities or on drug therapy. Only the first ECG from patients with multiple ECGs was accepted. The University of Glasgow ECG analysis program was used to automatically interpret the ECGs. For each variable, the 1st, 2nd, 50th, 98th and 99th percentiles were determined and results were compared to selected studies. A total of 1,493,905 ECGs were recorded. 1,007,891 were excluded and 486.014 were analyzed. This large study provided normal values for heart rate, P, QRS and T frontal axis, P and QRS overall duration, PR and QT overall intervals and QTc corrected by Hodges, Bazett, Fridericia and Framingham formulae. Overall, the results were similar to those from other studies performed in different populations but there were differences in extreme ages and specific measurements. This study has provided reference values for Latinos of both sexes older than 1 year. Our results are comparable to studies performed in different populations.
Addition of the electrocardiogram to the preparticipation examination of college athletes.
Le, Vy-Van; Wheeler, Matthew T; Mandic, Sandra; Dewey, Frederick; Fonda, Holly; Perez, Marco; Sungar, Gannon; Garza, Daniel; Ashley, Euan A; Matheson, Gordon; Froelicher, Victor
2010-03-01
Although the use of standardized cardiovascular (CV) system-focused history and physical examination is recommended for the preparticipation examination (PPE) of athletes, the addition of the electrocardiogram (ECG) has been controversial. Because the impact of ECG screening on college athletes has rarely been reported, we analyzed the findings of adding the ECG to the PPE of Stanford athletes. For the past 15 years, the Stanford Sports Medicine program has mandated a PPE questionnaire and physical examination by Stanford physicians for participation in intercollegiate athletics. In 2007, computerized ECGs with digital measurements were recorded on athletes and entered into a database. Although the use of standardized CV-focused history and physical examination are recommended for the PPE of athletes, the addition of the ECG has been controversial. Because the feasibility and outcomes of ECG screening on college athletes have rarely been reported, we present findings derived from the addition of the ECG to the PPE of Stanford athletes. For the past 15 years, the Stanford Sports Medicine program has mandated a PPE questionnaire and physical examination by Stanford physicians for participation in intercollegiate athletics. In 2007, computerized ECGs with digital measurements were recorded on athletes and entered into a database. Six hundred fifty-eight recordings were obtained (54% men, 10% African-American, mean age 20 years) representing 24 sports. Although 68% of the women had normal ECGs, only 38% of the men did so. Incomplete right bundle branch block (RBBB) (13%), right axis deviation (RAD) (10%), and atrial abnormalities (3%) were the 3 most common minor abnormalities. Sokolow-Lyon criteria for left ventricular hypertrophy (LVH) were found in 49%; however, only 27% had a Romhilt-Estes score of >or=4. T-wave inversion in V2 to V3 occurred in 7%, and only 5 men had abnormal Q-waves. Sixty-three athletes (10%) were judged to have distinctly abnormal ECG findings possibly associated with conditions including hypertrophic cardiomyopathy or arrhythmogenic right ventricular dysplasia/cardiomyopathy. These athletes were offered further testing but this was not mandated according to the research protocol. Six hundred fifty-three recordings were obtained (54% men, 7% African American, mean age 20 years), representing 24 sports. Although 68% of the women had normal ECGs, only 38% of the men did so. Incomplete RBBB (13%), RAD (10%), and atrial abnormalities (3%) were the 3 most common minor abnormalities. Sokolow-Lyon criteria for LVH were found in 49%; however, only 27% had a Romhilt-Estes score of >or=4. T-wave inversion in V2 to V3 occurred in 7% and only 5 men had abnormal Q-waves. Sixty-five athletes (10%) were judged to have distinctly abnormal ECG findings suggestive of arrhythmogenic right ventricular dysplasia, hypertrophic cardiomyopathy, and/or biventricular hypertrophy. These athletes will be submitted to further testing. Mass ECG screening is achievable within the collegiate setting by using volunteers when the appropriate equipment is available. However, the rate of secondary testing suggests the need for an evaluation of cost-effectiveness for mass screening and the development of new athlete-specific ECG interpretation algorithms.
Robust detection of heartbeats using association models from blood pressure and EEG signals.
Jeon, Taegyun; Yu, Jongmin; Pedrycz, Witold; Jeon, Moongu; Lee, Boreom; Lee, Byeongcheol
2016-01-15
The heartbeat is fundamental cardiac activity which is straightforwardly detected with a variety of measurement techniques for analyzing physiological signals. Unfortunately, unexpected noise or contaminated signals can distort or cut out electrocardiogram (ECG) signals in practice, misleading the heartbeat detectors to report a false heart rate or suspend itself for a considerable length of time in the worst case. To deal with the problem of unreliable heartbeat detection, PhysioNet/CinC suggests a challenge in 2014 for developing robust heart beat detectors using multimodal signals. This article proposes a multimodal data association method that supplements ECG as a primary input signal with blood pressure (BP) and electroencephalogram (EEG) as complementary input signals when input signals are unreliable. If the current signal quality index (SQI) qualifies ECG as a reliable input signal, our method applies QRS detection to ECG and reports heartbeats. Otherwise, the current SQI selects the best supplementary input signal between BP and EEG after evaluating the current SQI of BP. When BP is chosen as a supplementary input signal, our association model between ECG and BP enables us to compute their regular intervals, detect characteristics BP signals, and estimate the locations of the heartbeat. When both ECG and BP are not qualified, our fusion method resorts to the association model between ECG and EEG that allows us to apply an adaptive filter to ECG and EEG, extract the QRS candidates, and report heartbeats. The proposed method achieved an overall score of 86.26 % for the test data when the input signals are unreliable. Our method outperformed the traditional method, which achieved 79.28 % using QRS detector and BP detector from PhysioNet. Our multimodal signal processing method outperforms the conventional unimodal method of taking ECG signals alone for both training and test data sets. To detect the heartbeat robustly, we have proposed a novel multimodal data association method of supplementing ECG with a variety of physiological signals and accounting for the patient-specific lag between different pulsatile signals and ECG. Multimodal signal detectors and data-fusion approaches such as those proposed in this article can reduce false alarms and improve patient monitoring.
Ichihashi, Taku; Ito, Tsuyoshi; Murai, Shunsuke; Ikehara, Noriyuki; Fujita, Hiroshi; Suda, Hisao; Ohte, Nobuyuki
2016-09-01
A 58-year-old man was referred to our hospital because of chest pain. The 12-lead electrocardiogram (ECG) revealed ST-segment elevation in II, III, and a Vf with advanced heart block. Transthoracic echocardiography demonstrated aortic root dilatation at the sinus of Valsalva, moderate aortic regurgitation, and decreased wall motion in the inferior part of the left ventricle. Non-ECG-gated enhanced computed tomography (CT) did not reveal an aortic dissection. The patient underwent emergent coronary angiography, which revealed a severely narrowed ostium of the right coronary artery (RCA). Percutaneous coronary intervention (PCI) was performed under intravascular ultrasound (IVUS) guidance. IVUS images demonstrated an intimal flap extending from the aortic wall to the proximal RCA, suggesting that a periaortic hematoma in the false lumen compressed the ostium of the RCA, leading to acute myocardial infarction. To recover hemodynamic stability, the RCA ostium was stented. Subsequent ECG-gated enhanced CT clearly depicted the entry point and extension of the dissection localized within the sinus of Valsalva. The dissection likely involved the left main coronary artery and an emergent Bentall procedure was performed. Intraoperative findings confirmed an intimal tear and extension of the dissection. Thus, ECG-gated CT can clearly depict the entry site and extension of a dissection occurring in the localized area that cannot be detected by conventional CT.
NOTE: Solving the ECG forward problem by means of a meshless finite element method
NASA Astrophysics Data System (ADS)
Li, Z. S.; Zhu, S. A.; He, Bin
2007-07-01
The conventional numerical computational techniques such as the finite element method (FEM) and the boundary element method (BEM) require laborious and time-consuming model meshing. The new meshless FEM only uses the boundary description and the node distribution and no meshing of the model is required. This paper presents the fundamentals and implementation of meshless FEM and the meshless FEM method is adapted to solve the electrocardiography (ECG) forward problem. The method is evaluated on a single-layer torso model, in which the analytical solution exists, and tested in a realistic geometry homogeneous torso model, with satisfactory results being obtained. The present results suggest that the meshless FEM may provide an alternative for ECG forward solutions.
An ECG electrode-mounted heart rate, respiratory rhythm, posture and behavior recording system.
Yoshimura, Takahiro; Yonezawa, Yoshiharu; Maki, Hiromichi; Ogawa, Hidekuni; Ninomiya, Ishio; Morton Caldwell, W
2004-01-01
R-R interval, respiration rhythm, posture and behavior recording system has been developed for monitoring a patient's cardiovascular regulatory system in daily life. The recording system consists of three ECG chest electrodes, a variable gain instrumentation amplifier, a dual axis accelerometer, a low power 8-bit single-chip microcomputer and a 1024 KB EEPROM. The complete system is mounted on the chest electrodes. R-R interval and respiration rhythm are calculated by the R waves detected from the ECG. Posture and behavior such as walking and running are detected from the body movements recorded by the accelerometer. The detected data are stored by the EEPROM and, after recording, are downloaded to a desktop computer for analysis.
Improving ECG Competence in Medical Trainees in a UK District General Hospital
McAloon, Christopher; Leach, Helen; Gill, Simrat; Aluwalia, Arun; Trevelyan, Jasper
2014-01-01
Background Competency in electrocardiogram (ECG) interpretation is central to undergraduate and postgraduate clinical training. Studies have demonstrated ECGs are interpreted sub-optimally. Our study compares the effectiveness of two learning strategies to improve competence and confidence. Method A 1-month prospective randomized study compared the strategies in two cohorts: undergraduate third year medical students and postgraduate foundation year one (FY1) doctors. Both had blinded randomization to one of these learning strategies: focused teaching program (FTP) and self-directed learning (SDL). All volunteers completed a confidence questionnaire before and after allocation learning strategy and an ECG recognition multiple choice question (MCQ) paper at the end of the learning period. Results The FTP group of undergraduates demonstrated a significant difference in successfully interpreting “ventricular tachycardia” (P = 0.046) and “narrow complex tachycardia” (P = 0.009) than the SDL group. Participant confidence increased in both learning strategies. FTP confidence demonstrated a greater improvement than SDL for both cohorts. Conclusion A dedicated teaching program can improve trainee confidence and competence in ECG interpretation. A larger benefit is observed in undergraduates and those undertaking a FTP. PMID:28392875
Czekajska-Chehab, Elżbieta; Tomaszewska, Monika; Olchowik, Grażyna; Tomaszewski, Marek; Adamczyk, Piotr; Drop, Andrzej
2012-07-01
Lipomatous hypertrophy of the interatrial septum (LHIS) is a benign disorder characterized by fat accumulation in the interatrial septum (IAS). The purpose of the study was to analyze the incidental detection of LHIS in patients with various clinical conditions, referred to ECG-gated multislice computed tomography (ECG-MSCT) examinations of the heart. The ECG-MSCT examinations of 5786 patients (2839 women; 2947 men), were analyzed. The examinations were performed using 8-row (1015 patients) and 64-row (4771 patients) MSCT, in pre- and postcontrast scanning. We analyzed the shape of the IAS, density and maximal thickness of IAS, the thickness of the epicardial adipose tissue, and the degree of contact of IAS with the ascending aorta and superior vena cava. We also determined body mass index (BMI) in patients with LHIS. LHIS was detected in 56 (0.96%) patients, with an average age of 61.5±9.8 years. The mean BMI in the analyzed group was 30.1±4.86. During the end-diastolic phase the thickness of IAS was significantly higher (p<0.0001), and on average equaled 18.3 mm. The mean optical density of the IAS was conspicuously higher (p<0.0001) in post-contrast phase than in pre-contrast phase. The thickness of the epicardial adipose tissue in the region of the left atrioventricular groove was on average 15 mm. In all cases the dumbbell shape of IAS was observed. The incidental frequency of LHIS occurrence in patients diagnosed with the ECG-MSCT examinations is about 1%. In most subjects it is linked with a higher BMI and increased thickness of the epicardial adipose tissue.
Kim, Kye-Hwan; Jeon, Kyung Nyeo; Kang, Min Gyu; Ahn, Jong Hwa; Koh, Jin-Sin; Park, Yongwhi; Hwang, Seok-Jae; Jeong, Young-Hoon; Kwak, Choong Hwan; Hwang, Jin-Yong; Park, Jeong Rang
2016-01-01
Background/Aims: This study is a head-to-head comparison of predictive values for long-term cardiovascular outcomes between exercise electrocardiography (ex-ECG) and computed tomography coronary angiography (CTCA) in patients with chest pain. Methods: Four hundred and forty-two patients (mean age, 56.1 years; men, 61.3%) who underwent both ex-ECG and CTCA for evaluation of chest pain were included. For ex-ECG parameters, the patients were classified according to negative or positive results, and Duke treadmill score (DTS). Coronary artery calcium score (CACS), presence of plaque, and coronary artery stenosis were evaluated as CTCA parameters. Cardiovascular events for prognostic evaluation were defined as unstable angina, acute myocardial infarction, revascularization, heart failure, and cardiac death. Results: The mean follow-up duration was 2.8 ± 1.1 years. Fifteen patients experienced cardiovascular events. Based on pretest probability, the low- and intermediate-risks of coronary artery disease were 94.6%. Odds ratio of CACS > 40, presence of plaque, coronary stenosis ≥ 50% and DTS ≤ 4 were significant (3.79, p = 0.012; 9.54, p = 0.030; 6.99, p < 0.001; and 4.58, p = 0.008, respectively). In the Cox regression model, coronary stenosis ≥ 50% (hazard ratio, 7.426; 95% confidence interval, 2.685 to 20.525) was only significant. After adding DTS ≤ 4 to coronary stenosis ≥ 50%, the integrated discrimination improvement and net reclassification improvement analyses did not show significant. Conclusions: CTCA was better than ex-ECG in terms of predicting long-term outcomes in low- to intermediate-risk populations. The predictive value of the combination of CTCA and ex-ECG was not superior to that of CTCA alone. PMID:27017387
Cheng, Li-Fang; Chen, Tung-Chien; Chen, Liang-Gee
2012-01-01
Most of the abnormal cardiac events such as myocardial ischemia, acute myocardial infarction (AMI) and fatal arrhythmia can be diagnosed through continuous electrocardiogram (ECG) analysis. According to recent clinical research, early detection and alarming of such cardiac events can reduce the time delay to the hospital, and the clinical outcomes of these individuals can be greatly improved. Therefore, it would be helpful if there is a long-term ECG monitoring system with the ability to identify abnormal cardiac events and provide realtime warning for the users. The combination of the wireless body area sensor network (BASN) and the on-sensor ECG processor is a possible solution for this application. In this paper, we aim to design and implement a digital signal processor that is suitable for continuous ECG monitoring and alarming based on the continuous wavelet transform (CWT) through the proposed architectures--using both programmable RISC processor and application specific integrated circuits (ASIC) for performance optimization. According to the implementation results, the power consumption of the proposed processor integrated with an ASIC for CWT computation is only 79.4 mW. Compared with the single-RISC processor, about 91.6% of the power reduction is achieved.
Madeiro, João P V; Nicolson, William B; Cortez, Paulo C; Marques, João A L; Vázquez-Seisdedos, Carlos R; Elangovan, Narmadha; Ng, G Andre; Schlindwein, Fernando S
2013-08-01
This paper presents an innovative approach for T-wave peak detection and subsequent T-wave end location in 12-lead paced ECG signals based on a mathematical model of a skewed Gaussian function. Following the stage of QRS segmentation, we establish search windows using a number of the earliest intervals between each QRS offset and subsequent QRS onset. Then, we compute a template based on a Gaussian-function, modified by a mathematical procedure to insert asymmetry, which models the T-wave. Cross-correlation and an approach based on the computation of Trapezium's area are used to locate, respectively, the peak and end point of each T-wave throughout the whole raw ECG signal. For evaluating purposes, we used a database of high resolution 12-lead paced ECG signals, recorded from patients with ischaemic cardiomyopathy (ICM) in the University Hospitals of Leicester NHS Trust, UK, and the well-known QT database. The average T-wave detection rates, sensitivity and positive predictivity, were both equal to 99.12%, for the first database, and, respectively, equal to 99.32% and 99.47%, for QT database. The average time errors computed for T-wave peak and T-wave end locations were, respectively, -0.38±7.12 ms and -3.70±15.46 ms, for the first database, and 1.40±8.99 ms and 2.83±15.27 ms, for QT database. The results demonstrate the accuracy, consistency and robustness of the proposed method for a wide variety of T-wave morphologies studied. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.
Multifractal analysis of electronic cardiogram taken from healthy and unhealthy adult subjects
NASA Astrophysics Data System (ADS)
Wang, Jun; Ning, Xinbao; Chen, Ying
2003-05-01
Electronic Cardiogram (ECG) data taken from healthy adult subjects are found to characterize multifractality. In order to quantitatively analyze multifractal spectrum, the area of the spectrum is computed. We have a comparison between the spectrum of the young subjects and that of the old ones. We find that the area of young adult subject's multifractal spectrum is far larger than the older one's and the logarithm of the area of the spectrum is inversely proportion to age. It shows that when time is running on human heartbeat energy is exponentially decreasing until heart failure. And distinct difference between the area of the multifractal spectrum of healthy subjects and that of having coronary disease is not found. We analyze the ECG data taken from patients with brain injury. The area of their ECG multifractal spectrum is distinctly descending. It shows that a person's multifractal spectrum is controlled mainly by his neurosystem. With advancing age, the neuroautonomic control of people's body on the ECG decreases and tends from multifractality to monofractality.
T-wave axis deviation and left ventricular hypertrophy interaction in diabetes and hypertension.
Assanelli, Deodato; Di Castelnuovo, Augusto; Rago, Livia; Badilini, Fabio; Vinetti, Giovanni; Gianfagna, Francesco; Salvetti, Massimo; Zito, Francesco; Donati, Maria Benedetta; de Gaetano, Giovanni; Iacoviello, Licia
2013-01-01
Electrocardiographic signs of left ventricular hypertrophy (ECG-LVH) and T-wave axis (TA) deviation are independent predictors of fatal and non fatal events. We assessed the prevalence of ECG-LVH, TA abnormalities and their combination according to the presence or absence of diabetes and/or hypertension in a large sample of the adult general Italian population. Data from 10,184 women (54 ± 11 years) and 8775 men (54 ± 11 years) were analyzed from the Moli-sani cohort, a database of randomly recruited adults (age >35) from the general population of Molise, a central region of Italy that includes collection of standard 12-lead resting ECG. Subjects with previous myocardial infarction, angina, cerebrovascular disease or left bundle brunch block or missing values for TA or ECG-LVH have been excluded. TA was measured from the standard 12-lead ECG and it was defined as the rotation of the T wave in the frontal plane as computed by a proprietary algorithm (CalECG/Bravo, AMPS-LLC, NY). ECG-LVH was defined as Sokolow Lyon voltage (SLv) >35 mm or Cornell voltage duration Product (CP) >= 2440 mm*ms. Among subjects with ECG-LVH, prevalence of hypertension was 59.0% and 49.7%, respectively for men and women, whereas that of diabetes was 10.7% and 5.7%. In hypertensives, TA was normal in 72.3% of subjects, borderline in 24.8% and abnormal in 2.9%. In diabetics, TA was normal in 70.4% of subjects, borderline in 26.5% and abnormal in 3.1%. In both hypertensive and diabetic subjects, the prevalence of ECG-LVH, was significantly greater in subjects with borderline or abnormal TA. Hypertension was an independent predictor of abnormal TA (odd ratio: 1.38, P = .025). These results suggest that hypertension might play a relevant role in the pathogenesis of TA deviation. © 2013.
Elhaj, Fatin A; Salim, Naomie; Harris, Arief R; Swee, Tan Tian; Ahmed, Taqwa
2016-04-01
Arrhythmia is a cardiac condition caused by abnormal electrical activity of the heart, and an electrocardiogram (ECG) is the non-invasive method used to detect arrhythmias or heart abnormalities. Due to the presence of noise, the non-stationary nature of the ECG signal (i.e. the changing morphology of the ECG signal with respect to time) and the irregularity of the heartbeat, physicians face difficulties in the diagnosis of arrhythmias. The computer-aided analysis of ECG results assists physicians to detect cardiovascular diseases. The development of many existing arrhythmia systems has depended on the findings from linear experiments on ECG data which achieve high performance on noise-free data. However, nonlinear experiments characterize the ECG signal more effectively sense, extract hidden information in the ECG signal, and achieve good performance under noisy conditions. This paper investigates the representation ability of linear and nonlinear features and proposes a combination of such features in order to improve the classification of ECG data. In this study, five types of beat classes of arrhythmia as recommended by the Association for Advancement of Medical Instrumentation are analyzed: non-ectopic beats (N), supra-ventricular ectopic beats (S), ventricular ectopic beats (V), fusion beats (F) and unclassifiable and paced beats (U). The characterization ability of nonlinear features such as high order statistics and cumulants and nonlinear feature reduction methods such as independent component analysis are combined with linear features, namely, the principal component analysis of discrete wavelet transform coefficients. The features are tested for their ability to differentiate different classes of data using different classifiers, namely, the support vector machine and neural network methods with tenfold cross-validation. Our proposed method is able to classify the N, S, V, F and U arrhythmia classes with high accuracy (98.91%) using a combined support vector machine and radial basis function method. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Near Field Communication-based telemonitoring with integrated ECG recordings
Morak, J.; Kumpusch, H.; Hayn, D.; Leitner, M.; Scherr, D.; Fruhwald, F.M.; Schreier, G.
2011-01-01
Objectives Telemonitoring of vital signs is an established option in treatment of patients with chronic heart failure (CHF). In order to allow for early detection of atrial fibrillation (AF) which is highly prevalent in the CHF population telemonitoring programs should include electrocardiogram (ECG) signals. It was therefore the aim to extend our current home monitoring system based on mobile phones and Near Field Communication technology (NFC) to enable patients acquiring their ECG signals autonomously in an easy-to-use way. Methods We prototypically developed a sensing device for the concurrent acquisition of blood pressure and ECG signals. The design of the device equipped with NFC technology and Bluetooth allowed for intuitive interaction with a mobile phone based patient terminal. This ECG monitoring system was evaluated in the course of a clinical pilot trial to assess the system’s technical feasibility, usability and patient’s adherence to twice daily usage. Results 21 patients (4f, 54 ± 14 years) suffering from CHF were included in the study and were asked to transmit two ECG recordings per day via the telemonitoring system autonomously over a monitoring period of seven days. One patient dropped out from the study. 211 data sets were transmitted over a cumulative monitoring period of 140 days (overall adherence rate 82.2%). 55% and 8% of the transmitted ECG signals were sufficient for ventricular and atrial rhythm assessment, respectively. Conclusions Although ECG signal quality has to be improved for better AF detection the developed communication design of joining Bluetooth and NFC technology in our telemonitoring system allows for ambulatory ECG acquisition with high adherence rates and system usability in heart failure patients. PMID:23616890
Development of three methods for extracting respiration from the surface ECG: a review.
Helfenbein, Eric; Firoozabadi, Reza; Chien, Simon; Carlson, Eric; Babaeizadeh, Saeed
2014-01-01
Respiration rate (RR) is a critical vital sign that can be monitored to detect acute changes in patient condition (e.g., apnea) and potentially provide an early warning of impending life-threatening deterioration. Monitoring respiration signals is also critical for detecting sleep disordered breathing such as sleep apnea. Additionally, analyzing a respiration signal can enhance the quality of medical images by gating image acquisition based on the same phase of the patient's respiratory cycle. Although many methods exist for measuring respiration, in this review we focus on three ECG-derived respiration techniques we developed to obtain respiration from an ECG signal. The first step in all three techniques is to analyze the ECG to detect beat locations and classify them. 1) The EDR method is based on analyzing the heart axis shift due to respiration. In our method, one respiration waveform value is calculated for each normal QRS complex by measuring the peak to QRS trough amplitude. Compared to other similar EDR techniques, this method does not need removal of baseline wander from the ECG signal. 2) The RSA method uses instantaneous heart rate variability to derive a respiratory signal. It is based on the observed respiratory sinus arrhythmia governed by baroreflex sensitivity. 3) Our EMGDR method for computing a respiratory waveform uses measurement of electromyogram (EMG) activity created by respiratory effort of the intercostal muscles and diaphragm. The ECG signal is high-pass filtered and processed to reduce ECG components and accentuate the EMG signal before applying RMS and smoothing. Over the last five years, we have performed six studies using the above methods: 1) In 1907 sleep lab patients with >1.5M 30-second epochs, EDR achieved an apnea detection accuracy of 79%. 2) In 24 adult polysomnograms, use of EDR and chest belts for RR computation was compared to airflow RR; mean RR error was EDR: 1.8±2.7 and belts: 0.8±2.1. 3) During cardiac MRI, a comparison of EMGDR breath locations to the reference abdominal belt signal yielded sensitivity/PPV of 94/95%. 4) Another comparison study for breath detection during MRI yielded sensitivity/PPV pairs of EDR: 99/97, RSA: 79/78, and EMGDR: 89/86%. 5) We tested EMGDR performance in the presence of simulated respiratory disease using CPAP to produce PEEP. For 10 patients, no false breath waveforms were generated with mild PEEP, but they appeared in 2 subjects at high PEEP. 6) A patient monitoring study compared RR computation from EDR to impedance-derived RR, and showed that EDR provides a near equivalent RR measurement with reduced hardware circuitry requirements. Copyright © 2014 Elsevier Inc. All rights reserved.
Ogo, Takeshi; Fukuda, Tetsuya; Tsuji, Akihiro; Fukui, Shigefumi; Ueda, Jin; Sanda, Yoshihiro; Morita, Yoshiaki; Asano, Ryotaro; Konagai, Nao; Yasuda, Satoshi
2017-04-01
Chronic thromboembolic pulmonary hypertension (CTEPH) is a disease characterized by chronic obstructive thrombus and pulmonary hypertension. Balloon pulmonary angioplasty (BPA), an emerging alternative catheter-based treatment for inoperable patients with CTEPH, has not yet been standardised, especially for lesion assessment in distal pulmonary arteries. Recent advancement in computed tomography enables distal CTEPH lesions to be visualized. We retrospectively studied 80 consecutive patients with inoperable CTEPH who received BPA guided by cone-beam computed tomography (CT) (CBCT) or electrocardiogram (ECG)-gated area detector CT (ADCT) for target lesion assessment. We collected clinical and hemodynamic data, including procedural complications, before BPA and at 3 months and 1year after BPA. Three hundred eight-five BPA sessions (4.8 sessions/patient) were performed for the lesions of subsegmental arteries (1155 lesions), segmental arteries (738 lesions), and lobar arteries (4 lesions) identified by CBCT or ECG-gated ADCT. Significant improvements in the symptoms, 6-min walk distance, brain natriuretic peptide level, exercise capacity, and haemodynamics were observed 3 months and 1year after BPA. No cases of death or cardiogenic shock with a low rate of severe wire perforation (0.3%) and severe reperfusion oedema (0.3%) were observed. BPA guided by CBCT or ECG-gated ADCT is effective and remarkably safe in patients with CTEPH . These new advanced CT techniques may be useful in pre-BPA target lesion assessment. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
ECG-derived respiration based on iterated Hilbert transform and Hilbert vibration decomposition.
Sharma, Hemant; Sharma, K K
2018-06-01
Monitoring of the respiration using the electrocardiogram (ECG) is desirable for the simultaneous study of cardiac activities and the respiration in the aspects of comfort, mobility, and cost of the healthcare system. This paper proposes a new approach for deriving the respiration from single-lead ECG based on the iterated Hilbert transform (IHT) and the Hilbert vibration decomposition (HVD). The ECG signal is first decomposed into the multicomponent sinusoidal signals using the IHT technique. Afterward, the lower order amplitude components obtained from the IHT are filtered using the HVD to extract the respiration information. Experiments are performed on the Fantasia and Apnea-ECG datasets. The performance of the proposed ECG-derived respiration (EDR) approach is compared with the existing techniques including the principal component analysis (PCA), R-peak amplitudes (RPA), respiratory sinus arrhythmia (RSA), slopes of the QRS complex, and R-wave angle. The proposed technique showed the higher median values of correlation (first and third quartile) for both the Fantasia and Apnea-ECG datasets as 0.699 (0.55, 0.82) and 0.57 (0.40, 0.73), respectively. Also, the proposed algorithm provided the lowest values of the mean absolute error and the average percentage error computed from the EDR and reference (recorded) respiration signals for both the Fantasia and Apnea-ECG datasets as 1.27 and 9.3%, and 1.35 and 10.2%, respectively. In the experiments performed over different age group subjects of the Fantasia dataset, the proposed algorithm provided effective results in the younger population but outperformed the existing techniques in the case of elderly subjects. The proposed EDR technique has the advantages over existing techniques in terms of the better agreement in the respiratory rates and specifically, it reduces the need for an extra step required for the detection of fiducial points in the ECG for the estimation of respiration which makes the process effective and less-complex. The above performance results obtained from two different datasets validate that the proposed approach can be used for monitoring of the respiration using single-lead ECG.
Patocka, Catherine; Turner, Joel; Wiseman, Jeffrey
2015-11-01
There is no evidence-based description of electrocardiogram (ECG) interpretation competencies for emergency medicine (EM) trainees. The first step in defining these competencies is to develop a prioritized list of adult ECG findings relevant to EM contexts. The purpose of this study was to categorize the importance of various adult ECG diagnoses and/or findings for the EM trainee. We developed a list of potentially important adult ECG diagnoses/findings and conducted a Delphi opinion-soliciting process. Participants used a 4-point Likert scale to rate the importance of each diagnosis for EM trainees. Consensus was defined as a minimum of 75% agreement at the second round or later. In the absence of consensus, stability was defined as a shift of 20% or less after successive rounds. A purposive sampling of 22 emergency physicians participated in the Delphi process, and 16 (72%) completed the process. Of those, 15 were from 11 different EM training programs across Canada and one was an expert in EM electrocardiography. Overall, 78 diagnoses reached consensus, 42 achieved stability and one diagnosis achieved neither consensus nor stability. Out of 121 potentially important adult ECG diagnoses, 53 (44%) were considered "must know" diagnoses, 61 (50%) "should know" diagnoses, and 7 (6%) "nice to know" diagnoses. We have categorized adult ECG diagnoses within an EM training context, knowledge of which may allow clinical EM teachers to establish educational priorities. This categorization will also facilitate the development of an educational framework to establish EM trainee competency in ECG interpretation.
Fujita, Hideo; Uchimura, Yuji; Waki, Kayo; Omae, Koji; Takeuchi, Ichiro; Ohe, Kazuhiko
2013-01-01
To improve emergency services for accurate diagnosis of cardiac emergency, we developed a low-cost new mobile electrocardiography system "Cloud Cardiology®" based upon cloud computing for prehospital diagnosis. This comprises a compact 12-lead ECG unit equipped with Bluetooth and Android Smartphone with an application for transmission. Cloud server enables us to share ECG simultaneously inside and outside the hospital. We evaluated the clinical effectiveness by conducting a clinical trial with historical comparison to evaluate this system in a rapid response car in the real emergency service settings. We found that this system has an ability to shorten the onset to balloon time of patients with acute myocardial infarction, resulting in better clinical outcome. Here we propose that cloud-computing based simultaneous data sharing could be powerful solution for emergency service for cardiology, along with its significant clinical outcome.
Can Functional Cardiac Age be Predicted from ECG in a Normal Healthy Population
NASA Technical Reports Server (NTRS)
Schlegel, Todd; Starc, Vito; Leban, Manja; Sinigoj, Petra; Vrhovec, Milos
2011-01-01
In a normal healthy population, we desired to determine the most age-dependent conventional and advanced ECG parameters. We hypothesized that changes in several ECG parameters might correlate with age and together reliably characterize the functional age of the heart. Methods: An initial study population of 313 apparently healthy subjects was ultimately reduced to 148 subjects (74 men, 84 women, in the range from 10 to 75 years of age) after exclusion criteria. In all subjects, ECG recordings (resting 5-minute 12-lead high frequency ECG) were evaluated via custom software programs to calculate up to 85 different conventional and advanced ECG parameters including beat-to-beat QT and RR variability, waveform complexity, and signal-averaged, high-frequency and spatial/spatiotemporal ECG parameters. The prediction of functional age was evaluated by multiple linear regression analysis using the best 5 univariate predictors. Results: Ignoring what were ultimately small differences between males and females, the functional age was found to be predicted (R2= 0.69, P < 0.001) from a linear combination of 5 independent variables: QRS elevation in the frontal plane (p<0.001), a new repolarization parameter QTcorr (p<0.001), mean high frequency QRS amplitude (p=0.009), the variability parameter % VLF of RRV (p=0.021) and the P-wave width (p=0.10). Here, QTcorr represents the correlation between the calculated QT and the measured QT signal. Conclusions: In apparently healthy subjects with normal conventional ECGs, functional cardiac age can be estimated by multiple linear regression analysis of mostly advanced ECG results. Because some parameters in the regression formula, such as QTcorr, high frequency QRS amplitude and P-wave width also change with disease in the same direction as with increased age, increased functional age of the heart may reflect subtle age-related pathologies in cardiac electrical function that are usually hidden on conventional ECG.
NASA Astrophysics Data System (ADS)
Tian, Shudong; Han, Jun; Yang, Jianwei; Zeng, Xiaoyang
2017-10-01
Electrocardiogram (ECG) can be used as a valid way for diagnosing heart disease. To fulfill ECG processing in wearable devices by reducing computation complexity and hardware cost, two kinds of adaptive filters are designed to perform QRS complex detection and motion artifacts removal, respectively. The proposed design achieves a sensitivity of 99.49% and a positive predictivity of 99.72%, tested under the MIT-BIH ECG database. The proposed design is synthesized under the SMIC 65-nm CMOS technology and verified by post-synthesis simulation. Experimental results show that the power consumption and area cost of this design are of 160 μW and 1.09 × 10 5 μm2, respectively. Project supported by the National Natural Science Foundation of China (Nos. 61574040, 61234002, 61525401).
An ECG storage and retrieval system embedded in client server HIS utilizing object-oriented DB.
Wang, C; Ohe, K; Sakurai, T; Nagase, T; Kaihara, S
1996-02-01
In the University of Tokyo Hospital, the improved client server HIS has been applied to clinical practice and physicians can order prescription, laboratory examination, ECG examination and radiographic examination, etc. directly by themselves and read results of these examinations, except medical signal waves, schema and image, on UNIX workstations. Recently, we designed and developed an ECG storage and retrieval system embedded in the client server HIS utilizing object-oriented database to take the first step in dealing with digitized signal, schema and image data and show waves, graphics, and images directly to physicians by the client server HIS. The system was developed based on object-oriented analysis and design, and implemented with object-oriented database management system (OODMS) and C++ programming language. In this paper, we describe the ECG data model, functions of the storage and retrieval system, features of user interface and the result of its implementation in the HIS.
Conti, A; Bianchi, S; Grifoni, C; Trausi, F; Angeli, E; Paolini, D; Catarzi, S; Perrotta, M E; Covelli, A; Renzi, N; Bertolini, P; Mazzucchelli, M
2015-06-01
The novel exercise computer-assisted high-frequency QRS-analysis (ex-HF/QRS) has demonstrated improved sensitivity and specificity over the conventional exercise-ST/ECG-segment-analysis (ex-ST/ECG) in the detection of myocardial ischemia. The aim of the present study was to test the implementation in diagnostic value of the ex-HF/QRS in patient with hypertension and chest pain (CP) versus the conventional ex-ST/ECG anlysis alone. Patients with long-standing hypertension, CP, normal ECG, troponin and echocardiography were enrolled. All patients underwent the ex-ST/ECG and ex-HF/QRS. A decrease >/=50% of the signal of ex-HF/QRS intensity recorded in two contiguous leads, at least, was considered as index of ischaemia, as ST-segment depression >/=2 mm or >/=1 mm and CP on ex-ST/ECG. Exclusion criteria were QRS duration >/=120 msec and inability to exercise. The end-point was the composite of coronary stenosis >50% or acute coronary syndrome, revascularization, cardiovascular death at 3-month follow-up. Six-hundred thirty-one patients were enrolled (age 61+/-15 y). The percentage of age-adjusted maximal predicted heart rate was 88+/-10 beat-per-minute and the maximal systolic blood pressure was 169+/-22 mmHg. Twenty-seven patients achieved the end-point. On multivariate analysis, both the ex-ST/ECG and ex-HF/QRS were predictors of the end-point. The ex-HF/QRS showed higher sensitivity (88% vs 50%; p = 0.003), lower specificity (77% vs 97%; p = 0.245) and comparable negative predictive value (99% vs 99%; p = NS) when compared to ex-ST/ECG. Receiver operator characteristics (ROC) analysis showed the incremental diagnostic value of the ex-HF/QRS (area: 0.64, 95% Confidence Intervals, CI 0.51-0.77) over conventional ex-ST/ECG (0.60, CI 0.52-0.66) and Chest Pain Score (0.53, CI 0.48-0.59); p = NS on pairwise C-statistic. In patients with long-standing hypertension and CP submitted to risk stratification with exercise tolerance test, the novel ex-HF/QRS shows a valuable incremental diagnostic value over ex-ST/ECG.
Evolutionary computing based approach for the removal of ECG artifact from the corrupted EEG signal.
Priyadharsini, S Suja; Rajan, S Edward
2014-01-01
Electroencephalogram (EEG) is an important tool for clinical diagnosis of brain-related disorders and problems. However, it is corrupted by various biological artifacts, of which ECG is one among them that reduces the clinical importance of EEG especially for epileptic patients and patients with short neck. To remove the ECG artifact from the measured EEG signal using an evolutionary computing approach based on the concept of Hybrid Adaptive Neuro-Fuzzy Inference System, which helps the Neurologists in the diagnosis and follow-up of encephalopathy. The proposed hybrid learning methods are ANFIS-MA and ANFIS-GA, which uses Memetic Algorithm (MA) and Genetic algorithm (GA) for tuning the antecedent and consequent part of the ANFIS structure individually. The performances of the proposed methods are compared with that of ANFIS and adaptive Recursive Least Squares (RLS) filtering algorithm. The proposed methods are experimentally validated by applying it to the simulated data sets, subjected to non-linearity condition and real polysomonograph data sets. Performance metrics such as sensitivity, specificity and accuracy of the proposed method ANFIS-MA, in terms of correction rate are found to be 93.8%, 100% and 99% respectively, which is better than current state-of-the-art approaches. The evaluation process used and demonstrated effectiveness of the proposed method proves that ANFIS-MA is more effective in suppressing ECG artifacts from the corrupted EEG signals than ANFIS-GA, ANFIS and RLS algorithm.
Fast multi-scale feature fusion for ECG heartbeat classification
NASA Astrophysics Data System (ADS)
Ai, Danni; Yang, Jian; Wang, Zeyu; Fan, Jingfan; Ai, Changbin; Wang, Yongtian
2015-12-01
Electrocardiogram (ECG) is conducted to monitor the electrical activity of the heart by presenting small amplitude and duration signals; as a result, hidden information present in ECG data is difficult to determine. However, this concealed information can be used to detect abnormalities. In our study, a fast feature-fusion method of ECG heartbeat classification based on multi-linear subspace learning is proposed. The method consists of four stages. First, baseline and high frequencies are removed to segment heartbeat. Second, as an extension of wavelets, wavelet-packet decomposition is conducted to extract features. With wavelet-packet decomposition, good time and frequency resolutions can be provided simultaneously. Third, decomposed confidences are arranged as a two-way tensor, in which feature fusion is directly implemented with generalized N dimensional ICA (GND-ICA). In this method, co-relationship among different data information is considered, and disadvantages of dimensionality are prevented; this method can also be used to reduce computing compared with linear subspace-learning methods (PCA). Finally, support vector machine (SVM) is considered as a classifier in heartbeat classification. In this study, ECG records are obtained from the MIT-BIT arrhythmia database. Four main heartbeat classes are used to examine the proposed algorithm. Based on the results of five measurements, sensitivity, positive predictivity, accuracy, average accuracy, and t-test, our conclusion is that a GND-ICA-based strategy can be used to provide enhanced ECG heartbeat classification. Furthermore, large redundant features are eliminated, and classification time is reduced.
A wavelet-based ECG delineation algorithm for 32-bit integer online processing
2011-01-01
Background Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. Methods This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. Results The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. Conclusions The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra. PMID:21457580
A wavelet-based ECG delineation algorithm for 32-bit integer online processing.
Di Marco, Luigi Y; Chiari, Lorenzo
2011-04-03
Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra.
Nayan, Nazrul Anuar; Risman, Nur Sabrina; Jaafar, Rosmina
2016-07-27
Among vital signs of acutely ill hospital patients, respiratory rate (RR) is a highly accurate predictor of health deterioration. This study proposes a system that consists of a passive and non-invasive single-lead electrocardiogram (ECG) acquisition module and an ECG-derived respiratory (EDR) algorithm in the working prototype of a mobile application. Before estimating RR that produces the EDR rate, ECG signals were evaluated based on the signal quality index (SQI). The SQI algorithm was validated quantitatively using the PhysioNet/Computing in Cardiology Challenge 2011 training data set. The RR extraction algorithm was validated by adopting 40 MIT PhysioNet Multiparameter Intelligent Monitoring in Intensive Care II data set. The estimated RR showed a mean absolute error (MAE) of 1.4 compared with the ``gold standard'' RR. The proposed system was used to record 20 ECGs of healthy subjects and obtained the estimated RR with MAE of 0.7 bpm. Results indicate that the proposed hardware and algorithm could replace the manual counting method, uncomfortable nasal airflow sensor, chest band, and impedance pneumotachography often used in hospitals. The system also takes advantage of the prevalence of smartphone usage and increase the monitoring frequency of the current ECG of patients with critical illnesses.
Fahlenkamp, U L; Lembcke, A; Roesler, R; Schwenke, C; Huppertz, A; Streitparth, F; Taupitz, M; Hamm, B; Wagner, M
2013-10-01
To compare electrocardiography (ECG)-gated computed tomography angiography (CTA) with ECG-gated magnetic resonance angiography (MRA) for assessment of the left atrium (LA) and pulmonary veins (PVs). Twenty-nine consecutive patients who underwent both cardiac CTA and MRA were evaluated. Contrast-enhanced CTA was performed with prospective ECG-gating using a 320 detector row CT system. Contrast-enhanced MRA was performed with prospective ECG-gating using a 1.5 T MRI system equipped with a 32 channel cardiac coil. MRA was acquired during free-breathing with a navigator-gated inversion-recovery prepared steady-state free precession sequence. Two readers independently assessed the CTA and MRA images for vascular definition of the PVs (from 0, not visualized, to 4, excellent definition) and ostial PV diameters. Variants of LA anatomy were assessed in consensus. CTA was successfully performed in all patients with a mean radiation exposure of 5.1 ± 2.2 mSv. MRA was successfully performed in 27 of 29 patients (93 %). Visual definition of PVs was rated significantly higher on CTA compared to MRA (p < 0.0001; reader 1: excellent/good ratings of CTA versus MRA: 100% versus 86%; reader 2: excellent/good ratings of CTA versus MRA: 99% versus 89%). Assessment of ostial PV diameters showed good correlation between CTA and MRA (reader 1: Pearson r = 0.91; reader 2: Pearson r = 0.82). Moreover, agreement between both imaging methods for evaluation of variants of LA anatomy was high (agreement rate of 95% (95% CI: 92-99%). ECG-gated CTA provides higher image quality compared to ECG-gated MRA. Nevertheless, both CTA and MRA provided similar information of LA anatomy and ostial PV diameters. Copyright © 2013 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xie, Xueqian; Greuter, Marcel J. W.; Groen, Jaap M.
Purpose: Coronary artery calcium score, traditionally based on electrocardiography (ECG)-triggered computed tomography (CT), predicts cardiovascular risk. However, nontriggered CT is extensively utilized. The study-purpose is to evaluate the in vitro agreement in coronary calcium score between nontriggered thoracic CT and ECG-triggered cardiac CT.Methods: Three artificial coronary arteries containing calcifications of different densities (high, medium, and low), and sizes (large, medium, and small), were studied in a moving cardiac phantom. Two 64-detector CT systems were used. The phantom moved at 0–90 mm/s in nontriggered low-dose CT as index test, and at 0–30 mm/s in ECG-triggered CT as reference. Differences in calciummore » scores between nontriggered and ECG-triggered CT were analyzed by t-test and 95% confidence interval. The sensitivity to detect calcification was calculated as the percentage of positive calcium scores.Results: Overall, calcium scores in nontriggered CT were not significantly different to those in ECG-triggered CT (p > 0.05). Calcium scores in nontriggered CT were within the 95% confidence interval of calcium scores in ECG-triggered CT, except predominantly at higher velocities (≥50 mm/s) for the high-density and large-size calcifications. The sensitivity for a nonzero calcium score was 100% for large calcifications, but 46%± 11% for small calcifications in nontriggered CT.Conclusions: When performing multiple measurements, good agreement in positive calcium scores is found between nontriggered thoracic and ECG-triggered cardiac CT. Agreement decreases with increasing coronary velocity. From this phantom study, it can be concluded that a high calcium score can be detected by nontriggered CT, and thus, that nontriggered CT likely can identify individuals at high risk of cardiovascular disease. On the other hand, a zero calcium score in nontriggered CT does not reliably exclude coronary calcification.« less
Non-ECG-gated unenhanced MRA of the carotids: optimization and clinical feasibility.
Raoult, H; Gauvrit, J Y; Schmitt, P; Le Couls, V; Bannier, E
2013-11-01
To optimise and assess the clinical feasibility of a carotid non-ECG-gated unenhanced MRA sequence. Sixteen healthy volunteers and 11 patients presenting with internal carotid artery (ICA) disease underwent large field-of-view balanced steady-state free precession (bSSFP) unenhanced MRA at 3T. Sampling schemes acquiring the k-space centre either early (kCE) or late (kCL) in the acquisition window were evaluated. Signal and image quality was scored in comparison to ECG-gated kCE unenhanced MRA and TOF. For patients, computed tomography angiography was used as the reference. In volunteers, kCE sampling yielded higher image quality than kCL and TOF, with fewer flow artefacts and improved signal homogeneity. kCE unenhanced MRA image quality was higher without ECG-gating. Arterial signal and artery/vein contrast were higher with both bSSFP sampling schemes than with TOF. The kCE sequence allowed correct quantification of ten significant stenoses, and it facilitated the identification of an infrapetrous dysplasia, which was outside of the TOF imaging coverage. Non-ECG-gated bSSFP carotid imaging offers high-quality images and is a promising sequence for carotid disease diagnosis in a short acquisition time with high spatial resolution and a large field of view. • Non-ECG-gated unenhanced bSSFP MRA offers high-quality imaging of the carotid arteries. • Sequences using early acquisition of the k-space centre achieve higher image quality. • Non-ECG-gated unenhanced bSSFP MRA allows quantification of significant carotid stenosis. • Short MR acquisition times and ungated sequences are helpful in clinical practice. • High 3D spatial resolution and a large field of view improve diagnostic performance.
Pangerc, Urška; Jager, Franc
2015-08-01
In this work, we present the development, architecture and evaluation of a new and robust heart beat detector in multimodal records. The detector uses electrocardiogram (ECG) signals, and/or pulsatile (P) signals, such as: blood pressure, artery blood pressure and pulmonary artery pressure, if present. The base approach behind the architecture of the detector is collecting signal energy (differentiating and low-pass filtering, squaring, integrating). To calculate the detection and noise functions, simple and fast slope- and peak-sensitive band-pass digital filters were designed. By using morphological smoothing, the detection functions were further improved and noise intervals were estimated. The detector looks for possible pacemaker heart rate patterns and repairs the ECG signals and detection functions. Heart beats are detected in each of the ECG and P signals in two steps: a repetitive learning phase and a follow-up detecting phase. The detected heart beat positions from the ECG signals are merged into a single stream of detected ECG heart beat positions. The merged ECG heart beat positions and detected heart beat positions from the P signals are verified for their regularity regarding the expected heart rate. The detected heart beat positions of a P signal with the best match to the merged ECG heart beat positions are selected for mapping into the noise and no-signal intervals of the record. The overall evaluation scores in terms of average sensitivity and positive predictive values obtained on databases that are freely available on the Physionet website were as follows: the MIT-BIH Arrhythmia database (99.91%), the MGH/MF Waveform database (95.14%), the augmented training set of the follow-up phase of the PhysioNet/Computing in Cardiology Challenge 2014 (97.67%), and the Challenge test set (93.64%).
Kligfield, Paul; Badilini, Fabio; Rowlandson, Ian; Xue, Joel; Clark, Elaine; Devine, Brian; Macfarlane, Peter; de Bie, Johan; Mortara, David; Babaeizadeh, Saeed; Gregg, Richard; Helfenbein, Eric D; Green, Cynthia L
2014-02-01
Automated measurements of electrocardiographic (ECG) intervals are widely used by clinicians for individual patient diagnosis and by investigators in population studies. We examined whether clinically significant systematic differences exist in ECG intervals measured by current generation digital electrocardiographs from different manufacturers and whether differences, if present, are dependent on the degree of abnormality of the selected ECGs. Measurements of RR interval, PR interval, QRS duration, and QT interval were made blindly by 4 major manufacturers of digital electrocardiographs used in the United States from 600 XML files of ECG tracings stored in the US FDA ECG warehouse and released for the purpose of this study by the Cardiac Safety Research Consortium. Included were 3 groups based on expected QT interval and degree of repolarization abnormality, comprising 200 ECGs each from (1) placebo or baseline study period in normal subjects during thorough QT studies, (2) peak moxifloxacin effect in otherwise normal subjects during thorough QT studies, and (3) patients with genotyped variants of congenital long QT syndrome (LQTS). Differences of means between manufacturers were generally small in the normal and moxifloxacin subjects, but in the LQTS patients, differences of means ranged from 2.0 to 14.0 ms for QRS duration and from 0.8 to 18.1 ms for the QT interval. Mean absolute differences between algorithms were similar for QRS duration and QT intervals in the normal and in the moxifloxacin subjects (mean ≤6 ms) but were significantly larger in patients with LQTS. Small but statistically significant group differences in mean interval and duration measurements and means of individual absolute differences exist among automated algorithms of widely used, current generation digital electrocardiographs. Measurement differences, including QRS duration and the QT interval, are greatest for the most abnormal ECGs. © 2014.
Kim, Youn-Jung; Min, Sun-Yang; Lee, Dong Hun; Lee, Byung Kook; Jeung, Kyung Woon; Lee, Hui Jai; Shin, Jonghwan; Ko, Byuk Sung; Ahn, Shin; Nam, Gi-Byoung; Lim, Kyoung Soo; Kim, Won Young
2017-03-13
The authors aimed to evaluate the role of post-resuscitation electrocardiogram (ECG) in patients showing significant ST-segment changes on the initial ECG and to provide useful diagnostic indicators for physicians to determine in which out-of-hospital cardiac arrest (OHCA) patients brain computed tomography (CT) should be performed before emergency coronary angiography. The usefulness of immediate brain CT and ECG for all resuscitated patients with nontraumatic OHCA remains controversial. Between January 2010 and December 2014, 1,088 consecutive adult nontraumatic patients with return of spontaneous circulation who visited the emergency department of 3 tertiary care hospitals were enrolled. After excluding 245 patients with obvious extracardiac causes, 200 patients were finally included. The patients were categorized into 2 groups: those with ST-segment changes with spontaneous subarachnoid hemorrhage (SAH) (n = 50) and those with OHCA of suspected cardiac origin group (n = 150). The combination of 4 ECG characteristics including narrow QRS (<120 ms), atrial fibrillation, prolonged QTc interval (≥460 ms), and ≥4 ST-segment depressions had a 66.0% sensitivity, 80.0% specificity, 52.4% positive predictive value, and 87.6% negative predictive value for predicting SAH. The area under the receiver-operating characteristic curves in the post-resuscitation ECG findings was 0.816 for SAH. SAH was observed in a substantial number of OHCA survivors (25.0%) with significant ST-segment changes on post-resuscitation ECG. Resuscitated patients with narrow QRS complex and any 2 ECG findings of atrial fibrillation, QTc interval prolongation, or ≥4 ST-segment depressions may help identify patients who need brain CT as the next diagnostic work-up. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Montassier, Emmanuel; Hardouin, Jean-Benoît; Segard, Julien; Batard, Eric; Potel, Gilles; Planchon, Bernard; Trochu, Jean-Noël; Pottier, Pierre
2016-04-01
An ECG is pivotal for the diagnosis of coronary heart disease. Previous studies have reported deficiencies in ECG interpretation skills that have been responsible for misdiagnosis. However, the optimal way to acquire ECG interpretation skills is still under discussion. Thus, our objective was to compare the effectiveness of e-learning and lecture-based courses for learning ECG interpretation skills in a large randomized study. We conducted a prospective, randomized, controlled, noninferiority study. Participants were recruited from among fifth-year medical students and were assigned to the e-learning group or the lecture-based group using a computer-generated random allocation sequence. The e-learning and lecture-based groups were compared on a score of effectiveness, comparing the 95% unilateral confidence interval (95% UCI) of the score of effectiveness with the mean effectiveness in the lecture-based group, adjusted for a noninferiority margin. Ninety-eight students were enrolled. As compared with the lecture-based course, e-learning was noninferior with regard to the postcourse test score (15.1; 95% UCI 14.2; +∞), which can be compared with 12.5 [the mean effectiveness in the lecture-based group (15.0) minus the noninferiority margin (2.5)]. Furthermore, there was a significant increase in the test score points in both the e-learning and lecture-based groups during the study period (both P<0.0001). Our randomized study showed that the e-learning course is an effective tool for the acquisition of ECG interpretation skills by medical students. These preliminary results should be confirmed with further multicenter studies before the implementation of e-learning courses for learning ECG interpretation skills during medical school.
Electrocardiogram abnormalities and coronary calcification in postmenopausal women.
Sabour, Siamak; Grobbee, Diederick; Rutten, Annemarieke; Prokop, Mathias; Bartelink, Marie-Louise; van der Schouw, Yvonne; Bots, Michiel
2010-01-01
An electrocardiogram (ECG) can provide information on subclinical myocardial damage. The presence, and more importantly, the quantity of coronary artery calcification (CAC), relates well with the overall severity of the atherosclerotic process. A strong relation has been demonstrated between coronary calcium burden and the incidence of myocardial infarction, a relation independent of age. The aim of this study was to assess the relation of left ventricular hypertrophy (LVH) and ECG abnormalities with CAC. The study population comprised 566 postmenopausal women selected from a population-based cohort study. Information on LVH and repolarization abnormalities (T-axis and QRS-T angle) was obtained using electrocardiography. Modular ECG Analysis System (MEANS) was used to assess ECG abnormalities. The women underwent a multi detector-row computed tomography (MDCT) scan (Philips Mx 8000 IDT 16) to assess CAC. The Agatston score was used to quantify CAC; scores greater than zero were considered as the presence of coronary calcium. Logistic regression was used to assess the relation of ECG abnormality with coronary calcification. LVH was found in 2.7% (n = 15) of the women. The prevalence of T-axis abnormality was 6% (n = 34), whereas 8.5% (n = 48) had a QRS-T angle abnormality. CAC was found in 62% of the women. Compared to women with a normal T-axis, women with borderline or abnormal T-axes were 3.8 fold more likely to have CAC (95% CI: 1.4-10.2). Similarly, compared to women with a normal QRS-T angle, in women with borderline or abnormal QRS-T angle, CAC was 2.0 fold more likely to be present (95% CI: 1.0-4.1). Among women with ECG abnormalities reflecting subclinical ischemia, CAC is commonly found and may in part explain the increased coronary heart disease risk associated with these ECG abnormalities.
Guzik, Przemyslaw; Piekos, Caroline; Pierog, Olivia; Fenech, Naiman; Krauze, Tomasz; Piskorski, Jaroslaw; Wykretowicz, Andrzej
2018-05-01
We compared classic ECG-derived versus a mobile approach to heart rate variability (HRV) measurement. 29 young adult healthy volunteers underwent a simultaneous recording of heart rate using an ECG and a chest heart rate monitor at supine rest, during mental stress and active standing. Mean RR interval, Standard Deviation of Normal-to-Normal (SDNN) of RR intervals, and Root Mean Square of the Successive Differences (RMSSD) between RR intervals were computed in 168 pairs of 5-minute epochs by in-house software on a PC (only sinus beats) and by mobile application "ELITEHRV" on a smartphone (no beat type identification). ECG analysis showed that 33.9% of the recordings contained at least one non-sinus beat or artefact, the mobile app did not report this. The mean RR intervals were significantly longer (p = 0.0378), while SDNN (p = 0.0001) and RMSSD (p = 0.0199) were smaller for the mobile approach. Measures of identical HRV parameters by ECG-based and mobile approaches are not equivalent. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Smith, J. M.; Blue, B.; Clancy, E.; Valeri, C. R.; Cohen, R. J.
1985-01-01
Observations from finite-element computer models, together with analytic developments based on percolation theory have suggested that subtle fluctuations of ECG morphology might serve as an indicator diminished cardiac electrical stability. With fixed-rate atrial pacing in canines, we have previously observed a pattern of alternation in T wave energy which correlated with cardiac electrical stability. We report here on a series of 20 canine experiments in which cardiac electrical stability (measured via Ventricular Fibrillation Threshold determination) was compared to a non-degenerate, multidimensional measurement of the degree of alternating activity present in the ECG complex morphology. The decrease in cardiac electrical stability brought on by both coronary artery occlusion and systemic hypothermia was consistently accompanied by subtle alternation in ECG morphology, with the absolute degree of alternating activity being significantly (negatively) correlated with cardiac electrical stability.
[An ultra-low power, wearable, long-term ECG monitoring system with mass storage].
Liu, Na; Chen, Yingmin; Zhang, Wenzan; Luo, Zhangyuan; Jin, Xun; Ying, Weihai
2012-01-01
In this paper, we described an ultra-low power, wearable ECG system capable of long term monitoring and mass storage. This system is based on micro-chip PIC18F27J13 with consideration of its high level of integration and low power consumption. The communication with the micro-SD card is achieved through SPI bus. Through the USB, it can be connected to the computer for replay and disease diagnosis. Given its low power cost, lithium cells are used to support continuous ECG acquiring and storage for up to 15 days. Meanwhile, the wearable electrodes avoid the pains and possible risks in implanting. Besides, the mini size of the system makes long wearing possible for patients and meets the needs of long-term dynamic monitoring and mass storage requirements.
Automated Agatston score computation in non-ECG gated CT scans using deep learning
NASA Astrophysics Data System (ADS)
Cano-Espinosa, Carlos; González, Germán.; Washko, George R.; Cazorla, Miguel; San José Estépar, Raúl
2018-03-01
Introduction: The Agatston score is a well-established metric of cardiovascular disease related to clinical outcomes. It is computed from CT scans by a) measuring the volume and intensity of the atherosclerotic plaques and b) aggregating such information in an index. Objective: To generate a convolutional neural network that inputs a non-contrast chest CT scan and outputs the Agatston score associated with it directly, without a prior segmentation of Coronary Artery Calcifications (CAC). Materials and methods: We use a database of 5973 non-contrast non-ECG gated chest CT scans where the Agatston score has been manually computed. The heart of each scan is cropped automatically using an object detector. The database is split in 4973 cases for training and 1000 for testing. We train a 3D deep convolutional neural network to regress the Agatston score directly from the extracted hearts. Results: The proposed method yields a Pearson correlation coefficient of r = 0.93; p <= 0.0001 against manual reference standard in the 1000 test cases. It further stratifies correctly 72.6% of the cases with respect to standard risk groups. This compares to more complex state-of-the-art methods based on prior segmentations of the CACs, which achieve r = 0.94 in ECG-gated pulmonary CT. Conclusions: A convolutional neural network can regress the Agatston score from the image of the heart directly, without a prior segmentation of the CACs. This is a new and simpler paradigm in the Agatston score computation that yields similar results to the state-of-the-art literature.
... present. CT = computed tomography; ECG = electrocardiography; ESR = erythrocyte sedimentation rate; MRI = magnetic resonance imaging. Spotlight on Aging: ... swelling is seen during the eye examination. Erythrocyte sedimentation rate (ESR) and C-reactive protein level (blood ...
Israel, Carsten W; Ekosso-Ejangue, Lucy; Sheta, Mohamed-Karim
2015-09-01
The key to a successful analysis of a pacemaker electrocardiogram (ECG) is the application of the systematic approach used for any other ECG without a pacemaker: analysis of (1) basic rhythm and rate, (2) QRS axis, (3) PQ, QRS and QT intervals, (4) morphology of P waves, QRS, ST segments and T(U) waves and (5) the presence of arrhythmias. If only the most obvious abnormality of a pacemaker ECG is considered, wrong conclusions can easily be drawn. If a systematic approach is skipped it may be overlooked that e.g. atrial pacing is ineffective, the left ventricle is paced instead of the right ventricle, pacing competes with intrinsic conduction or that the atrioventricular (AV) conduction time is programmed too long. Apart from this analysis, a pacemaker ECG which is not clear should be checked for the presence of arrhythmias (e.g. atrial fibrillation, atrial flutter, junctional escape rhythm and endless loop tachycardia), pacemaker malfunction (e.g. atrial or ventricular undersensing or oversensing, atrial or ventricular loss of capture) and activity of specific pacing algorithms, such as automatic mode switching, rate adaptation, AV delay modifying algorithms, reaction to premature ventricular contractions (PVC), safety window pacing, hysteresis and noise mode. A systematic analysis of the pacemaker ECG almost always allows a probable diagnosis of arrhythmias and malfunctions to be made, which can be confirmed by pacemaker control and can often be corrected at the touch of the right button to the patient's benefit.
Lee, Ji Won; Kim, Chang Won; Lee, Geewon; Lee, Han Cheol; Kim, Sang-Pil; Choi, Bum Sung; Jeong, Yeon Joo
2018-02-01
Background Using the hybrid electrocardiogram (ECG)-gated computed tomography (CT) technique, assessment of entire aorta, coronary arteries, and aortic valve can be possible using single-bolus contrast administration within a single acquisition. Purpose To compare the image quality of hybrid ECG-gated and non-gated CT angiography of the aorta and evaluate the effect of a motion correction algorithm (MCA) on coronary artery image quality in a hybrid ECG-gated aorta CT group. Material and Methods In total, 104 patients (76 men; mean age = 65.8 years) prospectively randomized into two groups (Group 1 = hybrid ECG-gated CT; Group 2 = non-gated CT) underwent wide-detector array aorta CT. Image quality, assessed using a four-point scale, was compared between the groups. Coronary artery image quality was compared between the conventional reconstruction and motion correction reconstruction subgroups in Group 1. Results Group 1 showed significant advantages over Group 2 in aortic wall, cardiac chamber, aortic valve, coronary ostia, and main coronary arteries image quality (all P < 0.001). All Group 1 patients had diagnostic image quality of the aortic wall and left ostium. The MCA significantly improved the image quality of the three main coronary arteries ( P < 0.05). Moreover, per-vessel interpretability improved from 92.3% to 97.1% with the MCA ( P = 0.013). Conclusion Hybrid ECG-gated CT significantly improved the heart and aortic wall image quality and the MCA can further improve the image quality and interpretability of coronary arteries.
Evaluation of Heart Rate Variability by means of Laser Doppler Vibrometry measurements
NASA Astrophysics Data System (ADS)
Cosoli, G.; Casacanditella, L.; Tomasini, EP; Scalise, L.
2015-11-01
Heart Rate Variability (HRV) analysis aims to study the physiological variability of the Heart Rate (HR), which is related to the health conditions of the subject. HRV is assessed measuring heart periods (HP) on a time window of >5 minutes (1)-(2). HPs are determined from signals of different nature: electrocardiogram (ECG), photoplethysmogram (PPG), phonocardiogram (PCG) or vibrocardiogram (VCG) (3)-(4)-(5). The fundamental aspect is the identification of a feature in each heartbeat that allows to accurately compute cardiac periods (such as R peaks in ECG), in order to make possible the measurement of all the typical HRV evaluations on those intervals. VCG is a non-contact technique (4), very favourable in medicine, which detects the vibrations on the skin surface (e.g. on the carotid artery) resulting from vascular blood motion consequent to electrical signal (ECG). In this paper, we propose the use of VCG for the measurement of a signal related to HRV and the use of a novel algorithm based on signal geometry (7) to detect signal peaks, in order to accurately determine cardiac periods and the Poincare plot (9)-(10). The results reported are comparable to the ones reached with the gold standard (ECG) and in literature (3)-(5). We report mean values of HP of 832±54 ms and 832±55 ms by means of ECG and VCG, respectively. Moreover, this algorithm allow us to identify particular features of ECG and VCG signals, so that in the future we will be able to evaluate specific correlations between the two.
NASA Astrophysics Data System (ADS)
Efstathopoulos, E. P.; Kelekis, N. L.; Pantos, I.; Brountzos, E.; Argentos, S.; Grebáč, J.; Ziaka, D.; Katritsis, D. G.; Seimenis, I.
2009-09-01
Computed tomography (CT) coronary angiography has been widely used since the introduction of 64-slice scanners and dual-source CT technology, but high radiation doses have been reported. Prospective ECG-gating using a 'step-and-shoot' axial scanning protocol has been shown to reduce radiation exposure effectively while maintaining diagnostic accuracy. 256-slice scanners with 80 mm detector coverage have been currently introduced into practice, but their impact on radiation exposure has not been adequately studied. The aim of this study was to assess radiation doses associated with CT coronary angiography using a 256-slice CT scanner. Radiation doses were estimated for 25 patients scanned with either prospective or retrospective ECG-gating. Image quality was assessed objectively in terms of mean CT attenuation at selected regions of interest on axial coronary images and subjectively by coronary segment quality scoring. It was found that radiation doses associated with prospective ECG-gating were significantly lower than retrospective ECG-gating (3.2 ± 0.6 mSv versus 13.4 ± 2.7 mSv). Consequently, the radiogenic fatal cancer risk for the patient is much lower with prospective gating (0.0176% versus 0.0737%). No statistically significant differences in image quality were observed between the two scanning protocols for both objective and subjective quality assessments. Therefore, prospective ECG-gating using a 'step-and-shoot' protocol that covers the cardiac anatomy in two axial acquisitions effectively reduces radiation doses in 256-slice CT coronary angiography without compromising image quality.
A PDA-based electrocardiogram/blood pressure telemonitor for telemedicine.
Bolanos, Marcos; Nazeran, Homayoun; Gonzalez, Izzac; Parra, Ricardo; Martinez, Christopher
2004-01-01
An electrocardiogram (ECG) / blood pressure (BP) telemonitor consisting of comprehensive integration of various electrical engineering concepts, devices, and methods was developed. This personal digital assistant-based (PDAbased) system focused on integration of biopotential amplifiers, photoplethysmographic measurement of blood pressure, microcontroller devices, programming methods, wireless transmission, signal filtering and analysis, interfacing, and long term memory devices (24 hours) to develop a state-of-the-art ECG/BP telemonitor. These instrumentation modules were developed and tested to realize a complete and compact system that could be deployed to assist in telemedicine applications and heart rate variability studies. The specific objective of this device was to facilitate the long term monitoring and recording of ECG and blood pressure signals. This device was able to acquire ECG/BP waveforms, transmit them wirelessly to a PDA, save them onto a compact flash memory, and display them on the LCD screen of the PDA. It was also capable of calculating the heart rate (HR) in beats per minute, and providing systolic and diastolic blood pressure values.
2011-01-01
Background Diagnosis of extracardiac intrathoracic vascular anomalies is of clinical importance, but remains challenging. Traditional imaging modalities, such as radiography, echocardiography, and angiography, are inherently limited by the difficulties of a 2-dimensional approach to a 3-dimensional object. We postulated that accurate characterization of malformations of the aorta would benefit from 3-dimensional assessment. Therefore, multidetector-row computed tomography (MDCT) was chosen as a 3-dimensional, new, and noninvasive imaging technique. The purpose of this study was to evaluate patients with 2 common diseases of the intrathoracic aorta, either patent ductus arteriosus or vascular ring anomaly, by contrast-enhanced 64-row computed tomography. Results Electrocardiography (ECG)-gated and thoracic nongated MDCT images were reviewed in identified cases of either a patent ductus arteriosus or vascular ring anomaly. Ductal size and morphology were determined in 6 dogs that underwent ECG-gated MDCT. Vascular ring anomalies were characterized in 7 dogs and 3 cats by ECG-gated MDCT or by a nongated thoracic standard protocol. Cardiac ECG-gated MDCT clearly displayed the morphology, length, and caliber of the patent ductus arteriosus in 6 affected dogs. Persistent right aortic arch was identified in 10 animals, 8 of which showed a coexisting aberrant left subclavian artery. A mild dilation of the proximal portion of the aberrant subclavian artery near its origin of the aorta was present in 4 dogs, and a diverticulum analogous to the human Kommerell's diverticulum was present in 2 cats. Conclusions Contrast-enhanced MDCT imaging of thoracic anomalies gives valuable information about the exact aortic arch configuration. Furthermore, MDCT was able to characterize the vascular branching patterns in dogs and cats with a persistent right aortic arch and the morphology and size of the patent ductus arteriosus in affected dogs. This additional information can be of help with regard to improved diagnoses of thoracic anomalies and the planning of surgical interventions. PMID:21943366
Yamamoto, L G
1995-03-01
The feasibility of wireless portable teleradiology and facsimile (fax) transmission using a pocket cellular phone and a notebook computer to obtain immediate access to consultants at any location was studied. Modems specially designed for data and fax communication via cellular systems were employed to provide a data communication interface between the cellular phone and the notebook computer. Computed tomography (CT) scans, X-rays, and electrocardiograms (ECGs) were transmitted to a wireless unit to measure performance characteristics. Data transmission rates ranged from 520 to 1100 bytes per second. Typical image transmission times ranged from 1 to 10 minutes; however, using joint photographic experts group or fractal image compression methods would shorten typical transmission times to less than one minute. This study showed that wireless teleradiology and fax over cellular communication systems are feasible with current technology. Routine immediate cellular faxing of ECGs to cardiologists may expedite thrombolytic therapy decisions in questionable cases. Routine immediate teleradiology of CT scans may reduce operation room preparation times in severe head trauma.
Real-Time Monitoring and Analysis of Zebrafish Electrocardiogram with Anomaly Detection.
Lenning, Michael; Fortunato, Joseph; Le, Tai; Clark, Isaac; Sherpa, Ang; Yi, Soyeon; Hofsteen, Peter; Thamilarasu, Geethapriya; Yang, Jingchun; Xu, Xiaolei; Han, Huy-Dung; Hsiai, Tzung K; Cao, Hung
2017-12-28
Heart disease is the leading cause of mortality in the U.S. with approximately 610,000 people dying every year. Effective therapies for many cardiac diseases are lacking, largely due to an incomplete understanding of their genetic basis and underlying molecular mechanisms. Zebrafish ( Danio rerio ) are an excellent model system for studying heart disease as they enable a forward genetic approach to tackle this unmet medical need. In recent years, our team has been employing electrocardiogram (ECG) as an efficient tool to study the zebrafish heart along with conventional approaches, such as immunohistochemistry, DNA and protein analyses. We have overcome various challenges in the small size and aquatic environment of zebrafish in order to obtain ECG signals with favorable signal-to-noise ratio (SNR), and high spatial and temporal resolution. In this paper, we highlight our recent efforts in zebrafish ECG acquisition with a cost-effective simplified microelectrode array (MEA) membrane providing multi-channel recording, a novel multi-chamber apparatus for simultaneous screening, and a LabVIEW program to facilitate recording and processing. We also demonstrate the use of machine learning-based programs to recognize specific ECG patterns, yielding promising results with our current limited amount of zebrafish data. Our solutions hold promise to carry out numerous studies of heart diseases, drug screening, stem cell-based therapy validation, and regenerative medicine.
Real-Time Monitoring and Analysis of Zebrafish Electrocardiogram with Anomaly Detection
Lenning, Michael; Fortunato, Joseph; Le, Tai; Clark, Isaac; Sherpa, Ang; Yi, Soyeon; Hofsteen, Peter; Thamilarasu, Geethapriya; Yang, Jingchun; Xu, Xiaolei; Hsiai, Tzung K.; Cao, Hung
2017-01-01
Heart disease is the leading cause of mortality in the U.S. with approximately 610,000 people dying every year. Effective therapies for many cardiac diseases are lacking, largely due to an incomplete understanding of their genetic basis and underlying molecular mechanisms. Zebrafish (Danio rerio) are an excellent model system for studying heart disease as they enable a forward genetic approach to tackle this unmet medical need. In recent years, our team has been employing electrocardiogram (ECG) as an efficient tool to study the zebrafish heart along with conventional approaches, such as immunohistochemistry, DNA and protein analyses. We have overcome various challenges in the small size and aquatic environment of zebrafish in order to obtain ECG signals with favorable signal-to-noise ratio (SNR), and high spatial and temporal resolution. In this paper, we highlight our recent efforts in zebrafish ECG acquisition with a cost-effective simplified microelectrode array (MEA) membrane providing multi-channel recording, a novel multi-chamber apparatus for simultaneous screening, and a LabVIEW program to facilitate recording and processing. We also demonstrate the use of machine learning-based programs to recognize specific ECG patterns, yielding promising results with our current limited amount of zebrafish data. Our solutions hold promise to carry out numerous studies of heart diseases, drug screening, stem cell-based therapy validation, and regenerative medicine. PMID:29283402
The chaos and order in human ECG under the influence of the external perturbations
NASA Astrophysics Data System (ADS)
Ragulskaya, Maria; Valeriy, Pipin
The results of the many-year telecommunication heliomedical monitoring "Heliomed" show, that space weather and geophysical factor variations serve as a training factor for the adaptation-resistant member of the human population. Here we discuss the specific properties of the human ECG discovered in our experiment. The program "Heliomed" is carried out simultaneously at the different geographical areas that cover the different latitudes. The daily registered param-eters include: the psycho-emotional tests and the 1-st lead ECG, the arterial pressure, the variability cardiac contraction, the electric conduction of bioactive points on skin. The results time series compared with daily values of space weather and geomagnetic parameters. The analysis of ECG signal proceeds as follows. At first step we construct the ECG embedding into 3D phase space using the first 3 Principal Components of the ECG time series. Next, we divide ECG on the separate cycles using the maxima of the ECG's QRS complex. Then, we filter out the non-typical ECG beats by means of the Housdorff distance. Finally, we average the example of the ECG time series along the reference trajectory and study of the dynamical characteristics of the averaged ECG beat. It is found, that the ECG signal embeded in 3D phase space can be considered as a mix of a few states. At the rest, the occurrence of the primary ECG state compare to additional ones is about 8:2. The occurrence of the primary state increases after the stress. The main effect of the external perturbation is observed in structural change of the cardio-cycle and not in the variability of the R-R interval. The num-ber of none-typical cycles increase during an isolated magnetic storm. At the all monitoring centers participating experiment the same type of changes in the cardiac activity parameters is detected to go nearly simultaneously during an isolated magnetic storm. To understand the origin of the standard cardio-cycle changes we use the dynamical model reconstruction of the individual cardiac beat. It is found that the positions of the stationary points of the typical ECG attractor are in vicinities of Q and T waves. Additionally, we find that the stiffness of the beat is important for the general stability of ECG. The given results agues for the increase the relative disorder of the human cardiac system under external perturbations due to changes in the space weather and climatic factors. Also, the results of monitoring show that cardiac system can be stabilized by "internal" (physical) stress. The given difference in the cardiac sys-tem behavior under the different types of stress is obtained in the earth labaratory conditions. However, it should be considered as important factors influencing on the health of cosmonauts during the space missions, as well.
A Modular Low-Complexity ECG Delineation Algorithm for Real-Time Embedded Systems.
Bote, Jose Manuel; Recas, Joaquin; Rincon, Francisco; Atienza, David; Hermida, Roman
2018-03-01
This work presents a new modular and low-complexity algorithm for the delineation of the different ECG waves (QRS, P and T peaks, onsets, and end). Involving a reduced number of operations per second and having a small memory footprint, this algorithm is intended to perform real-time delineation on resource-constrained embedded systems. The modular design allows the algorithm to automatically adjust the delineation quality in runtime to a wide range of modes and sampling rates, from a ultralow-power mode when no arrhythmia is detected, in which the ECG is sampled at low frequency, to a complete high-accuracy delineation mode, in which the ECG is sampled at high frequency and all the ECG fiducial points are detected, in the case of arrhythmia. The delineation algorithm has been adjusted using the QT database, providing very high sensitivity and positive predictivity, and validated with the MIT database. The errors in the delineation of all the fiducial points are below the tolerances given by the Common Standards for Electrocardiography Committee in the high-accuracy mode, except for the P wave onset, for which the algorithm is above the agreed tolerances by only a fraction of the sample duration. The computational load for the ultralow-power 8-MHz TI MSP430 series microcontroller ranges from 0.2% to 8.5% according to the mode used.
Acute aortic syndromes: new insights from electrocardiographically gated computed tomography.
Fleischmann, Dominik; Mitchell, R Scott; Miller, D Craig
2008-01-01
The development of retrospective electrocardiographic (ECG)-gating has proved to be a diagnostic and therapeutic boon for computed tomography (CT) imaging of patients with acute thoracic aortic diseases, such as aortic dissection/intramural hematoma (AD/IMH), penetrating atherosclerotic ulcer (APU), and ruptured/leaking aneurysm. The notorious pulsation motion artifacts in the ascending aorta confounding regular CT scanning can be eliminated, and involvement of the sinuses of Valsalva, the valve cusps, the aortic annulus, and the coronary arteries in aortic dissection can be clearly depicted or excluded. Motion-free images also allow reliable identification of the site of the primary intimal tear, the location, and extent of the intimomedial flap, and branch artery involvement. ECG-gated CTA also allows the detection of more subtle lesions and variants of aortic dissection, which may ultimately expand our understanding of these complex, life-threatening disorders.
Cascade Classification with Adaptive Feature Extraction for Arrhythmia Detection.
Park, Juyoung; Kang, Mingon; Gao, Jean; Kim, Younghoon; Kang, Kyungtae
2017-01-01
Detecting arrhythmia from ECG data is now feasible on mobile devices, but in this environment it is necessary to trade computational efficiency against accuracy. We propose an adaptive strategy for feature extraction that only considers normalized beat morphology features when running in a resource-constrained environment; but in a high-performance environment it takes account of a wider range of ECG features. This process is augmented by a cascaded random forest classifier. Experiments on data from the MIT-BIH Arrhythmia Database showed classification accuracies from 96.59% to 98.51%, which are comparable to state-of-the art methods.
Koski, Antti; Tossavainen, Timo; Juhola, Martti
2004-01-01
Electrocardiogram (ECG) signals are the most prominent biomedical signal type used in clinical medicine. Their compression is important and widely researched in the medical informatics community. In the previous literature compression efficacy has been investigated only in the context of how much known or developed methods reduced the storage required by compressed forms of original ECG signals. Sometimes statistical signal evaluations based on, for example, root mean square error were studied. In previous research we developed a refined method for signal compression and tested it jointly with several known techniques for other biomedical signals. Our method of so-called successive approximation quantization used with wavelets was one of the most successful in those tests. In this paper, we studied to what extent these lossy compression methods altered values of medical parameters (medical information) computed from signals. Since the methods are lossy, some information is lost due to the compression when a high enough compression ratio is reached. We found that ECG signals sampled at 400 Hz could be compressed to one fourth of their original storage space, but the values of their medical parameters changed less than 5% due to compression, which indicates reliable results.
Singh, Omkar; Sunkaria, Ramesh Kumar
2017-12-01
This paper presents a novel technique to identify heartbeats in multimodal data using electrocardiogram (ECG) and arterial blood pressure (ABP) signals. Multiple physiological signals such as ECG, ABP, and Respiration are often recorded in parallel from the activity of heart. These signals generally possess related information as they are generated by the same physical system. The ECG and ABP correspond to the same phenomenon of contraction and relaxation activity of heart. Multiple signals acquired from various sensors are generally processed independently, thus discarding the information from other measurements. In the estimation of heart rate and heart rate variability, the R peaks are generally identified from ECG signal. Efficient detection of R-peaks in electrocardiogram (ECG) is a key component in the estimation of clinically relevant parameters from ECG. However, when the signal is severely affected by undesired artifacts, this becomes a challenging task. Sometimes in clinical environment, other physiological signals reflecting the cardiac activity such as ABP signal are also acquired simultaneously. Under the availability of such multimodal signals, the accuracy of R peak detection methods can be improved using sensor-fusion techniques. In the proposed method, the sample entropy (SampEn) is used as a metric for assessing the noise content in the physiological signal and the R peaks in ECG and the systolic peaks in ABP signals are fused together to enhance the efficiency of heartbeat detection. The proposed method was evaluated on the 100 records from the computing in cardiology challenge 2014 training data set. The performance parameters are: sensitivity (Se) and positive predictivity (PPV). The unimodal R peaks detector achieved: Se gross = 99.40%, PPV gross = 99.29%, Se average = 99.37%, PPV average = 99.29%. Similarly unimodal BP delineator achieved Se gross = 99.93%, PPV gross = 99.99%, Se average = 99.93%, PPV average = 99.99% whereas, the proposed multimodal beat detector achieved: Se gross = 99.65%, PPV gross = 99.91%, Se average = 99.68%, PPV average = 99.91%.
Electrocardiogram Abnormalities and Coronary Calcification in Postmenopausal Women
Sabour, Siamak; Grobbee, Diederick; Rutten, Annemarieke; Prokop, Mathias; Bartelink, Marie-Louise; van der Schouw, Yvonne; Bots, Michiel
2010-01-01
Background: An electrocardiogram (ECG) can provide information on subclinical myocardial damage. The presence, and more importantly, the quantity of coronary artery calcification (CAC), relates well with the overall severity of the atherosclerotic process. A strong relation has been demonstrated between coronary calcium burden and the incidence of myocardial infarction, a relation independent of age. The aim of this study was to assess the relation of left ventricular hypertrophy (LVH) and ECG abnormalities with CAC. Methods: The study population comprised 566 postmenopausal women selected from a population-based cohort study. Information on LVH and repolarization abnormalities (T-axis and QRS-T angle) was obtained using electrocardiography. Modular ECG Analysis System (MEANS) was used to assess ECG abnormalities. The women underwent a multi detector-row computed tomography (MDCT) scan (Philips Mx 8000 IDT 16) to assess CAC. The Agatston score was used to quantify CAC; scores greater than zero were considered as the presence of coronary calcium. Logistic regression was used to assess the relation of ECG abnormality with coronary calcification. Results: LVH was found in 2.7% (n = 15) of the women. The prevalence of T-axis abnormality was 6% (n = 34), whereas 8.5% (n = 48) had a QRS-T angle abnormality. CAC was found in 62% of the women. Compared to women with a normal T-axis, women with borderline or abnormal T-axes were 3.8 fold more likely to have CAC (95% CI: 1.4–10.2). Similarly, compared to women with a normal QRS-T angle, in women with borderline or abnormal QRS-T angle, CAC was 2.0 fold more likely to be present (95% CI: 1.0–4.1). Conclusion: Among women with ECG abnormalities reflecting subclinical ischemia, CAC is commonly found and may in part explain the increased coronary heart disease risk associated with these ECG abnormalities. PMID:23074563
A systematic review of prenatal screening for congenital heart disease by fetal electrocardiography.
Verdurmen, Kim M J; Eijsvoogel, Noortje B; Lempersz, Carlijn; Vullings, Rik; Schroer, Christian; van Laar, Judith O E H; Oei, S Guid
2016-11-01
Congenital heart disease (CHD) is the most common severe congenital anomaly worldwide. Diagnosis early in pregnancy is important, but the detection rate by two-dimensional ultrasonography is only 65%-81%. To evaluate existing data on CHD and noninvasive abdominal fetal electrocardiography (ECG). A systematic review was performed through a search of the Cochrane Library, PubMed, and Embase for studies published up to April 2016 using the terms "congenital heart disease," "fetal electrocardiogram," and other similar keywords. Primary articles that described changes in fetal ECG among fetuses with CHD published in English were included. Outcomes of interest were changes in fetal ECG parameters observed for fetuses with congenital heart disease. Findings were reported descriptively. Only five studies described changes observed in the fetal electrocardiogram for fetuses with CHD, including heart rate, heart rate variability, and PR, QRS, and QT intervals. Fetal ECG reflects the intimate relationship between the cardiac nerve conduction system and the structural morphology of the heart. It seems particularly helpful in detecting the electrophysiological effects of cardiac anatomic defects (e.g. hypotrophy, hypertrophy, and conduction interruption). Fetal ECG might be a promising clinical tool to complement ultrasonography in the screening program for CHD. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.
Novotny, Tomas; Bond, Raymond; Andrsova, Irena; Koc, Lumir; Sisakova, Martina; Finlay, Dewar; Guldenring, Daniel; Spinar, Jindrich; Malik, Marek
2017-05-01
Most contemporary 12-lead electrocardiogram (ECG) devices offer computerized diagnostic proposals. The reliability of these automated diagnoses is limited. It has been suggested that incorrect computer advice can influence physician decision-making. This study analyzed the role of diagnostic proposals in the decision process by a group of fellows of cardiology and other internal medicine subspecialties. A set of 100 clinical 12-lead ECG tracings was selected covering both normal cases and common abnormalities. A team of 15 junior Cardiology Fellows and 15 Non-Cardiology Fellows interpreted the ECGs in 3 phases: without any diagnostic proposal, with a single diagnostic proposal (half of them intentionally incorrect), and with four diagnostic proposals (only one of them being correct) for each ECG. Self-rated confidence of each interpretation was collected. Availability of diagnostic proposals significantly increased the diagnostic accuracy (p<0.001). Nevertheless, in case of a single proposal (either correct or incorrect) the increase of accuracy was present in interpretations with correct diagnostic proposals, while the accuracy was substantially reduced with incorrect proposals. Confidence levels poorly correlated with interpretation scores (rho≈2, p<0.001). Logistic regression showed that an interpreter is most likely to be correct when the ECG offers a correct diagnostic proposal (OR=10.87) or multiple proposals (OR=4.43). Diagnostic proposals affect the diagnostic accuracy of ECG interpretations. The accuracy is significantly influenced especially when a single diagnostic proposal (either correct or incorrect) is provided. The study suggests that the presentation of multiple computerized diagnoses is likely to improve the diagnostic accuracy of interpreters. Copyright © 2017 Elsevier B.V. All rights reserved.
A machine learning approach to multi-level ECG signal quality classification.
Li, Qiao; Rajagopalan, Cadathur; Clifford, Gari D
2014-12-01
Current electrocardiogram (ECG) signal quality assessment studies have aimed to provide a two-level classification: clean or noisy. However, clinical usage demands more specific noise level classification for varying applications. This work outlines a five-level ECG signal quality classification algorithm. A total of 13 signal quality metrics were derived from segments of ECG waveforms, which were labeled by experts. A support vector machine (SVM) was trained to perform the classification and tested on a simulated dataset and was validated using data from the MIT-BIH arrhythmia database (MITDB). The simulated training and test datasets were created by selecting clean segments of the ECG in the 2011 PhysioNet/Computing in Cardiology Challenge database, and adding three types of real ECG noise at different signal-to-noise ratio (SNR) levels from the MIT-BIH Noise Stress Test Database (NSTDB). The MITDB was re-annotated for five levels of signal quality. Different combinations of the 13 metrics were trained and tested on the simulated datasets and the best combination that produced the highest classification accuracy was selected and validated on the MITDB. Performance was assessed using classification accuracy (Ac), and a single class overlap accuracy (OAc), which assumes that an individual type classified into an adjacent class is acceptable. An Ac of 80.26% and an OAc of 98.60% on the test set were obtained by selecting 10 metrics while 57.26% (Ac) and 94.23% (OAc) were the numbers for the unseen MITDB validation data without retraining. By performing the fivefold cross validation, an Ac of 88.07±0.32% and OAc of 99.34±0.07% were gained on the validation fold of MITDB. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Wireless Self-Acquistion of 12-Lead ECG via Android Smart Phone
NASA Technical Reports Server (NTRS)
Schlegel, Todd T.
2012-01-01
Researchers at NASA s Johnson Space Center and at Orbital Research, Inc. (a NASA SBIR grant recipient) have recently developed a dry-electrode harness that allows for self-acquisition of resting 12-lead ECGs by minimally trained laypersons. When used in conjunction with commercial wireless (e.g., Bluetooth(TM) or 802.11-enabled) 12-lead ECG devices and custom smart phone-based software, the collected 12-lead ECG data can also immediately be forwarded from any geographic location within cellular range to the user s physician(s) of choice. The system can also be used to immediately forward to central receiving stations 12-lead ECG data collected during space flight or during activities in any remote terrestrial location supported by an internet or cellular phone infrastructure. The main novel aspects of the system are first, the dry-electrode 12-lead ECG harness itself, and second, an accompanying Android(TM) smart phone-based wireless 12-lead ECG capability. The ECG harness nominally employs dry electrodes manufactured by Orbital Research, Inc, recently cleared through the Food and Drug Administration (FDA). However, other dry electrodes that are not yet FDA cleared, for example those recently developed by Nanosonic, Inc as part of another NASA SBIR grant, can also be used. The various advantageous features of the harness include: 1) laypersons can be quickly instructed on its correct use, remotely if necessary; 2) all tangled "leadwire spaghetti" is eliminated, as is the common clinical problem of "leadwire reversal"; 3) all adhesives and disposables are also eliminated, the harness being fully reusable; if multiple individuals intend to use use the same harness, then standard antimicrobial wipes can be employed to sterilize the dry electrodes (and harness surface if needed) between users; 5) padded cushions at the lateral sides of the torso function to press the left arm (LA) and right arm (RA) dry electrodes mounted on the cushions against sideward or downward-rested arms of the subject; 6) sufficient distal placement of the arm electrodes achieves good electrode abutment to the arms without the need for adhesives, straps, bands, bracelets, or gloves; 7) padding over the sternum avoids "tenting" in the V1 through V3 (and, when present, the V3R) electrode positions; 8) easy-to-don, one-piece design with an adjustable, front-side single point of connection and an adjustable shoulder strap; and 9) Lund or "modified Lund" placement of the dry electrodes, the results of which more effectively reproduce results from "standard" 12-lead ECG placements than do results from Mason-Likar placements. The main limitation of the harness is that "one size does not fit all", meaning that an appropriately sized harness (small, medium, large, etc) must be chosen on the basis of an individual's size. To facilitate the use of the harness with inexpensive, commodity-grade cell phones and tablet devices, 12-lead ECG software is also being developed to accompany the harness for wireless use with Android. For this part of the project, NASA has teamed with TopCoder, Inc and the Harvard-affiliated NASA Tournament Lab in sponsoring java-based software programming contests through TopCoder. While ECG signals from the harness can already be wirelessly received and thoroughly processed (locally or remotely) by commercial-grade conventional (as well as advanced) 12-lead ECG software running on Microsoft Windows(TM), the Android-based software, once completed, will "cast a wider net" by allowing for a greater percentage of cell phone owners to participate in inexpensive, store-and-forward recordings of 12-lead ECGs worldwide, including for example Android cell phone users in many remote, third-world locations. At the time of writing, the Android 12-lead ECG software platform consists of a basic but expanding graphical user interface and accompanying software that: 1) wirelessly receives the 12-lead ECG data stream from a Bluetooth-based, FDA-cleared 12-leaCG device attached to the harness; 2) locally stores the same data in binary format to the SD card on the Android cell phone; and 3) makes the data stream in available in real time, for now to TopCoder's java programming contestants.
ECG-triggered high-pitch CT for simultaneous assessment of the aorta and coronary arteries.
Hachulla, Anne-Lise; Ronot, Maxime; Noble, Stéphane; Becker, Christoph D; Montet, Xavier; Vallée, Jean-Paul
2016-01-01
To study the image quality of ECG-gated-computed tomography (CT) acquisition with a high-pitch CT imaging for the exploration of both the aorta and coronary arteries. Eighty-four patients underwent high-pitch ECG-gated aortic CT without β-blockers with iterative reconstruction algorithms. Contrast-to-noise ratio (CNR) between vessels and adjacent perivascular fat tissue were calculated on the aorta and the coronary arteries. Dose-length-products (DLP) were recorded. Two blinded readers graded image quality of the aorta and the coronary arteries on a 3-point scale. Coronary artery stenoses were compared with coronary angiograms in 24 patients. Kappa values were calculated. High-pitch acquisition resulted in a mean DLP of 234 ± 93 mGy cm(4.2 mSv) for an acquisition of the entire aorta, (mean 73 ± 16 bpm). CNR for ascending aorta was 10.6 ± 4 and CNR for coronary arteries was 9.85 ± 4.1. Image quality was excellent in 79/84 patients (94%), and excellent or moderate but diagnostic in 1087/1127 coronary artery segments (96%). 74 significant stenoses were observed, and 38/40 significant stenoses were confirmed by coronary angiography (K = 0.91, Sensitivity = 0.97, Specificity = 0.98). High-pitch ECG-gated aortic CT with iterative reconstructions allows an accurate exploration of both aorta and coronary arteries during the same acquisition, with limited dose deposition, despite the lack of β-blockers and relatively high heart rate. Radiologists need to be aware of the necessity to analyze and report coronary artery disease in aortic examination. Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
Laborda-Vidal, P; Pedro, B; Baker, M; Gelzer, A R; Dukes-McEwan, J; Maddox, T W
2016-12-01
Pulmonic stenosis (PS) is the most common congenital cardiac disease in dogs. Boxers and English bulldogs are among the most commonly affected breeds and also commonly associated with an aberrant coronary artery (CA). If an aberrant CA is suspected and balloon valvuloplasty indicated, an intra-operative angiography is recommended prior to the procedure. ECG-gated computed tomography (CT) can be used to screen for CA anomalies in a quick and minimally-invasive way (preventing side effects associated with selective catheter angiography) and allowing early planning of the procedure. The aim of this case series was to report CT findings associated with PS diagnosed by echocardiography. Our database was retrospectively searched for cases of dogs with PS diagnosed by echocardiography, where an ECG-gated CT was performed. A total of six cases were retrieved: all were diagnosed with severe PS. Four dogs had concurrent congenital defects: two dogs had a patent ductus arteriosus, one dog had a ventricular septal defect and an overriding aorta, one dog had an aberrant CA. Detailed CT findings of all cases were reported, including one case of a patent ductus arteriosus and an overriding aorta not identified by transthoracic echocardiography. In addition, an abnormal single left coronary ostium, with a pre-pulmonic right CA was described. In conclusion, despite echocardiography remaining the gold standard for diagnosis and assessment of PS, ECG-gated-CT angiography is a complementary diagnostic method that may provide additional relevant information, shorten surgery/anaesthesia time and reduce the amount of radiation to which the clinician is subjected. Copyright © 2016 Elsevier B.V. All rights reserved.
Matsutani, Hideyuki; Sano, Tomonari; Kondo, Takeshi; Fujimoto, Shinichiro; Sekine, Takako; Arai, Takehiro; Morita, Hitomi; Takase, Shinichi
2010-12-20
A high radiation dose associated with 64 multidetector-row computed tomography (64-MDCT) is a major concern for physicians and patients alike. A new 320 row area detector computed tomography (ADCT) can obtain a view of the entire heart with one rotation (0.35 s) without requiring the helical method. As such, ADCT is expected to reduce the radiation dose. We studied image quality and radiation dose of ADCT compared to that of 64-MDCT in patients with a low heart rate (HR≤60). Three hundred eighty-five consecutive patients underwent 64-MDCT and 379 patients, ADCT. Patients with an arrhythmia were excluded. Prospective ECG-gated helical scan with high HP (FlashScan) in 64 was used for MDCT and prospective ECG-gated conventional one beat scan, for 320-ADCT. Image quality was visually evaluated by an image quality score. Radiation dose was estimated by DLP (mGy・cm) for 64-MDCT and DLP.e (mGy・cm) for 320-ADCT. Radiation dose of 320-ADCT (208±48 mGy・cm) was significantly (P<0.0001) lower than that of 64-MDCT (484±112 mGy・cm), and image quality score of 320-ADCT (3.0±0.2) was significantly (P=0.0011) higher than that of 64-MDCT (2.9±0.4). Scan time of 320-ADCT (1.4±0.1 s) was also significantly (P<0.0001) shorter than that of 64-MDCT (6.8±0.6 s). 320-ADCT can achieve not only a reduction in radiation dose but also a superior image quality and shortening of scan time compared to 64-MDCT.
Real-time, high frequency QRS electrocardiograph
NASA Technical Reports Server (NTRS)
Schlegel, Todd T. (Inventor); DePalma, Jude L. (Inventor); Moradi, Saeed (Inventor)
2006-01-01
Real time cardiac electrical data are received from a patient, manipulated to determine various useful aspects of the ECG signal, and displayed in real time in a useful form on a computer screen or monitor. The monitor displays the high frequency data from the QRS complex in units of microvolts, juxtaposed with a display of conventional ECG data in units of millivolts or microvolts. The high frequency data are analyzed for their root mean square (RMS) voltage values and the discrete RMS values and related parameters are displayed in real time. The high frequency data from the QRS complex are analyzed with imbedded algorithms to determine the presence or absence of reduced amplitude zones, referred to herein as RAZs. RAZs are displayed as go, no-go signals on the computer monitor. The RMS and related values of the high frequency components are displayed as time varying signals, and the presence or absence of RAZs may be similarly displayed over time.
Rhythmic chaos: irregularities of computer ECG diagnosis.
Wang, Yi-Ting Laureen; Seow, Swee-Chong; Singh, Devinder; Poh, Kian-Keong; Chai, Ping
2017-09-01
Diagnostic errors can occur when physicians rely solely on computer electrocardiogram interpretation. Cardiologists often receive referrals for computer misdiagnoses of atrial fibrillation. Patients may have been inappropriately anticoagulated for pseudo atrial fibrillation. Anticoagulation carries significant risks, and such errors may carry a high cost. Have we become overreliant on machines and technology? In this article, we illustrate three such cases and briefly discuss how we can reduce these errors. Copyright: © Singapore Medical Association.
Zhang, Shelley HuaLei; Ho Tse, Zion Tsz; Dumoulin, Charles L.; Kwong, Raymond Y.; Stevenson, William G.; Watkins, Ronald; Ward, Jay; Wang, Wei; Schmidt, Ehud J.
2015-01-01
Purpose To restore 12-lead ECG signal fidelity inside MRI by removing magnetic-field gradient induced-voltages during high gradient-duty-cycle sequences. Theory and Methods A theoretical equation was derived, providing first- and second-order electrical fields induced at individual ECG electrode as a function of gradient fields. Experiments were performed at 3T on healthy volunteers, using a customized acquisition system which captured full amplitude and frequency response of ECGs, or a commercial recording system. The 19 equation coefficients were derived by linear regression of data from accelerated sequences, and used to compute induced-voltages in real-time during full-resolution sequences to remove ECG artifacts. Restored traces were evaluated relative to ones acquired without imaging. Results Measured induced-voltages were 0.7V peak-to-peak during balanced Steady-State Free Precession (bSSFP) with heart at the isocenter. Applying the equation during gradient echo sequencing, three-dimensional fast spin echo and multi-slice bSSFP imaging restored nonsaturated traces and second-order concomitant terms showed larger contributions in electrodes farther from the magnet isocenter. Equation coefficients are evaluated with high repeatability (ρ = 0.996) and are subject, sequence, and slice-orientation dependent. Conclusion Close agreement between theoretical and measured gradient-induced voltages allowed for real-time removal. Prospective estimation of sequence-periods where large induced-voltages occur may allow hardware removal of these signals. PMID:26101951
Singularity detection by wavelet approach: application to electrocardiogram signal
NASA Astrophysics Data System (ADS)
Jalil, Bushra; Beya, Ouadi; Fauvet, Eric; Laligant, Olivier
2010-01-01
In signal processing, the region of abrupt changes contains the most of the useful information about the nature of the signal. The region or the points where these changes occurred are often termed as singular point or singular region. The singularity is considered to be an important character of the signal, as it refers to the discontinuity and interruption present in the signal and the main purpose of the detection of such singular point is to identify the existence, location and size of those singularities. Electrocardiogram (ECG) signal is used to analyze the cardiovascular activity in the human body. However the presence of noise due to several reasons limits the doctor's decision and prevents accurate identification of different pathologies. In this work we attempt to analyze the ECG signal with energy based approach and some heuristic methods to segment and identify different signatures inside the signal. ECG signal has been initially denoised by empirical wavelet shrinkage approach based on Steins Unbiased Risk Estimate (SURE). At the second stage, the ECG signal has been analyzed by Mallat approach based on modulus maximas and Lipschitz exponent computation. The results from both approaches has been discussed and important aspects has been highlighted. In order to evaluate the algorithm, the analysis has been done on MIT-BIH Arrhythmia database; a set of ECG data records sampled at a rate of 360 Hz with 11 bit resolution over a 10mv range. The results have been examined and approved by medical doctors.
Normal computerized Q wave measurements in healthy young athletes.
Saini, Divakar; Grober, Aaron F; Hadley, David; Froelicher, Victor
Recent Expert consensus statements have sought to decrease false positive rates of electrocardiographic abnormalities requiring further evaluation when screening young athletes. These statements are largely based on traditional ECG patterns and have not considered computerized measurements. To define the normal limits for Q wave measurements from the digitally recorded ECGs of healthy young athletes. All athletes were categorized by sex and level of participation (high school, college, and professional), and underwent screening ECGs with routine pre-participation physicals, which were electronically captured and analyzed. Q wave amplitude, area and duration were recorded for athletes with Q wave amplitudes greater than 0.5mm at standard paper amplitude display (1mV/10mm). ANOVA analyses were performed to determine differences these parameters among all groups. A positive ECG was defined by our Stanford Computerized Criteria as exceeding the 99th percentile for Q wave area in 2 or more leads. Proportions testing was used to compare the Seattle Conference Q wave criteria with our data-driven criteria. 2073 athletes in total were screened. Significant differences in Q wave amplitude, duration and area were identified both by sex and level of participation. When applying our Stanford Computerized Criteria and the Seattle criteria to our cohort, two largely different groups of athletes are identified as having abnormal Q waves. Computer analysis of athletes' ECGs should be included in future studies that have greater numbers, more diversity and adequate end points. Copyright © 2017 Elsevier Inc. All rights reserved.
Real-Time Analytics for the Healthcare Industry: Arrhythmia Detection.
Agneeswaran, Vijay Srinivas; Mukherjee, Joydeb; Gupta, Ashutosh; Tonpay, Pranay; Tiwari, Jayati; Agarwal, Nitin
2013-09-01
It is time for the healthcare industry to move from the era of "analyzing our health history" to the age of "managing the future of our health." In this article, we illustrate the importance of real-time analytics across the healthcare industry by providing a generic mechanism to reengineer traditional analytics expressed in the R programming language into Storm-based real-time analytics code. This is a powerful abstraction, since most data scientists use R to write the analytics and are not clear on how to make the data work in real-time and on high-velocity data. Our paper focuses on the applications necessary to a healthcare analytics scenario, specifically focusing on the importance of electrocardiogram (ECG) monitoring. A physician can use our framework to compare ECG reports by categorization and consequently detect Arrhythmia. The framework can read the ECG signals and uses a machine learning-based categorizer that runs within a Storm environment to compare different ECG signals. The paper also presents some performance studies of the framework to illustrate the throughput and accuracy trade-off in real-time analytics.
Smart wireless sensor for physiological monitoring.
Tomasic, Ivan; Avbelj, Viktor; Trobec, Roman
2015-01-01
Presented is a wireless body sensor capable of measuring local potential differences on a body surface. By using on-sensor signal processing capabilities, and developed algorithms for off-line signal processing on a personal computing device, it is possible to record single channel ECG, heart rate, breathing rate, EMG, and when three sensors are applied, even the 12-lead ECG. The sensor is portable, unobtrusive, and suitable for both inpatient and outpatient monitoring. The paper presents the sensor's hardware and results of power consumption analysis. The sensor's capabilities of recording various physiological parameters are also presented and illustrated. The paper concludes with envisioned sensor's future developments and prospects.
Rejection of the maternal electrocardiogram in the electrohysterogram signal.
Leman, H; Marque, C
2000-08-01
The electrohysterogram (EHG) signal is mainly corrupted by the mother's electrocardiogram (ECG), which remains present despite analog filtering during acquisition. Wavelets are a powerful denoising tool and have already proved their efficiency on the EHG. In this paper, we propose a new method that employs the redundant wavelet packet transform. We first study wavelet packet coefficient histograms and propose an algorithm to automatically detect the histogram mode number. Using a new criterion, we compute a best basis adapted to the denoising. After EHG wavelet packet coefficient thresholding in the selected basis, the inverse transform is applied. The ECG seems to be very efficiently removed.
Asif, Irfan M; Drezner, Jonathan A
2012-01-01
Sudden cardiac death (SCD) is the leading cause of death in young athletes during exercise, and there is international agreement among major medical and sporting bodies that young athletes should undergo preparticipation cardiovascular screening. However, there is currently no universally accepted screening protocol, and substantial debate exists about what constitutes the ideal approach to preparticipation screening. The primary objective of preparticipation screening is the detection of intrinsic structural or electrical cardiovascular disorders that predispose an athlete to SCD. Considerable evidence exists suggesting that screening athletes with only a history and physical examination leaves most athletes with a serious underlying cardiovascular disease undetected and, thus, cannot adequately achieve the primary objective of screening. Preparticipating cardiovascular screening inclusive of an electrocardiogram (ECG) greatly enhances the ability to identify athletes at risk and is the only model shown to be cost-effective and may reduce the rate of SCD. The major obstacle to ECG screening in the United States is the lack of a physician workforce skilled in interpretation of an athlete's ECG. However, recent studies have demonstrated a capacity to distinguish physiologic ECG alterations in athletes from findings suggestive of underlying pathology that is both feasible and has a low false-positive rate. Efforts are underway to increase physician education in ECG interpretation. After 2 decades debating the proper screening strategy to identify athletes at risk, the weight of scientific evidence suggests that a screening program inclusive of ECG is the only strategy that merits promotion. Copyright © 2012 Elsevier Inc. All rights reserved.
Robust QRS peak detection by multimodal information fusion of ECG and blood pressure signals.
Ding, Quan; Bai, Yong; Erol, Yusuf Bugra; Salas-Boni, Rebeca; Zhang, Xiaorong; Hu, Xiao
2016-11-01
QRS peak detection is a challenging problem when ECG signal is corrupted. However, additional physiological signals may also provide information about the QRS position. In this study, we focus on a unique benchmark provided by PhysioNet/Computing in Cardiology Challenge 2014 and Physiological Measurement focus issue: robust detection of heart beats in multimodal data, which aimed to explore robust methods for QRS detection in multimodal physiological signals. A dataset of 200 training and 210 testing records are used, where the testing records are hidden for evaluating the performance only. An information fusion framework for robust QRS detection is proposed by leveraging existing ECG and ABP analysis tools and combining heart beats derived from different sources. Results show that our approach achieves an overall accuracy of 90.94% and 88.66% on the training and testing datasets, respectively. Furthermore, we observe expected performance at each step of the proposed approach, as an evidence of the effectiveness of our approach. Discussion on the limitations of our approach is also provided.
Autoadaptivity and optimization in distributed ECG interpretation.
Augustyniak, Piotr
2010-03-01
This paper addresses principal issues of the ECG interpretation adaptivity in a distributed surveillance network. In the age of pervasive access to wireless digital communication, distributed biosignal interpretation networks may not only optimally solve difficult medical cases, but also adapt the data acquisition, interpretation, and transmission to the variable patient's status and availability of technical resources. The background of such adaptivity is the innovative use of results from the automatic ECG analysis to the seamless remote modification of the interpreting software. Since the medical relevance of issued diagnostic data depends on the patient's status, the interpretation adaptivity implies the flexibility of report content and frequency. Proposed solutions are based on the research on human experts behavior, procedures reliability, and usage statistics. Despite the limited scale of our prototype client-server application, the tests yielded very promising results: the transmission channel occupation was reduced by 2.6 to 5.6 times comparing to the rigid reporting mode and the improvement of the remotely computed diagnostic outcome was achieved in case of over 80% of software adaptation attempts.
Envelopment filter and K-means for the detection of QRS waveforms in electrocardiogram.
Merino, Manuel; Gómez, Isabel María; Molina, Alberto J
2015-06-01
The electrocardiogram (ECG) is a well-established technique for determining the electrical activity of the heart and studying its diseases. One of the most common pieces of information that can be read from the ECG is the heart rate (HR) through the detection of its most prominent feature: the QRS complex. This paper describes an offline version and a real-time implementation of a new algorithm to determine QRS localization in the ECG signal based on its envelopment and K-means clustering algorithm. The envelopment is used to obtain a signal with only QRS complexes, deleting P, T, and U waves and baseline wander. Two moving average filters are applied to smooth data. The K-means algorithm classifies data into QRS and non-QRS. The technique is validated using 22 h of ECG data from five Physionet databases. These databases were arbitrarily selected to analyze different morphologies of QRS complexes: three stored data with cardiac pathologies, and two had data with normal heartbeats. The algorithm has a low computational load, with no decision thresholds. Furthermore, it does not require any additional parameter. Sensitivity, positive prediction and accuracy from results are over 99.7%. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.
A new method for QRS detection in ECG signals using QRS-preserving filtering techniques.
Sharma, Tanushree; Sharma, Kamalesh K
2018-03-28
Detection of QRS complexes in ECG signals is required for various purposes such as determination of heart rate, feature extraction and classification. The problem of automatic QRS detection in ECG signals is complicated by the presence of noise spectrally overlapping with the QRS frequency range. As a solution to this problem, we propose the use of least-squares-optimisation-based smoothing techniques that suppress the noise peaks in the ECG while preserving the QRS complexes. We also propose a novel nonlinear transformation technique that is applied after the smoothing operations, which equalises the QRS amplitudes without boosting the supressed noise peaks. After these preprocessing operations, the R-peaks can finally be detected with high accuracy. The proposed technique has a low computational load and, therefore, it can be used for real-time QRS detection in a wearable device such as a Holter monitor or for fast offline QRS detection. The offline and real-time versions of the proposed technique have been evaluated on the standard MIT-BIH database. The offline implementation is found to perform better than state-of-the-art techniques based on wavelet transforms, empirical mode decomposition, etc. and the real-time implementation also shows improved performance over existing real-time QRS detection techniques.
Pilia, Nicolas; Schulze, Walther H. W.; Dössel, Olaf
2017-01-01
The most important ECG marker for the diagnosis of ischemia or infarction is a change in the ST segment. Baseline wander is a typical artifact that corrupts the recorded ECG and can hinder the correct diagnosis of such diseases. For the purpose of finding the best suited filter for the removal of baseline wander, the ground truth about the ST change prior to the corrupting artifact and the subsequent filtering process is needed. In order to create the desired reference, we used a large simulation study that allowed us to represent the ischemic heart at a multiscale level from the cardiac myocyte to the surface ECG. We also created a realistic model of baseline wander to evaluate five filtering techniques commonly used in literature. In the simulation study, we included a total of 5.5 million signals coming from 765 electrophysiological setups. We found that the best performing method was the wavelet-based baseline cancellation. However, for medical applications, the Butterworth high-pass filter is the better choice because it is computationally cheap and almost as accurate. Even though all methods modify the ST segment up to some extent, they were all proved to be better than leaving baseline wander unfiltered. PMID:28373893
Sun, Yuwen; Cheng, Allen C
2012-07-01
Artificial neural networks (ANNs) are a promising machine learning technique in classifying non-linear electrocardiogram (ECG) signals and recognizing abnormal patterns suggesting risks of cardiovascular diseases (CVDs). In this paper, we propose a new reusable neuron architecture (RNA) enabling a performance-efficient and cost-effective silicon implementation for ANN. The RNA architecture consists of a single layer of physical RNA neurons, each of which is designed to use minimal hardware resource (e.g., a single 2-input multiplier-accumulator is used to compute the dot product of two vectors). By carefully applying the principal of time sharing, RNA can multiplexs this single layer of physical neurons to efficiently execute both feed-forward and back-propagation computations of an ANN while conserving the area and reducing the power dissipation of the silicon. A three-layer 51-30-12 ANN is implemented in RNA to perform the ECG classification for CVD detection. This RNA hardware also allows on-chip automatic training update. A quantitative design space exploration in area, power dissipation, and execution speed between RNA and three other implementations representative of different reusable hardware strategies is presented and discussed. Compared with an equivalent software implementation in C executed on an embedded microprocessor, the RNA ASIC achieves three orders of magnitude improvements in both the execution speed and the energy efficiency. Copyright © 2012 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Grajek, Magdalena; Krzyminiewski, Ryszard; Kalawski, Ryszard; Kulczak, Mariusz
2008-01-01
Many bioelectric signals have a complex internal structure that can be a rich source of information on the tissue or cell processes. The structure of such signals can be analysed in detail by applying digital methods of signal processing. Therefore, of substantial use in diagnosis of the coronary arterial disease is the method of digital enhancement of increasing signal resolution ECG (NURSE-ECG), permitting detection of temporary changes in the electric potentials in the cardiac muscle in the process of depolarisation. Thanks to the application of NURSE-ECG it has become possible to detect relatively small changes in the electric activity of particular fragments of the cardiac muscle undetectable by the standard ECG method, caused by ischemia, the effect of a drug or infarct. The aim of this study was to identify and analyse changes in the electric activity of the cardiac muscle as a result of the Coronary Artery Bypass Graft (CABG) operation. In this study the method of NURSE-ECG has been applied in order to identify and analyse changes in the electric activity of the cardiac muscle as a result of the CABG operation. In the study performed in cooperation of the Institute of Physics Adam Mickiewicz University and the Strus Hospital, Cardiac Surgery Ward, 37 patients with advanced coronary arterial disease were asked to participate. The patients were examined prior to the operation, on the day after the operation and two months after the operation and a year after the operation. The ECG recordings were subjected to a numerical procedure of resolution enhancement by a NURSE-ECG program to reveal the tentative changes in the electric potential of the cardiac muscle on its depolarisation. Results of the study have shown that the NURSE ECG method can be applied to monitor changes in the electric activity of the cardiac muscle occurring as a result of CABG operation. One the second day after the operation in the majority of patients (70%) a rapid decrease of the total cardiac muscle activity was observed. The NURSE ECG seems to be a promising supplementary method in medical diagnosis. In particular it can be applied for qualification of patients for CABG operation and for verification of the operation effects.
Cardiac arrhythmia beat classification using DOST and PSO tuned SVM.
Raj, Sandeep; Ray, Kailash Chandra; Shankar, Om
2016-11-01
The increase in the number of deaths due to cardiovascular diseases (CVDs) has gained significant attention from the study of electrocardiogram (ECG) signals. These ECG signals are studied by the experienced cardiologist for accurate and proper diagnosis, but it becomes difficult and time-consuming for long-term recordings. Various signal processing techniques are studied to analyze the ECG signal, but they bear limitations due to the non-stationary behavior of ECG signals. Hence, this study aims to improve the classification accuracy rate and provide an automated diagnostic solution for the detection of cardiac arrhythmias. The proposed methodology consists of four stages, i.e. filtering, R-peak detection, feature extraction and classification stages. In this study, Wavelet based approach is used to filter the raw ECG signal, whereas Pan-Tompkins algorithm is used for detecting the R-peak inside the ECG signal. In the feature extraction stage, discrete orthogonal Stockwell transform (DOST) approach is presented for an efficient time-frequency representation (i.e. morphological descriptors) of a time domain signal and retains the absolute phase information to distinguish the various non-stationary behavior ECG signals. Moreover, these morphological descriptors are further reduced in lower dimensional space by using principal component analysis and combined with the dynamic features (i.e based on RR-interval of the ECG signals) of the input signal. This combination of two different kinds of descriptors represents each feature set of an input signal that is utilized for classification into subsequent categories by employing PSO tuned support vector machines (SVM). The proposed methodology is validated on the baseline MIT-BIH arrhythmia database and evaluated under two assessment schemes, yielding an improved overall accuracy of 99.18% for sixteen classes in the category-based and 89.10% for five classes (mapped according to AAMI standard) in the patient-based assessment scheme respectively to the state-of-art diagnosis. The results reported are further compared to the existing methodologies in literature. The proposed feature representation of cardiac signals based on symmetrical features along with PSO based optimization technique for the SVM classifier reported an improved classification accuracy in both the assessment schemes evaluated on the benchmark MIT-BIH arrhythmia database and hence can be utilized for automated computer-aided diagnosis of cardiac arrhythmia beats. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Individual identification via electrocardiogram analysis.
Fratini, Antonio; Sansone, Mario; Bifulco, Paolo; Cesarelli, Mario
2015-08-14
During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research. We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents. 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %. Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations.
Noninvasive fetal QRS detection using an echo state network and dynamic programming.
Lukoševičius, Mantas; Marozas, Vaidotas
2014-08-01
We address a classical fetal QRS detection problem from abdominal ECG recordings with a data-driven statistical machine learning approach. Our goal is to have a powerful, yet conceptually clean, solution. There are two novel key components at the heart of our approach: an echo state recurrent neural network that is trained to indicate fetal QRS complexes, and several increasingly sophisticated versions of statistics-based dynamic programming algorithms, which are derived from and rooted in probability theory. We also employ a standard technique for preprocessing and removing maternal ECG complexes from the signals, but do not take this as the main focus of this work. The proposed approach is quite generic and can be extended to other types of signals and annotations. Open-source code is provided.
Lin, Lu; Wang, Yi-Ning; Kong, Ling-Yan; Jin, Zheng-Yu; Lu, Guang-Ming; Zhang, Zhao-Qi; Cao, Jian; Li, Shuo; Song, Lan; Wang, Zhi-Wei; Zhou, Kang; Wang, Ming
2013-01-01
Objective To evaluate the image quality (IQ) and radiation dose of 128-slice dual-source computed tomography (DSCT) coronary angiography using prospectively electrocardiogram (ECG)-triggered sequential scan mode compared with ECG-gated spiral scan mode in a population with atrial fibrillation. Methods Thirty-two patients with suspected coronary artery disease and permanent atrial fibrillation referred for a second-generation 128-slice DSCT coronary angiography were included in the prospective study. Of them, 17 patients (sequential group) were randomly selected to use a prospectively ECG-triggered sequential scan, while the other 15 patients (spiral group) used a retrospectively ECG-gated spiral scan. The IQ was assessed by two readers independently, using a four-point grading scale from excel-lent (grade 1) to non-assessable (grade 4), based on the American Heart Association 15-segment model. IQ of each segment and effective dose of each patient were compared between the two groups. Results The mean heart rate (HR) of the sequential group was 96±27 beats per minute (bpm) with a variation range of 73±25 bpm, while the mean HR of the spiral group was 86±22 bpm with a variationrange of 65±24 bpm. Both of the mean HR (t=1.91, P=0.243) and HR variation range (t=0.950, P=0.350) had no significant difference between the two groups. In per-segment analysis, IQ of the sequential group vs. spiral group was rated as excellent (grade 1) in 190/244 (78%) vs. 177/217 (82%) by reader1 and 197/245 (80%) vs. 174/214 (81%) by reader2, as non-assessable (grade 4) in 4/244 (2%) vs. 2/217 (1%) by reader1 and 6/245 (2%) vs. 4/214 (2%) by reader2. Overall averaged IQ per-patient in the sequential and spiral group showed equally good (1.27±0.19 vs. 1.25±0.22, Z=-0.834, P=0.404). The effective radiation dose of the sequential group reduced significantly compared with the spiral group (4.88±1.77 mSv vs. 10.20±3.64 mSv; t=-5.372, P=0.000). Conclusion Compared with retrospectively ECG-gated spiral scan, prospectively ECG-triggered sequential DSCT coronary angiography provides similarly diagnostically valuable images in patients with atrial fibrillation and significantly reduces radiation dose.
Educational Software Applied in Teaching Electrocardiogram: A Systematic Review
Chaves, Rafael O.; de Souza, Érica F.; Seruffo, Marcos C. R.; Francês, Carlos R. L.
2018-01-01
Background The electrocardiogram (ECG) is the most used diagnostic tool in medicine; in this sense, it is essential that medical undergraduates learn how to interpret it correctly while they are still on training. Naturally, they go through classic learning (e.g., lectures and speeches). However, they are not often efficiently trained in analyzing ECG results. In this regard, methodologies such as other educational support tools in medical practice, such as educational software, should be considered a valuable approach for medical training purposes. Methods We performed a literature review in six electronic databases, considering studies published before April 2017. The resulting set comprises 2,467 studies. From this collection, 12 studies have been selected, initially, whereby we carried out a snowballing process to identify other relevant studies through the reference lists of these studies, resulting in five relevant studies, making up a total of 17 articles that passed all stages and criteria. Results The results show that 52.9% of software types were tutorial and 58.8% were designed to be run locally on a computer. The subjects were discussed together with a greater focus on the teaching of electrophysiology and/or cardiac physiology, identifying patterns of ECG and/or arrhythmias. Conclusions We found positive results with the introduction of educational software for ECG teaching. However, there is a clear need for using higher quality research methodologies and the inclusion of appropriate controls, in order to obtain more precise conclusions about how beneficial the inclusion of such tools can be for the practices of ECG interpretation. PMID:29736398
Implementation of a WAP-based telemedicine system for patient monitoring.
Hung, Kevin; Zhang, Yuan-Ting
2003-06-01
Many parties have already demonstrated telemedicine applications that use cellular phones and the Internet. A current trend in telecommunication is the convergence of wireless communication and computer network technologies, and the emergence of wireless application protocol (WAP) devices is an example. Since WAP will also be a common feature found in future mobile communication devices, it is worthwhile to investigate its use in telemedicine. This paper describes the implementation and experiences with a WAP-based telemedicine system for patient-monitoring that has been developed in our laboratory. It utilizes WAP devices as mobile access terminals for general inquiry and patient-monitoring services. Authorized users can browse the patients' general data, monitored blood pressure (BP), and electrocardiogram (ECG) on WAP devices in store-and-forward mode. The applications, written in wireless markup language (WML), WMLScript, and Perl, resided in a content server. A MySQL relational database system was set up to store the BP readings, ECG data, patient records, clinic and hospital information, and doctors' appointments with patients. A wireless ECG subsystem was built for recording ambulatory ECG in an indoor environment and for storing ECG data into the database. For testing, a WAP phone compliant with WAP 1.1 was used at GSM 1800 MHz by circuit-switched data (CSD) to connect to the content server through a WAP gateway, which was provided by a mobile phone service provider in Hong Kong. Data were successfully retrieved from the database and displayed on the WAP phone. The system shows how WAP can be feasible in remote patient-monitoring and patient data retrieval.
Cost-benefit of the telecardiology service in the state of Minas Gerais: Minas Telecardio Project.
Andrade, Mônica Viegas; Maia, Ana Carolina; Cardoso, Clareci Silva; Alkmim, Maria Beatriz; Ribeiro, Antônio Luiz Pinho
2011-10-01
Telecardiology is a tool that can aid in cardiovascular care, mainly in towns located in remote areas. However, economic assessments on this subject are scarce and have yielded controversial results. To evaluate the cost-benefit of implementing a Telecardiology service in remote, small towns in the state of Minas Gerais, Brazil. The study used the database from the Minas Telecardio (MTC) Project, developed from June 2006 to November 2008, in 82 towns in the countryside of the state. Each municipality received a microcomputer with a digital electrocardiograph, with the possibility of transmitting ECG tracings and communicating with the on-duty cardiologist at the University hospital. The cost-benefit analysis was carried out by comparing the cost of performing an ECG in the project versus the cost of performing it by patient referral to another city. The average cost of an ECG in the MTC project was R$ 28.92, decomposed into R$ 8.08 for the cost of implementation and R$ 20.84 for maintenance. The cost simulation of the ECG with referral ranged from R$ 30.91 to R$ 54.58, with the cost-benefit ratio being always favorable to the MTC program, regardless of the type of calculation used for referral distance. The simulations considered the financial sponsor's and society's points-of-view. The sensitivity analysis with variation of calibration parameters confirmed these results. The implementation of a Telecardiology system as support to primary care in small Brazilian towns is feasible and economically beneficial, and can be used as a regular program within the Brazilian public health system.
Optimisation algorithms for ECG data compression.
Haugland, D; Heber, J G; Husøy, J H
1997-07-01
The use of exact optimisation algorithms for compressing digital electrocardiograms (ECGs) is demonstrated. As opposed to traditional time-domain methods, which use heuristics to select a small subset of representative signal samples, the problem of selecting the subset is formulated in rigorous mathematical terms. This approach makes it possible to derive algorithms guaranteeing the smallest possible reconstruction error when a bounded selection of signal samples is interpolated. The proposed model resembles well-known network models and is solved by a cubic dynamic programming algorithm. When applied to standard test problems, the algorithm produces a compressed representation for which the distortion is about one-half of that obtained by traditional time-domain compression techniques at reasonable compression ratios. This illustrates that, in terms of the accuracy of decoded signals, existing time-domain heuristics for ECG compression may be far from what is theoretically achievable. The paper is an attempt to bridge this gap.
Automated acquisition system for routine, noninvasive monitoring of physiological data.
Ogawa, M; Tamura, T; Togawa, T
1998-01-01
A fully automated, noninvasive data-acquisition system was developed to permit long-term measurement of physiological functions at home, without disturbing subjects' normal routines. The system consists of unconstrained monitors built into furnishings and structures in a home environment. An electrocardiographic (ECG) monitor in the bathtub measures heart function during bathing, a temperature monitor in the bed measures body temperature, and a weight monitor built into the toilet serves as a scale to record weight. All three monitors are connected to one computer and function with data-acquisition programs and a data format rule. The unconstrained physiological parameter monitors and fully automated measurement procedures collect data noninvasively without the subject's awareness. The system was tested for 1 week by a healthy male subject, aged 28, in laboratory-based facilities.
Arica, Sami; Firat Ince, N; Bozkurt, Abdi; Tewfik, Ahmed H; Birand, Ahmet
2011-07-01
Pharmacological measurement of baroreflex sensitivity (BRS) is widely accepted and used in clinical practice. Following the introduction of pharmacologically induced BRS (p-BRS), alternative assessment methods eliminating the use of drugs were in the center of interest of the cardiovascular research community. In this study we investigated whether p-BRS using phenylephrine injection can be predicted from non-pharmacological time and frequency domain indices computed from electrocardiogram (ECG) and blood pressure (BP) data acquired during deep breathing. In this scheme, ECG and BP data were recorded from 16 subjects in a two-phase experiment. In the first phase the subjects performed irregular deep breaths and in the second phase the subjects received phenylephrine injection. From the first phase of the experiment, a large pool of predictors describing the local characteristic of beat-to-beat interval tachogram (RR) and systolic blood pressure (SBP) were extracted in time and frequency domains. A subset of these indices was selected using twelve subjects with an exhaustive search fused with a leave one subject out cross validation procedure. The selected indices were used to predict the p-BRS on the remaining four test subjects. A multivariate regression was used in all prediction steps. The algorithm achieved best prediction accuracy with only two features extracted from the deep breathing data, one from the frequency and the other from the time domain. The normalized L2-norm error was computed as 22.9% and the correlation coefficient was 0.97 (p=0.03). These results suggest that the p-BRS can be estimated from non-pharmacological indices computed from ECG and invasive BP data related to deep breathing. Copyright © 2011 Elsevier Ltd. All rights reserved.
Alday, Erick A Perez; Colman, Michael A; Langley, Philip; Zhang, Henggui
2017-03-01
Atrial tachy-arrhytmias, such as atrial fibrillation (AF), are characterised by irregular electrical activity in the atria, generally associated with erratic excitation underlain by re-entrant scroll waves, fibrillatory conduction of multiple wavelets or rapid focal activity. Epidemiological studies have shown an increase in AF prevalence in the developed world associated with an ageing society, highlighting the need for effective treatment options. Catheter ablation therapy, commonly used in the treatment of AF, requires spatial information on atrial electrical excitation. The standard 12-lead electrocardiogram (ECG) provides a method for non-invasive identification of the presence of arrhythmia, due to irregularity in the ECG signal associated with atrial activation compared to sinus rhythm, but has limitations in providing specific spatial information. There is therefore a pressing need to develop novel methods to identify and locate the origin of arrhythmic excitation. Invasive methods provide direct information on atrial activity, but may induce clinical complications. Non-invasive methods avoid such complications, but their development presents a greater challenge due to the non-direct nature of monitoring. Algorithms based on the ECG signals in multiple leads (e.g. a 64-lead vest) may provide a viable approach. In this study, we used a biophysically detailed model of the human atria and torso to investigate the correlation between the morphology of the ECG signals from a 64-lead vest and the location of the origin of rapid atrial excitation arising from rapid focal activity and/or re-entrant scroll waves. A focus-location algorithm was then constructed from this correlation. The algorithm had success rates of 93% and 76% for correctly identifying the origin of focal and re-entrant excitation with a spatial resolution of 40 mm, respectively. The general approach allows its application to any multi-lead ECG system. This represents a significant extension to our previously developed algorithms to predict the AF origins in association with focal activities.
2012-01-01
Background The compressed curriculum in modern knowledge-intensive medicine demands useful tools to achieve approved learning aims in a limited space of time. Web-based learning can be used in different ways to enhance learning. Little is however known regarding its optimal utilisation. Our aim was to investigate if the individual learning styles of medical students influence the choice to use a web-based ECG learning programme in a blended learning setting. Methods The programme, with three types of modules (learning content, self-assessment questions and interactive ECG interpretation training), was offered on a voluntary basis during a face to face ECG learning course for undergraduate medical students. The Index of Learning Styles (ILS) and a general questionnaire including questions about computer and Internet usage, preferred future speciality and prior experience of E-learning were used to explore different factors related to the choice of using the programme or not. Results 93 (76%) out of 123 students answered the ILS instrument and 91 the general questionnaire. 55 students (59%) were defined as users of the web-based ECG-interpretation programme. Cronbach's alpha was analysed with coefficients above 0.7 in all of the four dimensions of ILS. There were no significant differences with regard to learning styles, as assessed by ILS, between the user and non-user groups; Active/Reflective; Visual/Verbal; Sensing/Intuitive; and Sequential/Global (p = 0.56-0.96). Neither did gender, prior experience of E-learning or preference for future speciality differ between groups. Conclusion Among medical students, neither learning styles according to ILS, nor a number of other characteristics seem to influence the choice to use a web-based ECG programme. This finding was consistent also when the usage of the different modules in the programme were considered. Thus, the findings suggest that web-based learning may attract a broad variety of medical students. PMID:22248183
Nilsson, Mikael; Östergren, Jan; Fors, Uno; Rickenlund, Anette; Jorfeldt, Lennart; Caidahl, Kenneth; Bolinder, Gunilla
2012-01-16
The compressed curriculum in modern knowledge-intensive medicine demands useful tools to achieve approved learning aims in a limited space of time. Web-based learning can be used in different ways to enhance learning. Little is however known regarding its optimal utilisation. Our aim was to investigate if the individual learning styles of medical students influence the choice to use a web-based ECG learning programme in a blended learning setting. The programme, with three types of modules (learning content, self-assessment questions and interactive ECG interpretation training), was offered on a voluntary basis during a face to face ECG learning course for undergraduate medical students. The Index of Learning Styles (ILS) and a general questionnaire including questions about computer and Internet usage, preferred future speciality and prior experience of E-learning were used to explore different factors related to the choice of using the programme or not. 93 (76%) out of 123 students answered the ILS instrument and 91 the general questionnaire. 55 students (59%) were defined as users of the web-based ECG-interpretation programme. Cronbach's alpha was analysed with coefficients above 0.7 in all of the four dimensions of ILS. There were no significant differences with regard to learning styles, as assessed by ILS, between the user and non-user groups; Active/Reflective; Visual/Verbal; Sensing/Intuitive; and Sequential/Global (p = 0.56-0.96). Neither did gender, prior experience of E-learning or preference for future speciality differ between groups. Among medical students, neither learning styles according to ILS, nor a number of other characteristics seem to influence the choice to use a web-based ECG programme. This finding was consistent also when the usage of the different modules in the programme were considered. Thus, the findings suggest that web-based learning may attract a broad variety of medical students.
Spatial-temporal filter effect in a computer model study of ventricular fibrillation.
Nowak, Claudia N; Fischer, Gerald; Wieser, Leonhard; Tilg, Bernhard; Neurauter, Andreas; Strohmenger, Hans U
2008-08-01
Prediction of countershock success from ventricular fibrillation (VF) ECG is a major challenge in critical care medicine. Recent findings indicate that stable, high frequency mother rotors are one possible mechanism maintaining VF. A computer model study was performed to investigate how epicardiac sources are reflected in the ECG. In the cardiac tissues of two computer models - a model with cubic geometry and a simplified torso model with a left ventricle - a mother rotor was induced by increasing the potassium rectifier current. On the epicardium, the dominant frequency (DF) map revealed a constant DF of 23 Hz (cubic model) and 24.4 Hz (torso model) in the region of the mother rotor, respectively. A sharp drop of frequency (3-18 Hz in the cubic model and 12.4-18 Hz in the torso model) occurred in the surrounding epicardial tissue of chaotic fibrillatory conduction. While no organized pattern was observable on the body surface of the cubic model, the mother rotor frequency can be identified in the anterior surface of the torso model because of the chosen position of the mother rotor in the ventricle (shortest distance to the body surface). Nevertheless, the DFs were damped on the body surfaces of both models (4.6-8.5 Hz in the cubic model and 14.4-16.4 Hz in the torso model). Thus, it was shown in this computer model study that wave propagation transforms the spatial low pass filtering of the thorax into a temporal low pass. In contrast to the resistive-capacitive low pass filter formed by the tissue, this spatial-temporal low pass filter becomes effective at low frequencies (tens of Hertz). This effect damps the high frequency components arising from the heart and it hampers a direct observation of rapid, organized sources of VF in the ECGs, when in an emergency case an artifact-free recording is not possible.
NASA Technical Reports Server (NTRS)
Ocasio, W. C.; Rigney, D. R.; Clark, K. P.; Mark, R. G.; Goldberger, A. L. (Principal Investigator)
1993-01-01
We describe the theory and computer implementation of a newly-derived mathematical model for analyzing the shape of blood pressure waveforms. Input to the program consists of an ECG signal, plus a single continuous channel of peripheral blood pressure, which is often obtained invasively from an indwelling catheter during intensive-care monitoring or non-invasively from a tonometer. Output from the program includes a set of parameter estimates, made for every heart beat. Parameters of the model can be interpreted in terms of the capacitance of large arteries, the capacitance of peripheral arteries, the inertance of blood flow, the peripheral resistance, and arterial pressure due to basal vascular tone. Aortic flow due to contraction of the left ventricle is represented by a forcing function in the form of a descending ramp, the area under which represents the stroke volume. Differential equations describing the model are solved by the method of Laplace transforms, permitting rapid parameter estimation by the Levenberg-Marquardt algorithm. Parameter estimates and their confidence intervals are given in six examples, which are chosen to represent a variety of pressure waveforms that are observed during intensive-care monitoring. The examples demonstrate that some of the parameters may fluctuate markedly from beat to beat. Our program will find application in projects that are intended to correlate the details of the blood pressure waveform with other physiological variables, pathological conditions, and the effects of interventions.
Implementation of Virtualization Oriented Architecture: A Healthcare Industry Case Study
NASA Astrophysics Data System (ADS)
Rao, G. Subrahmanya Vrk; Parthasarathi, Jinka; Karthik, Sundararaman; Rao, Gvn Appa; Ganesan, Suresh
This paper presents a Virtualization Oriented Architecture (VOA) and an implementation of VOA for Hridaya - a Telemedicine initiative. Hadoop Compute cloud was established at our labs and jobs which require a massive computing capability such as ECG signal analysis were submitted and the study is presented in this current paper. VOA takes advantage of inexpensive community PCs and provides added advantages such as Fault Tolerance, Scalability, Performance, High Availability.
Tomlinson, David R; Bashir, Yaver; Betts, Timothy R; Rajappan, Kim
2009-05-01
Patients with left ventricular systolic dysfunction and electrocardiographic QRS duration (QRSd) >or=120 ms may obtain symptomatic and prognostic benefits from cardiac resynchronization therapy (CRT). However, clinical trials do not describe the methods used to measure QRSd. We investigated the effect of electrocardiogram (ECG) display format and paper speed on the accuracy of manual QRSd assessment and concordance of manual QRSd with computer-calculated mean and maximal QRSd. Six cardiologists undertook QRSd measurements on ECGs, with computer-calculated mean QRSd close to 120 ms. Display formats were 12-lead, 6-limb, and 6-precordial leads, each at 25 and 50 mm/s. When the computer-calculated mean was used to define QRSd, manual assessment demonstrated 97 and 83% concordance at categorizing QRSd as < and >or=120 ms, respectively. Using the computer-calculated maximal QRSd, manual assessment demonstrated 83% concordance when QRSd was <120 ms and 19% concordance when QRSd was >or=120 ms. The six-precordial lead format demonstrated significantly less intra and inter-observer variabilities than the 12-lead, but this did not improve concordance rates. Manual QRSd assessments demonstrate significant variability, and concordance with computer-calculated measurement depends on whether QRSd is defined as the mean or maximal value. Consensus is required both on the most appropriate definition of QRSd and its measurement.
NASA Technical Reports Server (NTRS)
1972-01-01
Electrocardiographic and vectorcardiographic bioinstrumentation work centered on the development of a new electrode system harness for Project Skylab. Evaluation of several silver electrode configurations proved superior impedance voltage performance for silver/silver chloride electrodes mounted flush by using a paste adhesive. A portable ECG processor has been designed and a breadboard unit has been built to sample ECG input data at a rate of 500 samples per second for arrhythmia detection. A small real time display driver program has been developed for statistical analysis on selected QPS features. Engineering work on a sleep monitoring cap assembly continued.
Kubios HRV--heart rate variability analysis software.
Tarvainen, Mika P; Niskanen, Juha-Pekka; Lipponen, Jukka A; Ranta-Aho, Perttu O; Karjalainen, Pasi A
2014-01-01
Kubios HRV is an advanced and easy to use software for heart rate variability (HRV) analysis. The software supports several input data formats for electrocardiogram (ECG) data and beat-to-beat RR interval data. It includes an adaptive QRS detection algorithm and tools for artifact correction, trend removal and analysis sample selection. The software computes all the commonly used time-domain and frequency-domain HRV parameters and several nonlinear parameters. There are several adjustable analysis settings through which the analysis methods can be optimized for different data. The ECG derived respiratory frequency is also computed, which is important for reliable interpretation of the analysis results. The analysis results can be saved as an ASCII text file (easy to import into MS Excel or SPSS), Matlab MAT-file, or as a PDF report. The software is easy to use through its compact graphical user interface. The software is available free of charge for Windows and Linux operating systems at http://kubios.uef.fi. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Real-time, high frequency QRS electrocardiograph with reduced amplitude zone detection
NASA Technical Reports Server (NTRS)
Schlegel, Todd T. (Inventor); DePalma, Jude L. (Inventor); Moradi, Saeed (Inventor)
2009-01-01
Real time cardiac electrical data are received from a patient, manipulated to determine various useful aspects of the ECG signal, and displayed in real time in a useful form on a computer screen or monitor. The monitor displays the high frequency data from the QRS complex in units of microvolts, juxtaposed with a display of conventional ECG data in units of millivolts or microvolts. The high frequency data are analyzed for their root mean square (RMS) voltage values and the discrete RMS values and related parameters are displayed in real time. The high frequency data from the QRS complex are analyzed with imbedded algorithms to determine the presence or absence of reduced amplitude zones, referred to herein as ''RAZs''. RAZs are displayed as ''go, no-go'' signals on the computer monitor. The RMS and related values of the high frequency components are displayed as time varying signals, and the presence or absence of RAZs may be similarly displayed over time.
Computer-assisted education system for arrhythmia (CAESAR).
Fukushima, M; Inoue, M; Fukunami, M; Ishikawa, K; Inada, H; Abe, H
1984-08-01
A computer-assisted education system for arrhythmia (CAESAR) was developed for students to acquire the ability to logically diagnose complicated arrhythmias. This system has a logical simulator of cardiac rhythm using a mathematical model of the impulse formation and conduction system of the heart. A simulated arrhythmia (ECG pattern) is given on a graphic display unit with simulated series of the action potential of five pacemaker centers and the "ladder diagram" of impulse formation and conduction, which show the mechanism of that arrhythmia. For the purpose of the evaluation of this system, 13 medical students were given two types of tests concerning arrhythmias before and after 2-hr learning with this system. The scores they obtained after learning increased significantly from 73.3 +/- 11.9 to 93.2 +/- 3.0 (P less than 0.001) in one test and from 47.2 +/- 17.9 to 64.9 +/- 19.6 (P less than 0.001) in another one. These results proved that this CAI system is useful and effective for training ECG interpretation of arrhythmias.
Tan, Sock Keow; Yeong, Chai Hong; Ng, Kwan Hoong; Abdul Aziz, Yang Faridah; Sun, Zhonghua
2016-01-01
This study aimed to measure the absorbed doses in selected organs for prospectively ECG-triggered coronary computed tomography angiography (CCTA) using five different generations CT scanners in a female adult anthropomorphic phantom and to estimate the effective dose (HE). Prospectively ECG-triggered CCTA was performed using five commercially available CT scanners: 64-detector-row single source CT (SSCT), 2 × 32-detector-row-dual source CT (DSCT), 2 × 64-detector-row DSCT and 320-detector-row SSCT scanners. Absorbed doses were measured in 34 organs using pre-calibrated optically stimulated luminescence dosimeters (OSLDs) placed inside a standard female adult anthropomorphic phantom. HE was calculated from the measured organ doses and compared to the HE derived from the air kerma-length product (PKL) using the conversion coefficient of 0.014 mSv∙mGy-1∙cm-1 for the chest region. Both breasts and lungs received the highest radiation dose during CCTA examination. The highest HE was received from 2 × 32-detector-row DSCT scanner (6.06 ± 0.72 mSv), followed by 64-detector-row SSCT (5.60 ± 0.68 and 5.02 ± 0.73 mSv), 2 × 64-detector-row DSCT (1.88 ± 0.25 mSv) and 320-detector-row SSCT (1.34 ± 0.48 mSv) scanners. HE calculated from the measured organ doses were about 38 to 53% higher than the HE derived from the PKL-to-HE conversion factor. The radiation doses received from a prospectively ECG-triggered CCTA are relatively small and are depending on the scanner technology and imaging protocols. HE as low as 1.34 and 1.88 mSv can be achieved in prospectively ECG-triggered CCTA using 320-detector-row SSCT and 2 × 64-detector-row DSCT scanners.
Tan, Sock Keow; Yeong, Chai Hong; Ng, Kwan Hoong; Abdul Aziz, Yang Faridah; Sun, Zhonghua
2016-01-01
Objectives This study aimed to measure the absorbed doses in selected organs for prospectively ECG-triggered coronary computed tomography angiography (CCTA) using five different generations CT scanners in a female adult anthropomorphic phantom and to estimate the effective dose (HE). Materials and Methods Prospectively ECG-triggered CCTA was performed using five commercially available CT scanners: 64-detector-row single source CT (SSCT), 2 × 32-detector-row-dual source CT (DSCT), 2 × 64-detector-row DSCT and 320-detector-row SSCT scanners. Absorbed doses were measured in 34 organs using pre-calibrated optically stimulated luminescence dosimeters (OSLDs) placed inside a standard female adult anthropomorphic phantom. HE was calculated from the measured organ doses and compared to the HE derived from the air kerma-length product (PKL) using the conversion coefficient of 0.014 mSv∙mGy-1∙cm-1 for the chest region. Results Both breasts and lungs received the highest radiation dose during CCTA examination. The highest HE was received from 2 × 32-detector-row DSCT scanner (6.06 ± 0.72 mSv), followed by 64-detector-row SSCT (5.60 ± 0.68 and 5.02 ± 0.73 mSv), 2 × 64-detector-row DSCT (1.88 ± 0.25 mSv) and 320-detector-row SSCT (1.34 ± 0.48 mSv) scanners. HE calculated from the measured organ doses were about 38 to 53% higher than the HE derived from the PKL-to-HE conversion factor. Conclusion The radiation doses received from a prospectively ECG-triggered CCTA are relatively small and are depending on the scanner technology and imaging protocols. HE as low as 1.34 and 1.88 mSv can be achieved in prospectively ECG-triggered CCTA using 320-detector-row SSCT and 2 × 64-detector-row DSCT scanners. PMID:27552224
Inan, O T; Kovacs, G T A
2010-04-01
A novel two-electrode biosignal amplifier circuit is demonstrated by using a composite transimpedance amplifier input stage with active current feedback. Micropower, low gain-bandwidth product operational amplifiers can be used, leading to the lowest reported overall power consumption in the literature for a design implemented with off-the-shelf commercial integrated circuits (11 μW). Active current feedback forces the common-mode input voltage to stay within the supply rails, reducing baseline drift and amplifier saturation problems that can be present in two-electrode systems. The bandwidth of the amplifier extends from 0.05-200 Hz and the midband voltage gain (assuming an electrode-to-skin resistance of 100 kΩ) is 48 dB. The measured output noise level is 1.2 mV pp, corresponding to a voltage signal-to-noise ratio approaching 50 dB for a typical electrocardiogram (ECG) level input of 1 mVpp. Recordings were taken from a subject by using the proposed two-electrode circuit and, simultaneously, a three-electrode standard ECG circuit. The residual of the normalized ensemble averages for both measurements was computed, and the power of this residual was 0.54% of the power of the standard ECG measurement output. While this paper primarily focuses on ECG applications, the circuit can also be used for amplifying other biosignals, such as the electroencephalogram.
Automatic QRS complex detection using two-level convolutional neural network.
Xiang, Yande; Lin, Zhitao; Meng, Jianyi
2018-01-29
The QRS complex is the most noticeable feature in the electrocardiogram (ECG) signal, therefore, its detection is critical for ECG signal analysis. The existing detection methods largely depend on hand-crafted manual features and parameters, which may introduce significant computational complexity, especially in the transform domains. In addition, fixed features and parameters are not suitable for detecting various kinds of QRS complexes under different circumstances. In this study, based on 1-D convolutional neural network (CNN), an accurate method for QRS complex detection is proposed. The CNN consists of object-level and part-level CNNs for extracting different grained ECG morphological features automatically. All the extracted morphological features are used by multi-layer perceptron (MLP) for QRS complex detection. Additionally, a simple ECG signal preprocessing technique which only contains difference operation in temporal domain is adopted. Based on the MIT-BIH arrhythmia (MIT-BIH-AR) database, the proposed detection method achieves overall sensitivity Sen = 99.77%, positive predictivity rate PPR = 99.91%, and detection error rate DER = 0.32%. In addition, the performance variation is performed according to different signal-to-noise ratio (SNR) values. An automatic QRS detection method using two-level 1-D CNN and simple signal preprocessing technique is proposed for QRS complex detection. Compared with the state-of-the-art QRS complex detection approaches, experimental results show that the proposed method acquires comparable accuracy.
Unsupervised heart-rate estimation in wearables with Liquid states and a probabilistic readout.
Das, Anup; Pradhapan, Paruthi; Groenendaal, Willemijn; Adiraju, Prathyusha; Rajan, Raj Thilak; Catthoor, Francky; Schaafsma, Siebren; Krichmar, Jeffrey L; Dutt, Nikil; Van Hoof, Chris
2018-03-01
Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine learning technique to estimate heart-rate from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach lies in (1) encoding spatio-temporal properties of ECG signals directly into spike train and using this to excite recurrently connected spiking neurons in a Liquid State Machine computation model; (2) a novel learning algorithm; and (3) an intelligently designed unsupervised readout based on Fuzzy c-Means clustering of spike responses from a subset of neurons (Liquid states), selected using particle swarm optimization. Our approach differs from existing works by learning directly from ECG signals (allowing personalization), without requiring costly data annotations. Additionally, our approach can be easily implemented on state-of-the-art spiking-based neuromorphic systems, offering high accuracy, yet significantly low energy footprint, leading to an extended battery-life of wearable devices. We validated our approach with CARLsim, a GPU accelerated spiking neural network simulator modeling Izhikevich spiking neurons with Spike Timing Dependent Plasticity (STDP) and homeostatic scaling. A range of subjects is considered from in-house clinical trials and public ECG databases. Results show high accuracy and low energy footprint in heart-rate estimation across subjects with and without cardiac irregularities, signifying the strong potential of this approach to be integrated in future wearable devices. Copyright © 2018 Elsevier Ltd. All rights reserved.
Realtime Multichannel System for Beat to Beat QT Interval Variability
NASA Technical Reports Server (NTRS)
Starc, Vito; Schlegel, Todd T.
2006-01-01
The measurement of beat-to-beat QT interval variability (QTV) shows clinical promise for identifying several types of cardiac pathology. However, until now, there has been no device capable of displaying, in real time on a beattobeat basis, changes in QTV in all 12 conventional leads in a continuously monitored patient. While several software programs have been designed to analyze QTV, heretofore, such programs have all involved only a few channels (at most) and/or have required laborious user interaction or offline calculations and postprocessing, limiting their clinical utility. This paper describes a PC-based ECG software program that in real time, acquires, analyzes and displays QTV and also PQ interval variability (PQV) in each of the eight independent channels that constitute the 12lead conventional ECG. The system also processes certain related signals that are derived from singular value decomposition and that help to reduce the overall effects of noise on the realtime QTV and PQV results.
[Practical experience about the compatibility of PDF converter in ECG information system].
Yang, Gang; Lu, Weishi; Zhou, Jiacheng
2009-11-01
To find a way to view ECG from different manufacturers in electrocardiogram information system. Different format ECG data were transmitted to ECG center by different ways. Corresponding analysis software was used to make the diagnosis reports in the center. Then we use PDF convert to change all ECG reports into PDF format. The electrocardiogram information system manage these PDF format ECG data for clinic user. The ECG reports form several major ECG manufacturers were transformed to PDF format successfully. In the electrocardiogram information system it is freely to view the ECG figure. PDF format ECG report is a practicable way to solve the compatibility problem in electrocardiogram information system.
Chatlapalli, S; Nazeran, H; Melarkod, V; Krishnam, R; Estrada, E; Pamula, Y; Cabrera, S
2004-01-01
The electrocardiogram (ECG) signal is used extensively as a low cost diagnostic tool to provide information concerning the heart's state of health. Accurate determination of the QRS complex, in particular, reliable detection of the R wave peak, is essential in computer based ECG analysis. ECG data from Physionet's Sleep-Apnea database were used to develop, test, and validate a robust heart rate variability (HRV) signal derivation algorithm. The HRV signal was derived from pre-processed ECG signals by developing an enhanced Hilbert transform (EHT) algorithm with built-in missing beat detection capability for reliable QRS detection. The performance of the EHT algorithm was then compared against that of a popular Hilbert transform-based (HT) QRS detection algorithm. Autoregressive (AR) modeling of the HRV power spectrum for both EHT- and HT-derived HRV signals was achieved and different parameters from their power spectra as well as approximate entropy were derived for comparison. Poincare plots were then used as a visualization tool to highlight the detection of the missing beats in the EHT method After validation of the EHT algorithm on ECG data from the Physionet, the algorithm was further tested and validated on a dataset obtained from children undergoing polysomnography for detection of sleep disordered breathing (SDB). Sensitive measures of accurate HRV signals were then derived to be used in detecting and diagnosing sleep disordered breathing in children. All signal processing algorithms were implemented in MATLAB. We present a description of the EHT algorithm and analyze pilot data for eight children undergoing nocturnal polysomnography. The pilot data demonstrated that the EHT method provides an accurate way of deriving the HRV signal and plays an important role in extraction of reliable measures to distinguish between periods of normal and sleep disordered breathing (SDB) in children.
Weber-Krüger, Mark; Gelbrich, Götz; Stahrenberg, Raoul; Liman, Jan; Kermer, Pawel; Hamann, Gerhard F; Seegers, Joachim; Gröschel, Klaus; Wachter, Rolf
2014-10-01
Detecting paroxysmal atrial fibrillation (AF) in patients with ischemic strokes presenting in sinus rhythm is challenging because episodes are often short, occur randomly, and are frequently asymptomatic. If AF is detected, recurrent thromboembolism can be prevented efficiently by oral anticoagulation. Numerous uncontrolled studies using various electrocardiogram (ECG) devices have established that prolonged ECG monitoring increases the yield of AF detection, but most established procedures are time-consuming and costly. The few randomized trials are mostly limited to cryptogenic strokes. The optimal method, duration, and patient selection remain unclear. Repeated prolonged continuous Holter ECG monitoring to detect paroxysmal AF within an unspecific stroke population may prove to be a widely applicable, effective secondary prevention strategy. Find-AFRANDOMISED is a randomized and controlled prospective multicenter trial. Four hundred patients 60 years or older with manifest (symptoms ≥24 hours or acute computed tomography/magnetic resonance imaging lesion) and acute (symptoms ≤7 days) ischemic strokes will be included at 4 certified stroke centers in Germany. Those with previously diagnosed AF/flutter, indications/contraindications for oral anticoagulation, or obvious causative blood vessel pathologies will be excluded. Patients will be randomized 1:1 to either enhanced and prolonged Holter ECG monitoring (10 days at baseline and after 3 and 6 months) or standard of care (≥24-hour continuous ECG monitoring, according to current stroke guidelines). All patients will be followed up for at least 12 months. The primary end point is newly detected AF (≥30 seconds) after 6 months, confirmed by an independent adjudication committee. We plan to complete recruitment in autumn 2014. First results can be expected by spring 2016. Copyright © 2014 Mosby, Inc. All rights reserved.
Homaeinezhad, M R; Sabetian, P; Feizollahi, A; Ghaffari, A; Rahmani, R
2012-02-01
The major focus of this study is to present a performance accuracy assessment framework based on mathematical modelling of cardiac system multiple measurement signals. Three mathematical algebraic subroutines with simple structural functions for synthetic generation of the synchronously triggered electrocardiogram (ECG), phonocardiogram (PCG) and arterial blood pressure (ABP) signals are described. In the case of ECG signals, normal and abnormal PQRST cycles in complicated conditions such as fascicular ventricular tachycardia, rate dependent conduction block and acute Q-wave infarctions of inferior and anterolateral walls can be simulated. Also, continuous ABP waveform with corresponding individual events such as systolic, diastolic and dicrotic pressures with normal or abnormal morphologies can be generated by another part of the model. In addition, the mathematical synthetic PCG framework is able to generate the S4-S1-S2-S3 cycles in normal and in cardiac disorder conditions such as stenosis, insufficiency, regurgitation and gallop. In the PCG model, the amplitude and frequency content (5-700 Hz) of each sound and variation patterns can be specified. The three proposed models were implemented to generate artificial signals with varies abnormality types and signal-to-noise ratios (SNR), for quantitative detection-delineation performance assessment of several ECG, PCG and ABP individual event detectors designed based on the Hilbert transform, discrete wavelet transform, geometric features such as area curve length (ACLM), the multiple higher order moments (MHOM) metric, and the principal components analysed geometric index (PCAGI). For each method the detection-delineation operating characteristics were obtained automatically in terms of sensitivity, positive predictivity and delineation (segmentation) error rms and checked by the cardiologist. The Matlab m-file script of the synthetic ECG, ABP and PCG signal generators are available in the Appendix.
PDF-ECG in clinical practice: A model for long-term preservation of digital 12-lead ECG data.
Sassi, Roberto; Bond, Raymond R; Cairns, Andrew; Finlay, Dewar D; Guldenring, Daniel; Libretti, Guido; Isola, Lamberto; Vaglio, Martino; Poeta, Roberto; Campana, Marco; Cuccia, Claudio; Badilini, Fabio
In clinical practice, data archiving of resting 12-lead electrocardiograms (ECGs) is mainly achieved by storing a PDF report in the hospital electronic health record (EHR). When available, digital ECG source data (raw samples) are only retained within the ECG management system. The widespread availability of the ECG source data would undoubtedly permit successive analysis and facilitate longitudinal studies, with both scientific and diagnostic benefits. PDF-ECG is a hybrid archival format which allows to store in the same file both the standard graphical report of an ECG together with its source ECG data (waveforms). Using PDF-ECG as a model to address the challenge of ECG data portability, long-term archiving and documentation, a real-world proof-of-concept test was conducted in a northern Italy hospital. A set of volunteers undertook a basic ECG using routine hospital equipment and the source data captured. Using dedicated web services, PDF-ECG documents were then generated and seamlessly uploaded in the hospital EHR, replacing the standard PDF reports automatically generated at the time of acquisition. Finally, the PDF-ECG files could be successfully retrieved and re-analyzed. Adding PDF-ECG to an existing EHR had a minimal impact on the hospital's workflow, while preserving the ECG digital data. Copyright © 2017 Elsevier Inc. All rights reserved.
On the normal scalar ECG. A new classification system considering age, sex and heart position.
Lundh, B
1984-01-01
472 randomly selected men and women from the city of Lund were examined for disease in the heart, lungs and for hypertension. 163 men and 194 women who had no symptom or sign of disease were accepted for the further study. The prevalence of various exclusion criterias, such as symptoms and signs of heart disease, lung disease and other diseases which may possibly affect the ECG are reported as well as the distribution of blood pressures in the sample. A computer-averaged standard 12-lead ECG (leads aVL, I, -aVR, II, aVF, III, V1-V6) was recorded. All measurements of ECG-deflections have been made visually using a magnifying glass (6 times). ST-segments were classified according to the Punsar code by independent visual observers as well as by the computer. The mean frontal QRS-axis shifted to the left with advancing age, but the shift was statistically significant only in men. In both men and women there was a leftward shift of the mean frontal QRS-axis with increased weight, increased chest circumference and increased obesity index. The normal range of axis was found to be 0 degrees to 90 degrees in men and +15 degrees to 90 degrees in women. The problems concerning the definition of the electrical heart position is discussed. The concept of a Q-axis is introduced as an alternative way to indicate electrical heart position. There is a statistical significant relationship between the Q-axis and the QRS-axis in the frontal plane, although this relationship is not always apparent in the individual ECG. The presence or absence of a Q-wave in an individual lead was used to denote a lead as being a left ventricular lead or not. Using the Q-wave as a marker of heart position in the individual lead is more practical than to use the QRS-axis or the transitional zone. Duration and amplitude of the Q-wave have been measured. The upper limit of normal duration exceeded 0.03 s in leads aVL and aVF in men but not in women. The R-wave amplitudes proved to vary with age and heart position in men. In women variation of the R-wave amplitude was found with heart position but not with age.(ABSTRACT TRUNCATED AT 400 WORDS)
Ubiquitous wireless ECG recording: a powerful tool physicians should embrace.
Saxon, Leslie A
2013-04-01
The use of smart phones has increased dramatically and there are nearly a billion users on 3G and 4G networks worldwide. Nearly 60% of the U.S. population uses smart phones to access the internet, and smart phone sales now surpass those of desktop and laptop computers. The speed of wireless communication technology on 3G and 4G networks and the widespread adoption and use of iOS equipped smart phones (Apple Inc., Cupertino, CA, USA) provide infrastructure for the transmission of wireless biomedical data, including ECG data. These technologies provide an unprecedented opportunity for physicians to continually access data that can be used to detect issues before symptoms occur or to have definitive data when symptoms are present. The technology also greatly empowers and enables the possibility for unprecedented patient participation in their own medical education and health status as well as that of their social network. As patient advocates, physicians and particularly cardiac electrophysiologists should embrace the future and promise of wireless ECG recording, a technology solution that can truly scale across the global population. © 2013 Wiley Periodicals, Inc.
New paradigms in telemedicine: ambient intelligence, wearable, pervasive and personalized.
Rubel, Paul; Fayn, Jocelyne; Simon-Chautemps, Lucas; Atoui, Hussein; Ohlsson, Mattias; Telisson, David; Adami, Stefano; Arod, Sébastien; Forlini, Marie Claire; Malossi, Cesare; Placide, Joël; Ziliani, Gian Luca; Assanelli, Deodato; Chevalier, Philippe
2004-01-01
After decades of development of information systems dedicated to health professionals, there is an increasing demand for personalized and non-hospital based care. An especially critical domain is cardiology: almost two third of cardiac deaths occur out of hospital, and victims do not survive long enough to benefit from in-hospital treatments. We need to reduce the time before treatment. But symptoms are often interpreted wrongly. The only immediate diagnostic tool to assess the possibility of a cardiac event is the electrocardiogram (ECG). Event and transtelephonic ECG recorders are used to improve decision making but require setting up new infrastructures. The European EPI-MEDICS project has developed an intelligent Personal ECG Monitor (PEM) for the early detection of cardiac events. The PEM embeds advanced decision making techniques, generates different alarm levels and forwards alarm messages to the relevant care providers by means of new generation wireless communication. It is cost saving, involving care provider only if necessary and requiring no specific infrastructure. This solution is a typical example of pervasive computing and ambient intelligence that demonstrates how personalized, wearable, ubiquitous devices could improve healthcare.
An augmented magnetic navigation system for Transcatheter Aortic Valve Implantation.
Luo, Zhe; Cai, Junfeng; Nie, Yuanyuan; Wang, Guotai; Gu, Lixu
2013-01-01
This research proposes an augmented magnetic navigation system for Transcatheter Aortic Valve Implantation (TAVI) employing a magnetic tracking system (MTS) combined with a dynamic aortic model and intra-operative ultrasound (US) images. The dynamic 3D aortic model is constructed based on the preoperative 4D computed tomography (CT), which is animated according to the real time electrocardiograph (ECG) input of patient. And a preoperative planning is performed to determine the target position of the aortic valve prosthesis. The temporal alignment is performed to synchronize the ECG signals, intra-operative US image and tracking information. Afterwards, with the assistance of synchronized ECG signals, the contour of aortic root automatic extracted from short axis US image is registered to the dynamic aortic model by a feature based registration intra-operatively. Then the augmented MTS guides the interventionist to confidently position and deploy the aortic valve prosthesis to target. The system was validated by animal studies on three porcine subjects, the deployment and tilting errors of which are 3.17 ± 0.91 mm and 7.40 ± 2.89° respectively.
Development of Novel Non-Contact Electrodes for Mobile Electrocardiogram Monitoring System
Chou, Willy; Wang, Hsing-Yu; Huang, Yan-Jun; Pan, Jeng-Shyang
2013-01-01
Real-time monitoring of cardiac health is helpful for patients with cardiovascular disease. Many telemedicine systems based on ubiquitous computing and communication techniques have been proposed for monitoring the user's electrocardiogram (ECG) anywhere and anytime. Usually, wet electrodes are used in these telemedicine systems. However, wet electrodes require conduction gels and skin preparation that can be inconvenient and uncomfortable for users. In order to overcome this issue, a new non-contact electrode circuit was proposed and applied in developing a mobile electrocardiogram monitoring system. The proposed non-contact electrode can measure bio-potentials across thin clothing, allowing it to be embedded in a user's normal clothing to monitor ECG in daily life. We attempted to simplify the design of these non-contact electrodes to reduce power consumption while continuing to provide good signal quality. The electrical specifications and the performance of monitoring arrhythmia in clinical settings were also validated to investigate the reliability of the proposed design. Experimental results show that the proposed non-contact electrode provides good signal quality for measuring ECG across thin clothes. PMID:27170853
Low-power wireless ECG acquisition and classification system for body sensor networks.
Lee, Shuenn-Yuh; Hong, Jia-Hua; Hsieh, Cheng-Han; Liang, Ming-Chun; Chang Chien, Shih-Yu; Lin, Kuang-Hao
2015-01-01
A low-power biosignal acquisition and classification system for body sensor networks is proposed. The proposed system consists of three main parts: 1) a high-pass sigma delta modulator-based biosignal processor (BSP) for signal acquisition and digitization, 2) a low-power, super-regenerative on-off keying transceiver for short-range wireless transmission, and 3) a digital signal processor (DSP) for electrocardiogram (ECG) classification. The BSP and transmitter circuits, which are the body-end circuits, can be operated for over 80 days using two 605 mAH zinc-air batteries as the power supply; the power consumption is 586.5 μW. As for the radio frequency receiver and DSP, which are the receiving-end circuits that can be integrated in smartphones or personal computers, power consumption is less than 1 mW. With a wavelet transform-based digital signal processing circuit and a diagnosis control by cardiologists, the accuracy of beat detection and ECG classification are close to 99.44% and 97.25%, respectively. All chips are fabricated in TSMC 0.18-μm standard CMOS process.
Four-dimensional black holes in Einsteinian cubic gravity
NASA Astrophysics Data System (ADS)
Bueno, Pablo; Cano, Pablo A.
2016-12-01
We construct static and spherically symmetric generalizations of the Schwarzschild- and Reissner-Nordström-(anti-)de Sitter [RN-(A)dS] black-hole solutions in four-dimensional Einsteinian cubic gravity (ECG). The solutions are characterized by a single function which satisfies a nonlinear second-order differential equation. Interestingly, we are able to compute independently the Hawking temperature T , the Wald entropy S and the Abbott-Deser mass M of the solutions analytically as functions of the horizon radius and the ECG coupling constant λ . Using these we show that the first law of black-hole mechanics is exactly satisfied. Some of the solutions have positive specific heat, which makes them thermodynamically stable, even in the uncharged and asymptotically flat case. Further, we claim that, up to cubic order in curvature, ECG is the most general four-dimensional theory of gravity which allows for nontrivial generalizations of Schwarzschild- and RN-(A)dS characterized by a single function which reduce to the usual Einstein gravity solutions when the corresponding higher-order couplings are set to zero.
Panoramic ECG display versus conventional ECG: ischaemia detection by critical care nurses.
Wilson, Nick; Hassani, Aimen; Gibson, Vanessa; Lightfoot, Timothy; Zizzo, Claudio
2012-01-01
To compare accuracy and certainty of diagnosis of cardiac ischaemia using the Panoramic ECG display tool plus conventional 12-lead electrocardiogram (ECG) versus 12-lead ECG alone by UK critical care nurses who were members of the British Association of Critical Care Nurses (BACCN). Critically ill patients are prone to myocardial ischaemia. Symptoms may be masked by sedation or analgesia, and ECG changes may be the only sign. Critical care nurses have an essential role in detecting ECG changes promptly. Despite this, critical care nurses may lack expertise in interpreting ECGs and myocardial ischaemia often goes undetected by critical care staff. British Association of Critical Care Nurses (BACCN) members were invited to complete an online survey to evaluate the analysis of two sets of eight ECGs displayed alone and with the new display device. Data from 82 participants showed diagnostic accuracy improved from 67·1% reading ECG traces alone, to 96·0% reading ECG plus Panoramic ECG display tool (P < 0·01, significance level α = 0·05). Participants' diagnostic certainty score rose from 41·7% reading ECG alone to 66·8% reading ECG plus Panoramic ECG display tool (P < 0·01, α = 0·05). The Panoramic ECG display tool improves both accuracy and certainty of detecting ST segment changes among critical care nurses, when compared to conventional 12-lead ECG alone. This benefit was greatest with early ischaemic changes. Critical care nurses who are least confident in reading conventional ECGs benefit the most from the new display. Critical care nurses have an essential role in the monitoring of critically ill patients. However, nurses do not always have the expertise to detect subtle ischaemic ECG changes promptly. Introduction of the Panoramic ECG display tool into clinical practice could lead to patients receiving treatment for myocardial ischaemia sooner with the potential for reduction in morbidity and mortality. © 2012 The Authors. Nursing in Critical Care © 2012 British Association of Critical Care Nurses.
Accuracy of ECG interpretation in competitive athletes: the impact of using standised ECG criteria.
Drezner, Jonathan A; Asif, Irfan M; Owens, David S; Prutkin, Jordan M; Salerno, Jack C; Fean, Robyn; Rao, Ashwin L; Stout, Karen; Harmon, Kimberly G
2012-04-01
Interpretation of ECGs in athletes is complicated by physiological changes related to training. The purpose of this study was to determine the accuracy of ECG interpretation in athletes among different physician specialties, with and without use of a standised ECG criteria tool. Physicians were asked to interpret 40 ECGs (28 normal ECGs from college athletes randomised with 12 abnormal ECGs from individuals with known ciovascular pathology) and classify each ECG as (1) 'normal or variant--no further evaluation and testing needed' or (2) 'abnormal--further evaluation and testing needed.' After reading the ECGs, participants received a two-page ECG criteria tool to guide interpretation of the ECGs again. A total of 60 physicians participated: 22 primary care (PC) residents, 16 PC attending physicians, 12 sports medicine (SM) physicians and 10 ciologists. At baseline, the total number of ECGs correctly interpreted was PC residents 73%, PC attendings 73%, SM physicians 78% and ciologists 85%. With use of the ECG criteria tool, all physician groups significantly improved their accuracy (p<0.0001): PC residents 92%, PC attendings 90%, SM physicians 91% and ciologists 96%. With use of the ECG criteria tool, specificity improved from 70% to 91%, sensitivity improved from 89% to 94% and there was no difference comparing ciologists versus all other physicians (p=0.053). Providing standised criteria to assist ECG interpretation in athletes significantly improves the ability to accurately distinguish normal from abnormal findings across physician specialties, even in physicians with little or no experience.
A novel time-domain signal processing algorithm for real time ventricular fibrillation detection
NASA Astrophysics Data System (ADS)
Monte, G. E.; Scarone, N. C.; Liscovsky, P. O.; Rotter S/N, P.
2011-12-01
This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies.
Vezzosi, T; Buralli, C; Marchesotti, F; Porporato, F; Tognetti, R; Zini, E; Domenech, O
2016-10-01
The diagnostic accuracy of a smartphone electrocardiograph (ECG) in evaluating heart rhythm and ECG measurements was evaluated in 166 dogs. A standard 6-lead ECG was acquired for 1 min in each dog. A smartphone ECG tracing was simultaneously recorded using a single-lead bipolar ECG recorder. All ECGs were reviewed by one blinded operator, who judged if tracings were acceptable for interpretation and assigned an electrocardiographic diagnosis. Agreement between smartphone and standard ECG in the interpretation of tracings was evaluated. Sensitivity and specificity for the detection of arrhythmia were calculated for the smartphone ECG. Smartphone ECG tracings were interpretable in 162/166 (97.6%) tracings. A perfect agreement between the smartphone and standard ECG was found in detecting bradycardia, tachycardia, ectopic beats and atrioventricular blocks. A very good agreement was found in detecting sinus rhythm versus non-sinus rhythm (100% sensitivity and 97.9% specificity). The smartphone ECG provided tracings that were adequate for analysis in most dogs, with an accurate assessment of heart rate, rhythm and common arrhythmias. The smartphone ECG represents an additional tool in the diagnosis of arrhythmias in dogs, but is not a substitute for a 6-lead ECG. Arrhythmias identified by the smartphone ECG should be followed up with a standard ECG before making clinical decisions. Copyright © 2016 Elsevier Ltd. All rights reserved.
A markup language for electrocardiogram data acquisition and analysis (ecgML)
Wang, Haiying; Azuaje, Francisco; Jung, Benjamin; Black, Norman
2003-01-01
Background The storage and distribution of electrocardiogram data is based on different formats. There is a need to promote the development of standards for their exchange and analysis. Such models should be platform-/ system- and application-independent, flexible and open to every member of the scientific community. Methods A minimum set of information for the representation and storage of electrocardiogram signals has been synthesised from existing recommendations. This specification is encoded into an XML-vocabulary. The model may aid in a flexible exchange and analysis of electrocardiogram information. Results Based on advantages of XML technologies, ecgML has the ability to present a system-, application- and format-independent solution for representation and exchange of electrocardiogram data. The distinction between the proposal developed by the U.S Food and Drug Administration and ecgML model is given. A series of tools, which aim to facilitate ecgML-based applications, are presented. Conclusions The models proposed here can facilitate the generation of a data format, which opens ways for better and clearer interpretation by both humans and machines. Its structured and transparent organisation will allow researchers to expand and test its capabilities in different application domains. The specification and programs for this protocol are publicly available. PMID:12735790
Fermi-Pasta-Ulam auto recurrence in the description of the electrical activity of the heart.
Novopashin, M A; Shmid, A V; Berezin, A A
2017-04-01
The authors proposed and mathematically described model of a new type of the Fermi-Pasta-Ulam recurrence (the FPU auto recurrence) and hypothesized an adequate description of the heart's electrical dynamics within the observed phenomenon. The dynamics of the FPU auto recurrence making appropriate electrical dynamics of the normal functioning of the heart in the form of an electrocardiogram (ECG) was obtained by a computer model study. The model solutions in the form of the FPU auto recurrence - ECG Fourier spectrum were evaluated for resistance to external disturbances in the form of random effects, as well as periodic perturbation at a frequency close to the heart beating rate of about 1Hz. In addition, in order to simulate the dynamics of myocardial infarction model, studied the effect of the surface area of the myocardium on the stability and shape of the auto recurrence - ECG spectrum. It has been found that the intense external disturbing periodic impacts at a frequency of about 1Hz lead to a sharp disturbance spectrum shape FPU auto recurrence - ECG structure. In addition, the decrease in the surface of the myocardium by 50% in the model led to the destruction of structures of the auto recurrence - ECG, which corresponds to the state of atrial myocardium. Research models have revealed a hypothetical basis of coronary heart disease in the form of increasing the energy of high-frequency harmonics spectrum of the auto recurrence by reducing the energy of low-frequency harmonic spectrum of the auto recurrence, which ultimately leads to a sharp decrease in myocardial contractility. In order to test the hypothesis has been studied more than 20,000 ECGs both healthy people and patients with cardiovascular disease. As a result of these studies, it was found that the dynamics of the electrical activity of normal functioning of the heart can be interpreted by the display of the detected by authors the FPU auto recurrence, and coronary heart disease is a violation of the energy ratio between the low and high frequency harmonics of the FPU auto recurrence Fourier spectrum equal to the ECG spectrum. Thus, the hypothesis has been confirmed. Copyright © 2017 Elsevier Ltd. All rights reserved.
Tele-electrocardiography in the epidemiological 'Study of Health in Pomerania' (SHIP).
Alte, Dietrich; Völzke, Henry; Robinson, Daniel M; Kleine, Volker; Grabe, Hans Jörgen; John, Ulrich; Felix, Stephan B
2006-01-01
We have evaluated a portable electrocardiogram (ECG) card in the large population-based epidemiological 'Study of Health in Pomerania' (SHIP). In all, 7008 men and women (20-79 years) were randomly selected from population registries and 4310 subjects participated. Participants used an ECG card for four weeks and recorded two ECGs daily. The participants were also encouraged to record additional ECGs in the case of symptomatic arrhythmias, chest pain or dizziness. The ECGs were sent via telephone. Acrobat (.pdf) files arrived at the study centre via email. Arrhythmias were analysed by visual ECG inspection. Seventy-one per cent of the participants sent at least 80% of the requested ECGs for four weeks. There were few problems (about 70) in the total of 38,162 ECGs transmitted. Overall, 94% of all ECGs were rated as 'good'. Physicians required about 1.5 h to read approximately 100 ECGs daily. The functionality and ergonomics of ECG cards appear to be sufficiently developed for large-scale use in epidemiological studies.
WaveformECG: A Platform for Visualizing, Annotating, and Analyzing ECG Data
Winslow, Raimond L.; Granite, Stephen; Jurado, Christian
2017-01-01
The electrocardiogram (ECG) is the most commonly collected data in cardiovascular research because of the ease with which it can be measured and because changes in ECG waveforms reflect underlying aspects of heart disease. Accessed through a browser, WaveformECG is an open source platform supporting interactive analysis, visualization, and annotation of ECGs. PMID:28642673
Pourier, Milanthy S; Mavinkurve-Groothuis, Annelies M C; Loonen, Jacqueline; Bökkerink, Jos P M; Roeleveld, Nel; Beer, Gil; Bellersen, Louise; Kapusta, Livia
2017-03-01
ECG and echocardiography are noninvasive screening tools to detect subclinical cardiotoxicity in childhood cancer survivors (CCSs). Our aims were as follows: (1) assess the prevalence of abnormal ECG patterns, (2) determine the agreement between abnormal ECG patterns and echocardiographic abnormalities; and (3) determine whether ECG screening for subclinical cardiotoxicity in CCSs is justified. We retrospectively studied ECG and echocardiography in asymptomatic CCSs more than 5 years after anthracycline treatment. Exclusion criteria were abnormal ECG and/or echocardiogram at the start of therapy, incomplete follow-up data, clinical heart failure, cardiac medication, and congenital heart disease. ECG abnormalities were classified using the Minnesota Code. Level of agreement between ECG and echocardiography was calculated with Cohen kappa. We included 340 survivors with a mean follow-up of 14.5 years (range 5-32). ECG was abnormal in 73 survivors (21.5%), with ventricular conduction disorders, sinus bradycardia, and high-amplitude R waves being most common. Prolonged QTc (>0.45 msec) was found in two survivors, both with a cumulative anthracycline dose of 300 mg/m 2 or higher. Echocardiography showed abnormalities in 44 survivors (12.9%), mostly mild valvular abnormalities. The level of agreement between ECG and echocardiography was low (kappa 0.09). Male survivors more often had an abnormal ECG (corrected odds ratio: 3.00, 95% confidence interval: 1.68-5.37). Abnormal ECG patterns were present in 21% of asymptomatic long-term CCSs. Lack of agreement between abnormal ECG patterns and echocardiographic abnormalities may suggest that ECG is valuable in long-term follow-up of CCSs. However, it is not clear whether these abnormal ECG patterns will be clinically relevant. © 2016 Wiley Periodicals, Inc.
Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery
Sivaraks, Haemwaan
2015-01-01
Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods. PMID:25688284
Evaluation of an electrocardiogram on QR code.
Nakayama, Masaharu; Shimokawa, Hiroaki
2013-01-01
An electrocardiogram (ECG) is an indispensable tool to diagnose cardiac diseases, such as ischemic heart disease, myocarditis, arrhythmia, and cardiomyopathy. Since ECG patterns vary depend on patient status, it is also used to monitor patients during treatment and comparison with ECGs with previous results is important for accurate diagnosis. However, the comparison requires connection to ECG data server in a hospital and the availability of data connection among hospitals is limited. To improve the portability and availability of ECG data regardless of server connection, we here introduce conversion of ECG data into 2D barcodes as text data and decode of the QR code for drawing ECG with Google Chart API. Fourteen cardiologists and six general physicians evaluated the system using iPhone and iPad. Overall, they were satisfied with the system in usability and accuracy of decoded ECG compared to the original ECG. This new coding system may be useful in utilizing ECG data irrespective of server connections.
The future of remote ECG monitoring systems.
Guo, Shu-Li; Han, Li-Na; Liu, Hong-Wei; Si, Quan-Jin; Kong, De-Feng; Guo, Fu-Su
2016-09-01
Remote ECG monitoring systems are becoming commonplace medical devices for remote heart monitoring. In recent years, remote ECG monitoring systems have been applied in the monitoring of various kinds of heart diseases, and the quality of the transmission and reception of the ECG signals during remote process kept advancing. However, there remains accompanying challenges. This report focuses on the three components of the remote ECG monitoring system: patient (the end user), the doctor workstation, and the remote server, reviewing and evaluating the imminent challenges on the wearable systems, packet loss in remote transmission, portable ECG monitoring system, patient ECG data collection system, and ECG signals transmission including real-time processing ST segment, R wave, RR interval and QRS wave, etc. This paper tries to clarify the future developmental strategies of the ECG remote monitoring, which can be helpful in guiding the research and development of remote ECG monitoring.
Fernandez, Antonio B; Nunes, Maria Carmo P; Clark, Eva H; Samuels, Aaron; Menacho, Silvio; Gomez, Jesus; Bozo Gutierrez, Ricardo W; Crawford, Thomas C; Gilman, Robert H; Bern, Caryn
2015-09-01
Chagas disease is a neglected and preventable tropical disease that causes significant cardiac morbidity and mortality in Latin America. This study sought to describe cardiac findings among inhabitants of rural communities of the Bolivian Chaco. The cardiac study drew participants from an epidemiologic study in 7 indigenous Guarani communities. All infected participants 10 years or older were asked to undergo a brief physical examination and 12-lead electrocardiogram (ECG). A subset had echocardiograms. ECG and echocardiograms were read by 1 or more cardiologists. Of 1,137 residents 10 years or older, 753 (66.2%) had Trypanosoma cruzi infection. Cardiac evaluations were performed for 398 infected participants 10 years or older. Fifty-five participants (13.8%) had 1 or more ECG abnormalities suggestive of Chagas cardiomyopathy. The most frequent abnormalities were bundle branch blocks in 42 (11.3%), followed by rhythm disturbances or ventricular ectopy in 13 (3.3%), and atrioventricular blocks (AVB) in 10 participants (2.6%). The prevalence of any abnormality rose from 1.1% among those 10 to 19 years old to 14.2%, 17.3%, and 26.4% among those 20 to 39, 40 to 59, and older than 60 years, respectively. First-degree AVB was seen most frequently in participants 60 years or older, but the 4 patients with third-degree AVB were all under 50 years old. Eighteen and 2 participants had a left ventricular ejection fraction of 40% to 54% and <40%, respectively. An increasing number of ECG abnormalities was associated with progressively larger left ventricular end-diastolic dimensions and lower left ventricular ejection fraction. We found a high prevalence of ECG abnormalities and substantial evidence of Chagas cardiomyopathy. Programs to improve access to basic cardiac care (annual ECG, antiarrhythmics, pacemakers) could have an immediate impact on morbidity and mortality in these highly endemic communities. Copyright © 2015 World Heart Federation (Geneva). All rights reserved.
Wang, Duolao; Bakhai, Ameet; Arezina, Radivoj; Täubel, Jörg
2016-11-01
Electrocardiogram (ECG) variability is greatly affected by the ECG recording method. This study aims to compare Holter and standard ECG recording methods in terms of central locations and variations of ECG data. We used the ECG data from a double-blinded, placebo-controlled, randomized clinical trial and used a mixed model approach to assess the agreement between two methods in central locations and variations of eight ECG parameters (Heart Rate, PR, QRS, QT, RR, QTcB, QTcF, and QTcI intervals). A total of 34 heathy male subjects with mean age of 25.7 ± 4.78 years were randomized to receive either active drug or placebo. Digital 12-lead ECG and digital 12-lead Holter ECG recordings were performed to assess ECG variability. There are no significant differences in least square mean between the Holter and the standard method for all ECG parameters. The total variance is consistently higher for the Holter method than the standard method for all ECG parameters except for QRS. The intraclass correlation coefficient (ICC) values for the Holter method are consistently lower than those for the standard method for all ECG parameters except for QRS, in particular, the ICC for QTcF is reduced from 0.86 for the standard method to 0.67 for the Holter method. This study suggests that Holter ECGs recorded in a controlled environment are not significantly different but more variable than those from the standard method. © 2016 Wiley Periodicals, Inc.
Bolen, Michael A; Popovic, Zoran B; Dahiya, Arun; Kapadia, Samir R; Tuzcu, E Murat; Flamm, Scott D; Halliburton, Sandra S; Schoenhagen, Paul
2012-01-01
Transcatheter valve interventions rely on imaging for patient selection, preprocedural planning, and intraprocedural guidance. We explored the use of prospective electrocardiogram (ECG)-triggered 4-dimensional (4-D) CT imaging in patients evaluated for transcatheter aortic valve replacement (TAVR). A total of 47 consecutive patients underwent 128-slice dual-source CT with wide-window dose-modulated prospective ECG-triggered, axial acquisition of the aortic root, reconstructed during diastolic and systolic cardiac phases. Image quality was evaluated, aortic root and left ventricular (LV) geometry and function were analyzed, and radiation exposure was estimated. Image quality was generally good, with 41 of 47 (87%) patients scored as good or excellent. The mean aortic valve area was 0.93 ± 0.24 cm(2). Mean LV ejection fraction was 56.8% ± 16.4%, and mean LV mass was 130.4 ± 43.8 g. The minor diameter of the annulus was larger in systole (systole, 2.29 ± 0.24 cm; diastole, 2.14 ± 0.25 cm; P = 0.006), but the mean and major diameters did not vary significantly between systole and diastole. The mean estimated effective dose was 5.9 ± 2.4 mSv. Multiphase, prospective ECG-triggered axial image acquisition is a lower dose acquisition technique for 4-D aortic root imaging in patients being considered for TAVR. Copyright © 2012 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
Some regularity on how to locate electrodes for higher fECG SNRs
NASA Astrophysics Data System (ADS)
Zhang, Jie-Min; Huang, Xiao-Lin; Guan, Qun; Liu, Tie-Bing; Li, Ping; Zhao, Ying; Liu, Hong-Xing
2015-03-01
The electrocardiogram (ECG) recorded from the abdominal surface of a pregnant woman is a composite of maternal ECG, fetal ECG (fECG) and other noises, while only the fECG component is always needed by us. With different locations of electrode pairs on the maternal abdominal surface to measure fECGs, the signal-to-noise ratios (SNRs) of the recorded abdominal ECGs are also correspondingly different. Some regularity on how to locate electrodes to obtain higher fECG SNRs is needed practically. In this paper, 343 groups of abdominal ECG records were acquired from 78 pregnant women with different electrode pairs locating, and an appropriate extended research database is formed. Then the regularity on fECG SNRs corresponding to different electrode pairs locating was studied. Based on statistical analysis, it is shown that the fECG SNRs are significantly higher in certain locations than others. Reasonable explanation is also provided to the statistical result using the theories of the fetal cardiac electrical axis and the signal phase delay. Project supported by the National Natural Science Foundation of China (Grant No. 61271079) and the Supporting Plan Project of Jiangsu Province, China (Grant No. BE2010720).
Chang, Anthony C
2012-03-01
The preparticipation screening for athlete participation in sports typically entails a comprehensive medical and family history and a complete physical examination. A 12-lead electrocardiogram (ECG) can increase the likelihood of detecting cardiac diagnoses such as hypertrophic cardiomyopathy, but this diagnostic test as part of the screening process has engendered considerable controversy. The pro position is supported by argument that international screening protocols support its use, positive diagnosis has multiple benefits, history and physical examination are inadequate, primary prevention is essential, and the cost effectiveness is justified. Although the aforementioned myriad of justifications for routine ECG screening of young athletes can be persuasive, several valid contentions oppose supporting such a policy, namely, that the sudden death incidence is very (too) low, the ECG screening will be too costly, the false-positive rate is too high, resources will be allocated away from other diseases, and manpower is insufficient for its execution. Clinicians, including pediatric cardiologists, have an understandable proclivity for avoiding this prodigious national endeavor. The controversy, however, should not be focused on whether an inexpensive, noninvasive test such as an ECG should be mandated but should instead be directed at just how these tests for young athletes can be performed in the clinical imbroglio of these disease states (with variable genetic penetrance and phenotypic expression) with concomitant fiscal accountability and logistical expediency in this era of economic restraint. This monumental endeavor in any city or region requires two crucial elements well known to business scholars: implementation and execution. The eventual solution for the screening ECG dilemma requires a truly innovative and systematic approach that will liberate us from inadequate conventional solutions. Artificial intelligence, specifically the process termed "machine learning" and "neural networking," involves complex algorithms that allow computers to improve the decision-making process based on repeated input of empirical data (e.g., databases and ECGs). These elements all can be improved with a national database, evidence-based medicine, and in the near future, innovation that entails a Kurzweilian artificial intelligence infrastructure with machine learning and neural networking that will construct the ultimate clinical decision-making algorithm.
Design of portable electrocardiogram device using DSO138
NASA Astrophysics Data System (ADS)
Abuzairi, Tomy; Matondang, Josef Stevanus; Purnamaningsih, Retno Wigajatri; Basari, Ratnasari, Anita
2018-02-01
Cardiovascular disease has been one of the leading causes of sudden cardiac deaths in many countries, covering Indonesia. Electrocardiogram (ECG) is a medical test to detect cardiac abnormalities by measuring the electrical activity generated by the heart, as the heart contracts. By using ECG, we can observe anomaly at the time of heart abnormalities. In this paper, design of portable ECG device is presented. The portable ECG device was designed to easily use in the village clinic or houses, due to the small size device and other benefits. The device was designed by using four units: (1) ECG electrode; (2) ECG analog front-end; (3) DSO138; and (4) battery. To create a simple electrode system in the portable ECG, 1-lead ECG with two electrodes were applied. The analog front-end circuitry consists of three integrated circuits, an instrumentation amplifier AD820AN, a low noise operational amplifier OPA134, and a low offset operational amplifier TL082. Digital ECG data were transformed to graphical data on DSO138. The results show that the portable ECG is successfully read the signal from 1-lead ECG system.
ECG Sensor Card with Evolving RBP Algorithms for Human Verification.
Tseng, Kuo-Kun; Huang, Huang-Nan; Zeng, Fufu; Tu, Shu-Yi
2015-08-21
It is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a statistical-based ECG algorithm, with the aid of a reduced binary pattern (RBP), with the aim of achieving faster ECG human identity recognition with high accuracy. The proposed algorithm has one advantage that previous ECG algorithms lack-the waveform complex information and de-noising preprocessing can be bypassed; therefore, it is more suitable for non-stationary ECG signals. Experimental results tested on two public ECG databases (MIT-BIH) from MIT University confirm that the proposed scheme is feasible with excellent accuracy, low complexity, and speedy processing. To be more specific, the advanced RBP algorithm achieves high accuracy in human identity recognition and is executed at least nine times faster than previous algorithms. Moreover, based on the test results from a long-term ECG database, the evolving RBP algorithm also demonstrates superior capability in handling long-term and non-stationary ECG signals.
Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.
Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko
2017-07-01
Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.
Isoflurane increases cardiorespiratory coordination in rats
NASA Astrophysics Data System (ADS)
Kabir, Muammar M.; Beig, Mirza I.; Nalivaiko, Eugene; Abbott, Derek; Baumert, Mathias
2008-12-01
Anesthetics such as isoflurane adversely affect heart rate. In this study we analysed the interaction between heart rhythm and respiration at different concentrations of isoflurane and ventilation rates. In two rats, the electrocardiogram (ECG) and respiratory signals were recorded under the influence of isoflurane. For the assessment of cardiorespiratory coordination, we analysed the phase locking between heart rate, computed from the R-R intervals of body surface ECG, and respiratory rate, computed from impedance changes, using Hilbert transform. The changes in heart rate, percentage of synchronization and duration of synchronized epochs at different isoflurane concentrations and ventilation rates were assessed using linear regression model. From this study it appears that the amount of phase locking between cardiac and respiratory rates increases with the increase in concentration of isoflurane. Heart rate and duration of synchronized epochs increased significantly with the increase in the level of isoflurane concentration while respiratory rate was not significantly affected. Cardiorespiratory coordination also showed a considerable increase at the ventilation rates of 50- 55 cpm in both the rats, suggesting that the phase-locking between the cardiac and respiratory oscillators can be increased by breathing at a particular respiratory frequency.
The order of three lowest-energy states of the six-electron harmonium at small force constant
DOE Office of Scientific and Technical Information (OSTI.GOV)
Strasburger, Krzysztof
2016-06-21
The order of low-energy states of six-electron harmonium is uncertain in the case of strong correlation, which is not a desired situation for the model system being considered for future testing of approximate methods of quantum chemistry. The computational study of these states has been carried out at the frequency parameter ω = 0.01, using the variational method with the basis of symmetry-projected, explicitly correlated Gaussian (ECG) lobe functions. It has revealed that the six-electron harmonium at this confinement strength is an octahedral Wigner molecule, whose order of states is different than in the strong confinement regime and does notmore » agree with the earlier predictions. The results obtained for ω = 0.5 and 10 are consistent with the findings based on the Hund’s rules for the s{sup 2}p{sup 4} electron configuration. Substantial part of the computations has been carried out on the graphical processing units and the efficiency of these devices in calculation of the integrals over ECG functions has been compared with traditional processors.« less
Lee, Sun Hee; Jung, Ji Mi; Song, Min Seob; Choi, Seok jin; Chung, Woo Yeong
2013-08-01
Turner syndrome is well known to be associated with significant cardiovascular abnormalities. This paper studied the incidence of cardiovascular abnormalities in asymptomatic adolescent patients with Turner syndrome using multidetector computed tomography (MDCT) instead of echocardiography. Twenty subjects diagnosed with Turner syndrome who had no cardiac symptoms were included. Blood pressure and electrocardiography (ECG) was checked. Cardiovascular abnormalities were checked by MDCT. According to the ECG results, 11 had a prolonged QTc interval, 5 had a posterior fascicular block, 3 had a ventricular conduction disorder. MDCT revealed vascular abnormalities in 13 patients (65%). Three patients had an aberrant right subclavian artery, 2 had dilatation of left subclavian artery, and others had an aortic root dilatation, aortic diverticulum, and abnormal left vertebral artery. As for venous abnormalities, 3 patients had partial anomalous pulmonary venous return and 2 had a persistent left superior vena cava. This study found cardiovascular abnormalities in 65% of asymptomatic Turner syndrome patients using MDCT. Even though, there are no cardiac symptoms in Turner syndrome patients, a complete evaluation of the heart with echocardiography or MDCT at transition period to adults must be performed.
Competency in ECG Interpretation Among Medical Students
Kopeć, Grzegorz; Magoń, Wojciech; Hołda, Mateusz; Podolec, Piotr
2015-01-01
Background Electrocardiogram (ECG) is commonly used in diagnosis of heart diseases, including many life-threatening disorders. We aimed to assess skills in ECG interpretation among Polish medical students and to analyze the determinants of these skills. Material/Methods Undergraduates from all Polish medical schools were asked to complete a web-based survey containing 18 ECG strips. Questions concerned primary ECG parameters (rate, rhythm, and axis), emergencies, and common ECG abnormalities. Analysis was restricted to students in their clinical years (4th–6th), and students in their preclinical years (1st–3rd) were used as controls. Results We enrolled 536 medical students (females: n=299; 55.8%), aged 19 to 31 (23±1.6) years from all Polish medical schools. Most (72%) were in their clinical years. The overall rate of good response was better in students in years 4th–5th than those in years 1st–3rd (66% vs. 56%; p<0.0001). Competency in ECG interpretation was higher in students who reported ECG self-learning (69% vs. 62%; p<0.0001) but no difference was found between students who attended or did not attend regular ECG classes (66% vs. 66%; p=0.99). On multivariable analysis (p<0.0001), being in clinical years (OR: 2.45 [1.35–4.46] and self-learning (OR: 2.44 [1.46–4.08]) determined competency in ECG interpretation. Conclusions Polish medical students in their clinical years have a good level of competency in interpreting the primary ECG parameters, but their ability to recognize ECG signs of emergencies and common heart abnormalities is low. ECG interpretation skills are determined by self-education but not by attendance at regular ECG classes. Our results indicate qualitative and quantitative deficiencies in teaching ECG interpretation at medical schools. PMID:26541993
NASA Technical Reports Server (NTRS)
Schlegel, Todd T. (Inventor); Arenare, Brian (Inventor)
2008-01-01
Cardiac electrical data are received from a patient, manipulated to determine various useful aspects of the ECG signal, and displayed and stored in a useful form using a computer. The computer monitor displays various useful information, and in particular graphically displays various permutations of reduced amplitude zones and kurtosis that increase the rapidity and accuracy of cardiac diagnoses. New criteria for reduced amplitude zones are defined that enhance the sensitivity and specificity for detecting cardiac abnormalities.
O'Donnell, Daniel; Mancera, Mike; Savory, Eric; Christopher, Shawn; Schaffer, Jason; Roumpf, Steve
2015-01-01
Early and accurate identification of ST-elevation myocardial infarction (STEMI) by prehospital providers has been shown to significantly improve door to balloon times and improve patient outcomes. Previous studies have shown that paramedic accuracy in reading 12 lead ECGs can range from 86% to 94%. However, recent studies have demonstrated that accuracy diminishes for the more uncommon STEMI presentations (e.g. lateral). Unlike hospital physicians, paramedics rarely have the ability to review previous ECGs for comparison. Whether or not a prior ECG can improve paramedic accuracy is not known. The availability of prior ECGs improves paramedic accuracy in ECG interpretation. 130 paramedics were given a single clinical scenario. Then they were randomly assigned 12 computerized prehospital ECGs, 6 with and 6 without an accompanying prior ECG. All ECGs were obtained from a local STEMI registry. For each ECG paramedics were asked to determine whether or not there was a STEMI and to rate their confidence in their interpretation. To determine if the old ECGs improved accuracy we used a mixed effects logistic regression model to calculate p-values between the control and intervention. The addition of a previous ECG improved the accuracy of identifying STEMIs from 75.5% to 80.5% (p=0.015). A previous ECG also increased paramedic confidence in their interpretation (p=0.011). The availability of previous ECGs improves paramedic accuracy and enhances their confidence in interpreting STEMIs. Further studies are needed to evaluate this impact in a clinical setting. Copyright © 2015 Elsevier Inc. All rights reserved.
O'Neal, Wesley T; Lee, Kristine E; Soliman, Elsayed Z; Klein, Ronald; Klein, Barbara E K
2017-03-01
To determine the incidence and determinants of developing abnormalities on the 12-lead electrocardiogram (ECG) in persons with type 1 diabetes. We evaluated the distribution of ECG abnormalities and risk factors for developing new abnormalities in 266 (mean age = 44 years ± 9.0; 50 % female) people with type 1 diabetes from the Wisconsin Epidemiologic Study of Diabetic Retinopathy. This analysis included participants with complete ECG data from study visit 5 (2000-2001) and follow-up ECGs from study visit 7 (2012-2014). ECG abnormalities were classified as major and minor according to Minnesota Code Classification. At baseline, 94 (35 %) participants had at least one ECG abnormality, including 13 major ECG abnormalities. At follow-up, 117 (44 %) participants developed at least one new ECG abnormality, including 35 new major ECG abnormalities. In a multivariable logistic regression model, older age (per 5-year increase: OR = 1.31, 95 % CI = 1.08, 1.60) was associated with the development of at least one new ECG abnormality, while serum HDL cholesterol (per 10-unit increase: OR = 0.98, 95 % CI = 0.96, 1.00) was protective against developing new ECG abnormalities. The development of new ECG abnormalities is common in type 1 diabetes. Older age and HDL cholesterol are independent risk factors for developing new ECG abnormalities. Further research is needed to determine whether routine ECG screening is indicated in people with type 1 diabetes to identify those with underlying subclinical coronary heart disease.
ECG based Myocardial Infarction detection using Hybrid Firefly Algorithm.
Kora, Padmavathi
2017-12-01
Myocardial Infarction (MI) is one of the most frequent diseases, and can also cause demise, disability and monetary loss in patients who suffer from cardiovascular disorder. Diagnostic methods of this ailment by physicians are typically invasive, even though they do not fulfill the required detection accuracy. Recent feature extraction methods, for example, Auto Regressive (AR) modelling; Magnitude Squared Coherence (MSC); Wavelet Coherence (WTC) using Physionet database, yielded a collection of huge feature set. A large number of these features may be inconsequential containing some excess and non-discriminative components that present excess burden in computation and loss of execution performance. So Hybrid Firefly and Particle Swarm Optimization (FFPSO) is directly used to optimise the raw ECG signal instead of extracting features using the above feature extraction techniques. Provided results in this paper show that, for the detection of MI class, the FFPSO algorithm with ANN gives 99.3% accuracy, sensitivity of 99.97%, and specificity of 98.7% on MIT-BIH database by including NSR database also. The proposed approach has shown that methods that are based on the feature optimization of the ECG signals are the perfect to diagnosis the condition of the heart patients. Copyright © 2017 Elsevier B.V. All rights reserved.
[Observations and significance of extrasystole in very young athletes].
Rossini, G; Mazzoli, M; Dalmastri, G; Crescimbeni, L; Berti, P; Arata, G; Losi, G; Martines, G
1982-01-01
80 very young football players (from 8 to 12) have been examined for three months by some clinical and instrumental cardiologic tests (starting E.C.G. and after graduated stresses on a football court). The starting E.C.G. showed variable extresystolic arrhythmias in 8 subjects, without any sure signs of a cardiopathy, to point out by deeper tests (such as polygraphic, echocardiographic test and rx heart teleradiography). The above-mentioned arrhythmias felt the effects of training variably, since they regressed in 6 cases, however two subjects needed a pharmacological intervention. They are still talking over the meaning to give to extrasystolic arrhythmias in very young people in evaluation of attitude to agonism and in programming training.
Funk, Marjorie; Fennie, Kristopher P; Stephens, Kimberly E; May, Jeanine L; Winkler, Catherine G; Drew, Barbara J
2017-02-01
Although continuous electrocardiographic (ECG) monitoring is ubiquitous in hospitals, monitoring practices are inconsistent. We evaluated implementation of American Heart Association practice standards for ECG monitoring on nurses' knowledge, quality of care, and patient outcomes. The PULSE (Practical Use of the Latest Standards of Electrocardiography) Trial was a 6-year multisite randomized clinical trial with crossover that took place in 65 cardiac units in 17 hospitals. We measured outcomes at baseline, time 2 after group 1 hospitals received the intervention, and time 3 after group 2 hospitals received the intervention. Measurement periods were 15 months apart. The 2-part intervention consisted of an online ECG monitoring education program and strategies to implement and sustain change in practice. Nurses' knowledge (N=3013 nurses) was measured by a validated 20-item online test, quality of care related to ECG monitoring (N=4587 patients) by on-site observation, and patient outcomes (mortality, in-hospital myocardial infarction, and not surviving a cardiac arrest; N=95 884 hospital admissions) by review of administrative, laboratory, and medical record data. Nurses' knowledge improved significantly immediately after the intervention in both groups but was not sustained 15 months later. For most measures of quality of care (accurate electrode placement, accurate rhythm interpretation, appropriate monitoring, and ST-segment monitoring when indicated), the intervention was associated with significant improvement, which was sustained 15 months later. Of the 3 patient outcomes, only in-hospital myocardial infarction declined significantly after the intervention and was sustained. Online ECG monitoring education and strategies to change practice can lead to improved nurses' knowledge, quality of care, and patient outcomes. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01269736. © 2017 American Heart Association, Inc.
Funk, Marjorie; Fennie, Kristopher P.; Stephens, Kimberly E.; May, Jeanine L.; Winkler, Catherine G.; Drew, Barbara J.
2017-01-01
Background Although continuous electrocardiographic (ECG) monitoring is ubiquitous in hospitals, monitoring practices are inconsistent. We evaluated implementation of American Heart Association practice standards for ECG monitoring on nurses’ knowledge, quality of care, and patient outcomes. Methods and Results The PULSE Trial was a 6-year multi-site randomized clinical trial with crossover that took place in 65 cardiac units in 17 hospitals. We measured outcomes at baseline, Time 2 after Group 1 hospitals received the intervention, and Time 3 after Group 2 hospitals received the intervention. Measurement periods were 15 months apart. The 2-part intervention consisted of an online ECG monitoring education program and strategies to implement and sustain change in practice. Nurses’ knowledge (N=3,013 nurses) was measured by a validated 20-item online test, quality of care related to ECG monitoring (N=4,587 patients) by on-site observation, and patient outcomes (mortality, in-hospital myocardial infarction, and not surviving a cardiac arrest) (N=95,884 hospital admissions) by review of administrative, laboratory, and medical record data. Nurses’ knowledge improved significantly immediately following the intervention in both groups, but was not sustained 15 months later. For most measures of quality of care (accurate electrode placement, accurate rhythm interpretation, appropriate monitoring, and ST-segment monitoring when indicated), the intervention was associated with significant improvement, which was sustained 15 months later. Of the 3 patient outcomes, only in-hospital myocardial infarction declined significantly after the intervention, and was sustained. Conclusions Online ECG monitoring education and strategies to change practice can lead to improved nurses’ knowledge, quality of care, and patient outcomes. PMID:28174175
Zhu, Bohui; Ding, Yongsheng; Hao, Kuangrong
2013-01-01
This paper presents a novel maximum margin clustering method with immune evolution (IEMMC) for automatic diagnosis of electrocardiogram (ECG) arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm. Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy. Compared with K-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias. PMID:23690875
Kwonjoon Lee; Kiseok Song; Taehwan Roh; Hoi-Jun Yoo
2016-08-01
The wrist patch-type ECG/APW sensor system is proposed for continuous and comprehensive monitoring of the patient's cardiovascular system. The wrist patch-type ECG/APW sensor system is consists of ECG/APW sensor, ECG/APW electrodes, and base station for real-time monitoring of the patient's status. The ECG/APW sensor and electrodes are composed of wrist patch, bandage-type ECG electrode and fabric APW electrode, respectively so that the patient's cardiovascular system can be continuously monitored in daily life with free hand-movement. Since the proposed wrist patchtype ECG/APW sensor simultaneously measures ECG/APW, the cardiac indicators, such as HR and PAT, can be extracted for comprehensive and accurate monitoring of the patient's cardiovascular system. The proposed wrist patch-type ECG/APW sensor system is successfully verified using the commercial PPG sensor (RP520) and demonstrated with the customized Android application on the smart phone.
Kim, Hanvit; Minh Phuong Nguyen; Se Young Chun
2017-07-01
Biometrics such as ECG provides a convenient and powerful security tool to verify or identify an individual. However, one important drawback of biometrics is that it is irrevocable. In other words, biometrics cannot be re-used practically once it is compromised. Cancelable biometrics has been investigated to overcome this drawback. In this paper, we propose a cancelable ECG biometrics by deriving a generalized likelihood ratio test (GLRT) detector from a composite hypothesis testing in randomly projected domain. Since it is common to observe performance degradation for cancelable biometrics, we also propose a guided filtering (GF) with irreversible guide signal that is a non-invertibly transformed signal of ECG authentication template. We evaluated our proposed method using ECG-ID database with 89 subjects. Conventional Euclidean detector with original ECG template yielded 93.9% PD1 (detection probability at 1% FAR) while Euclidean detector with 10% compressed ECG (1/10 of the original data size) yielded 90.8% PD1. Our proposed GLRT detector with 10% compressed ECG yielded 91.4%, which is better than Euclidean with the same compressed ECG. GF with our proposed irreversible ECG template further improved the performance of our GLRT with 10% compressed ECG up to 94.3%, which is higher than Euclidean detector with original ECG. Lastly, we showed that our proposed cancelable ECG biometrics practically met cancelable biometrics criteria such as efficiency, re-usability, diversity and non-invertibility.
Early electrocardiographic abnormalities in Trypanosoma cruzi-seropositive children.
de Andrade, A L; Zicker, F; Rassi, A; Rassi, A G; Oliveira, R M; Silva, S A; de Andrade, S S; Martelli, C M
1998-10-01
As part of a major epidemiologic study on Chagas' disease, we compared the prevalence of electrocardiographic (ECG) abnormalities among 141 school children 7-12 years of age and seropositive for Trypanosoma cruzi, and 282 age-, sex-, and school-matched seronegative children in an endemic area in Brazil. The prevalence of ECG abnormalities was 11.3% among seropositive children and 3.5% among seronegative children (odds ratio = 3.5, 95% confidence interval [CI] = 1.5-8.4). The prevalence rate of ECG alterations was 10.7% for seropositive males versus 8.9% for seropositive females. Complete right bundle branch block (CRBBB), which is highly suggestive of Chagas' disease cardiopathy, was diagnosed in nine (6.4%) seropositive children and in only one (0.3%) seronegative child (odds ratio = 18.5, 95% CI = 2.3-146.5, attributable fraction = 58.3%). Five incident new cases of CRBBB were diagnosed after a 36-month follow-up of seropositive children who were enrolled in an independent clinical field trial. No case of frequent and/or multifocal ventricular premature beats was found in the cohort of children. The surprisingly high frequency of early ECG abnormalities, which indicates a rapid evolution from infection to disease, suggests the existence of endemic areas with a particular accelerated disease progression that was not described before. Under such conditions, a public health chemotherapy program focusing on the treatment of young seropositive children would be recommended.
Sufi, Fahim; Khalil, Ibrahim
2009-04-01
With cardiovascular disease as the number one killer of modern era, Electrocardiogram (ECG) is collected, stored and transmitted in greater frequency than ever before. However, in reality, ECG is rarely transmitted and stored in a secured manner. Recent research shows that eavesdropper can reveal the identity and cardiovascular condition from an intercepted ECG. Therefore, ECG data must be anonymized before transmission over the network and also stored as such in medical repositories. To achieve this, first of all, this paper presents a new ECG feature detection mechanism, which was compared against existing cross correlation (CC) based template matching algorithms. Two types of CC methods were used for comparison. Compared to the CC based approaches, which had 40% and 53% misclassification rates, the proposed detection algorithm did not perform any single misclassification. Secondly, a new ECG obfuscation method was designed and implemented on 15 subjects using added noises corresponding to each of the ECG features. This obfuscated ECG can be freely distributed over the internet without the necessity of encryption, since the original features needed to identify personal information of the patient remain concealed. Only authorized personnel possessing a secret key will be able to reconstruct the original ECG from the obfuscated ECG. Distribution of the would appear as regular ECG without encryption. Therefore, traditional decryption techniques including powerful brute force attack are useless against this obfuscation.
NASA Astrophysics Data System (ADS)
Ma, Yaping; Xiao, Yegui; Wei, Guo; Sun, Jinwei
2016-01-01
In this paper, a multichannel nonlinear adaptive noise canceller (ANC) based on the generalized functional link artificial neural network (FLANN, GFLANN) is proposed for fetal electrocardiogram (FECG) extraction. A FIR filter and a GFLANN are equipped in parallel in each reference channel to respectively approximate the linearity and nonlinearity between the maternal ECG (MECG) and the composite abdominal ECG (AECG). A fast scheme is also introduced to reduce the computational cost of the FLANN and the GFLANN. Two (2) sets of ECG time sequences, one synthetic and one real, are utilized to demonstrate the improved effectiveness of the proposed nonlinear ANC. The real dataset is derived from the Physionet non-invasive FECG database (PNIFECGDB) including 55 multichannel recordings taken from a pregnant woman. It contains two subdatasets that consist of 14 and 8 recordings, respectively, with each recording being 90 s long. Simulation results based on these two datasets reveal, on the whole, that the proposed ANC does enjoy higher capability to deal with nonlinearity between MECG and AECG as compared with previous ANCs in terms of fetal QRS (FQRS)-related statistics and morphology of the extracted FECG waveforms. In particular, for the second real subdataset, the F1-measure results produced by the PCA-based template subtraction (TSpca) technique and six (6) single-reference channel ANCs using LMS- and RLS-based FIR filters, Volterra filter, FLANN, GFLANN, and adaptive echo state neural network (ESN a ) are 92.47%, 93.70%, 94.07%, 94.22%, 94.90%, 94.90%, and 95.46%, respectively. The same F1-measure statistical results from five (5) multi-reference channel ANCs (LMS- and RLS-based FIR filters, Volterra filter, FLANN, and GFLANN) for the second real subdataset turn out to be 94.08%, 94.29%, 94.68%, 94.91%, and 94.96%, respectively. These results indicate that the ESN a and GFLANN perform best, with the ESN a being slightly better than the GFLANN but about four times more computationally expensive than the GFLANN, which makes the GFLANN a good alternative for NI-FECG extraction.
Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System.
Li, Hongqiang; Yuan, Danyang; Wang, Youxi; Cui, Dianyin; Cao, Lu
2016-10-20
Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.
Lee, Kwang Jin; Lee, Boreom
2016-01-01
Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR. PMID:27376296
Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System
Li, Hongqiang; Yuan, Danyang; Wang, Youxi; Cui, Dianyin; Cao, Lu
2016-01-01
Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias. PMID:27775596
Lee, Kwang Jin; Lee, Boreom
2016-07-01
Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR.
Thomas, Robert Joseph; Mietus, Joseph E.; Peng, Chung-Kang; Gilmartin, Geoffrey; Daly, Robert W.; Goldberger, Ary L.; Gottlieb, Daniel J.
2007-01-01
Study Objectives: Complex sleep apnea is defined as sleep disordered breathing secondary to simultaneous upper airway obstruction and respiratory control dysfunction. The objective of this study was to assess the utility of an electrocardiogram (ECG)-based cardiopulmonary coupling technique to distinguish obstructive from central or complex sleep apnea. Design: Analysis of archived polysomnographic datasets. Setting: A laboratory for computational signal analysis. Interventions: None. Measurements and Results: The PhysioNet Sleep Apnea Database, consisting of 70 polysomnograms including single-lead ECG signals of approximately 8 hours duration, was used to train an ECG-based measure of autonomic and respiratory interactions (cardiopulmonary coupling) to detect periods of apnea and hypopnea, based on the presence of elevated low-frequency coupling (e-LFC). In the PhysioNet BIDMC Congestive Heart Failure Database (ECGs of 15 subjects), a pattern of “narrow spectral band” e-LFC was especially common. The algorithm was then applied to the Sleep Heart Health Study–I dataset, to select the 15 records with the highest amounts of broad and narrow spectral band e-LFC. The latter spectral characteristic seemed to detect not only periods of central apnea, but also obstructive hypopneas with a periodic breathing pattern. Applying the algorithm to 77 sleep laboratory split-night studies showed that the presence of narrow band e-LFC predicted an increased sensitivity to induction of central apneas by positive airway pressure. Conclusions: ECG-based spectral analysis allows automated, operator-independent characterization of probable interactions between respiratory dyscontrol and upper airway anatomical obstruction. The clinical utility of spectrographic phenotyping, especially in predicting failure of positive airway pressure therapy, remains to be more thoroughly tested. Citation: Thomas RJ; Mietus JE; Peng CK; Gilmartin G; Daly RW; Goldberger AL; Gottlieb DJ. Differentiating obstructive from central and complex sleep apnea using an automated electrocardiogram-based method. SLEEP 2007;30(12):1756-1769. PMID:18246985
Barrios, V; Calderón, A; Coca, A; González-Juanatey, J R; Sarríá, A; Rodríguez-Padial, L
2011-09-01
Despite its low sensitivity, the electrocardiogram (ECG) is the tool used the most in the daily practice for detection of left ventricular hypertrophy (LVH). This study has aimed to assess the impact of the computerized interpretation of the ECG on the diagnosis of LVH in the practical clinical setting. ELECTROPRES is a project based on a free access computer platform that permits an online interpretation of the electrocardiogram. It includes 19 different left LVH criteria previously validated by echocardiography in a substudy. We analyzed the data from the first 669 patients with essential arterial hypertension (ATH) included in the ELECTROPRES platform from 21 primary care centers in 9 of the 17 Spanish autonomous communities. Up to April 2010, a cohort of 669 hypertensive patients (51.7% women), with a mean age of 66.3±11.89 years, was analyzed. The mean evolution of the disease was 8 years, and the patients had been receiving an average of 2.4 antihypertensive agents. Systolic blood pressure was 139±17 mmHg and diastolic blood pressure 76±11. The ECG-known frequency of LVH was 3%. The prevalence of LVH increased up to 33.3% (P<0.001) with the ELECTROPRES platform. When all the criteria were independently examined, the Lewis index (R-I+S-III) and the Cornell product [(R-aVL+S-V3 (+6 for women)] were those in which the most cases of left ventricular hypertrophy were detected (24.8% and 13.3%, respectively). The Lewis index and the Cornell product were the criteria that detected more cases of left ventricular hypertrophy, regardless of the AHT stage and of the presence of cardiovascular complications. The ECG computerized reading (ELECTROPRES platform) significantly increases detection of left ventricular hypertrophy in a population of essential hypertense subjects compared to conventional detection with the ECG by the physician in the usual clinical practice setting. Copyright © 2011 Elsevier España, S.L. All rights reserved.
Tague, Lauren; Wiggs, Justin; Li, Qianxi; McCarter, Robert; Sherwin, Elizabeth; Weinberg, Jacqueline; Sable, Craig
2018-05-17
Left ventricular hypertrophy (LVH) is a common finding on pediatric electrocardiography (ECG) leading to many referrals for echocardiography (echo). This study utilizes a novel analytics tool that combines ECG and echo databases to evaluate ECG as a screening tool for LVH. SQL Server 2012 data warehouse incorporated ECG and echo databases for all patients from a single institution from 2006 to 2016. Customized queries identified patients 0-18 years old with LVH on ECG and an echo performed within 24 h. Using data visualization (Tableau) and analytic (Stata 14) software, ECG and echo findings were compared. Of 437,699 encounters, 4637 met inclusion criteria. ECG had high sensitivity (≥ 90%) but poor specificity (43%), and low positive predictive value (< 20%) for echo abnormalities. ECG performed only 11-22% better than chance (AROC = 0.50). 83% of subjects with LVH on ECG had normal left ventricle (LV) structure and size on echo. African-Americans with LVH were least likely to have an abnormal echo. There was a low correlation between V 6 R on ECG and echo-derived Z score of left ventricle diastolic diameter (r = 0.14) and LV mass index (r = 0.24). The data analytics client was able to mine a database of ECG and echo reports, comparing LVH by ECG and LV measurements and qualitative findings by echo, identifying an abnormal LV by echo in only 17% of cases with LVH on ECG. This novel tool is useful for rapid data mining for both clinical and research endeavors.
Scalable Telemonitoring Model in Cloud for Health Care Analysis
NASA Astrophysics Data System (ADS)
Sawant, Yogesh; Jayakumar, Naveenkumar, Dr.; Pawar, Sanket Sunil
2017-08-01
Telemonitoring model is health observations model that going to surveillance patients remotely. Telemonitoring model is suitable for patients to avoid high operating expense to get Emergency treatment. Telemonitoring gives the path for monitoring the medical device that generates a complete profile of patient’s health through assembling essential signs as well as additional health information. Telemonitoring model is relying on four differential modules which is capable to generate realistic synthetic electrocardiogram (ECG) signals. Telemonitoring model shows four categories of chronic disease: pulmonary state, diabetes, hypertension, as well as cardiovascular diseases. On the other hand, the results of this application model recommend facilitating despite of their nationality, socioeconomic grade, or age, patients observe amid tele-monitoring programs as well as the utilization of technologies. Patient’s multiple health status is shown in the result such as beat-to-beat variation in morphology and timing of the human ECG, including QT dispersion and R-peak amplitude modulation. This model will be utilized to evaluate biomedical signal processing methods that are utilized to calculate clinical information from the ECG.
Resting ECG findings in elite football players.
Bohm, Philipp; Ditzel, Roman; Ditzel, Heribert; Urhausen, Axel; Meyer, Tim
2013-01-01
The purpose of the study was to evaluate ECG abnormalities in a large sample of elite football players. Data from 566 elite male football players (57 of them of African origin) above 16 years of age were screened retrospectively (age: 20.9 ± 5.3 years; BMI: 22.9 ± 1.7 kg · m(-2), training history: 13.8 ± 4.7 years). The resting ECGs were analysed and classified according to the most current ECG categorisation of the European Society of Cardiology (ESC) (2010) and a classification of Pelliccia et al. (2000) in order to assess the impact of the new ESC-approach. According to the classification of Pelliccia, 52.5% showed mildly abnormal ECG patterns and 12% were classified as distinctly abnormal ECG patterns. According to the classification of the ESC, 33.7% showed 'uncommon ECG patterns'. Short-QT interval was the most frequent ECG pattern in this group (41.9%), followed by a shortened PR-interval (19.9%). When assessed with a QTc cut-off-point of 340 ms (instead of 360 ms), only 22.2% would have had 'uncommon ECG patterns'. Resting ECG changes amongst elite football players are common. Adjustment of the ESC criteria by adapting proposed time limits for the ECG (e.g. QTc, PR) should further reduce the rate of false-positive results.
Extended Kalman smoother with differential evolution technique for denoising of ECG signal.
Panigrahy, D; Sahu, P K
2016-09-01
Electrocardiogram (ECG) signal gives a lot of information on the physiology of heart. In reality, noise from various sources interfere with the ECG signal. To get the correct information on physiology of the heart, noise cancellation of the ECG signal is required. In this paper, the effectiveness of extended Kalman smoother (EKS) with the differential evolution (DE) technique for noise cancellation of the ECG signal is investigated. DE is used as an automatic parameter selection method for the selection of ten optimized components of the ECG signal, and those are used to create the ECG signal according to the real ECG signal. These parameters are used by the EKS for the development of the state equation and also for initialization of the parameters of EKS. EKS framework is used for denoising the ECG signal from the single channel. The effectiveness of proposed noise cancellation technique has been evaluated by adding white, colored Gaussian noise and real muscle artifact noise at different SNR to some visually clean ECG signals from the MIT-BIH arrhythmia database. The proposed noise cancellation technique of ECG signal shows better signal to noise ratio (SNR) improvement, lesser mean square error (MSE) and percent of distortion (PRD) compared to other well-known methods.
The effects of metronome breathing on the variability of autonomic activity measurements.
Driscoll, D; Dicicco, G
2000-01-01
Many chiropractors hypothesize that spinal manipulation affects the autonomic nervous system (ANS). However, the ANS responses to chiropractic manipulative therapy are not well documented, and more research is needed to support this hypothesis. This study represents a step toward the development of a reliable method by which to document that chiropractic manipulative therapy does affect the ANS by exploring the use of paced breathing as a way to reduce the inherent variability in ANS measurements. To examine the hypothesis that the variability of ANS measurements would be reduced if breathing were paced to a metronome at 12 breaths/min. The study was performed at Parker College Research Institute. Eight normotensive subjects were recruited from the student body and staff. Respiration frequency was measured through a strain gauge. A 3-lead electrocardiogram (ECG) was used to register the electric activity of the heart, and arterial tonometry monitors were used to record the left and right radial artery blood pressures. Signals were recorded on an IBM-compatible computer with a sampling frequency of 100 Hz. Normal breathing was used for the first 3 recordings, and breathing was paced to a metronome for the final 3 recordings at 12 breaths/min. Fourier analysis was performed on the beat-by-beat fluctuations of the ECG-determined R-R interval and systolic arterial pressure (SBP). Low-frequency fluctuations (LF; 0.04-0.15 Hz) reflected sympathetic activity, whereas high-frequency fluctuations (HF; 0.15-0.4 Hz) represented parasympathetic activity. Sympathovagal indices were determined from the ratio of the two bandwidths (LF/HF). The coefficient of variation (CV%) for autonomic parameters was calculated ([average/SD] x 100%) to compare breathing normally and breathing to a metronome with respect to variability. One-way analysis of variance was used to detect differences. A value of P < 0.05 was considered statistically significant; all results are presented as average +/- SD. Three male and 5 female normotensive subjects were studied. Metronome breathing did not produce any significant changes in blood pressure for the left and right radial arteries, heart rate, or pressure pulse transmission time. Breathing to a metronome increased ECG-HF power (0.25 +/- 0.07 vs 0.35 +/- 0.09, P < 0.04), decreased ECG-LF/HF (1.08 +/- 0.55 vs 0.57 +/- 0.35, P < 0.05), and reduced the CV% for ECG-LF (47.6% +/- 23.4% vs 23.8% +/- 14.6%, P < 0.03), ECG-HF (46.2% +/- 14.2% vs 25.8% +/- 17.0%, P < 0.03) and ECG-LF/HF (50.1% +/- 27.6% vs 23.4% +/- 12.3%, P < 0.03) in comparison with normal breathing. Metronome breathing increased the left and right radial artery SBP-HF fluctuations (left, 0.11 +/- 0.05 vs 0.30 +/- 0.16, P < 0.007; right, 0.09 +/- 0.05 vs 0.27 +/- 0.15, P < 0.008) and decreased the SBP-LF/HF components (left, 3.42 +/- 2.36 vs 1.14 +/- 0.88, P > 0.03; right, 3.08 +/- 1.77 vs 1.20 +/- 0.93, P < 0.02). Metronome breathing did not significantly alter the CV% for SBP-HF, SBP-LF, and SBP-LF/HF. Metronome breathing increased parasympathetic activity, as evidenced by augmented HF power in the ECG and SBP data. The variability (CV%) of ECG-determined ANS measurements was significantly reduced with paced breathing at 12 breaths/min, but no significant reductions were observed for the SBP-determined ANS measurements. These findings indicate that ECG data are more sensitive than SBP data for future clinical trials.
Neic, Aurel; Campos, Fernando O; Prassl, Anton J; Niederer, Steven A; Bishop, Martin J; Vigmond, Edward J; Plank, Gernot
2017-10-01
Anatomically accurate and biophysically detailed bidomain models of the human heart have proven a powerful tool for gaining quantitative insight into the links between electrical sources in the myocardium and the concomitant current flow in the surrounding medium as they represent their relationship mechanistically based on first principles. Such models are increasingly considered as a clinical research tool with the perspective of being used, ultimately, as a complementary diagnostic modality. An important prerequisite in many clinical modeling applications is the ability of models to faithfully replicate potential maps and electrograms recorded from a given patient. However, while the personalization of electrophysiology models based on the gold standard bidomain formulation is in principle feasible, the associated computational expenses are significant, rendering their use incompatible with clinical time frames. In this study we report on the development of a novel computationally efficient reaction-eikonal (R-E) model for modeling extracellular potential maps and electrograms. Using a biventricular human electrophysiology model, which incorporates a topologically realistic His-Purkinje system (HPS), we demonstrate by comparing against a high-resolution reaction-diffusion (R-D) bidomain model that the R-E model predicts extracellular potential fields, electrograms as well as ECGs at the body surface with high fidelity and offers vast computational savings greater than three orders of magnitude. Due to their efficiency R-E models are ideally suitable for forward simulations in clinical modeling studies which attempt to personalize electrophysiological model features.
NASA Astrophysics Data System (ADS)
Neic, Aurel; Campos, Fernando O.; Prassl, Anton J.; Niederer, Steven A.; Bishop, Martin J.; Vigmond, Edward J.; Plank, Gernot
2017-10-01
Anatomically accurate and biophysically detailed bidomain models of the human heart have proven a powerful tool for gaining quantitative insight into the links between electrical sources in the myocardium and the concomitant current flow in the surrounding medium as they represent their relationship mechanistically based on first principles. Such models are increasingly considered as a clinical research tool with the perspective of being used, ultimately, as a complementary diagnostic modality. An important prerequisite in many clinical modeling applications is the ability of models to faithfully replicate potential maps and electrograms recorded from a given patient. However, while the personalization of electrophysiology models based on the gold standard bidomain formulation is in principle feasible, the associated computational expenses are significant, rendering their use incompatible with clinical time frames. In this study we report on the development of a novel computationally efficient reaction-eikonal (R-E) model for modeling extracellular potential maps and electrograms. Using a biventricular human electrophysiology model, which incorporates a topologically realistic His-Purkinje system (HPS), we demonstrate by comparing against a high-resolution reaction-diffusion (R-D) bidomain model that the R-E model predicts extracellular potential fields, electrograms as well as ECGs at the body surface with high fidelity and offers vast computational savings greater than three orders of magnitude. Due to their efficiency R-E models are ideally suitable for forward simulations in clinical modeling studies which attempt to personalize electrophysiological model features.
Empirical mode decomposition of the ECG signal for noise removal
NASA Astrophysics Data System (ADS)
Khan, Jesmin; Bhuiyan, Sharif; Murphy, Gregory; Alam, Mohammad
2011-04-01
Electrocardiography is a diagnostic procedure for the detection and diagnosis of heart abnormalities. The electrocardiogram (ECG) signal contains important information that is utilized by physicians for the diagnosis and analysis of heart diseases. So good quality ECG signal plays a vital role for the interpretation and identification of pathological, anatomical and physiological aspects of the whole cardiac muscle. However, the ECG signals are corrupted by noise which severely limit the utility of the recorded ECG signal for medical evaluation. The most common noise presents in the ECG signal is the high frequency noise caused by the forces acting on the electrodes. In this paper, we propose a new ECG denoising method based on the empirical mode decomposition (EMD). The proposed method is able to enhance the ECG signal upon removing the noise with minimum signal distortion. Simulation is done on the MIT-BIH database to verify the efficacy of the proposed algorithm. Experiments show that the presented method offers very good results to remove noise from the ECG signal.
Liang, Lijun; Hu, Yao; Liu, Hao; Li, Xiaojiu; Li, Jin; He, Yin
2017-04-01
In order to reduce the mortality rate of cardiovascular disease patients effectively, improve the electrocardiogram (ECG) accuracy of signal acquisition, and reduce the influence of motion artifacts caused by the electrodes in inappropriate location in the clothing for ECG measurement, we in this article present a research on the optimum place of ECG electrodes in male clothing using three-lead monitoring methods. In the 3-lead ECG monitoring clothing for men we selected test points. Comparing the ECG and power spectrum analysis of the acquired ECG signal quality of each group of points, we determined the best location of ECG electrodes in the male monitoring clothing. The electrode motion artifacts caused by improper location had been significantly improved when electrodes were put in the best position of the clothing for men. The position of electrodes is crucial for ECG monitoring clothing. The stability of the acquired ECG signal could be improved significantly when electrodes are put at optimal locations.
Artifacts and noise removal in electrocardiograms using independent component analysis.
Chawla, M P S; Verma, H K; Kumar, Vinod
2008-09-26
Independent component analysis (ICA) is a novel technique capable of separating independent components from electrocardiogram (ECG) complex signals. The purpose of this analysis is to evaluate the effectiveness of ICA in removing artifacts and noise from ECG recordings. ICA is applied to remove artifacts and noise in ECG segments of either an individual ECG CSE data base file or all files. The reconstructed ECGs are compared with the original ECG signal. For the four special cases discussed, the R-Peak magnitudes of the CSE data base ECG waveforms before and after applying ICA are also found. In the results, it is shown that in most of the cases, the percentage error in reconstruction is very small. The results show that there is a significant improvement in signal quality, i.e. SNR. All the ECG recording cases dealt showed an improved ECG appearance after the use of ICA. This establishes the efficacy of ICA in elimination of noise and artifacts in electrocardiograms.
Challenges of ECG monitoring and ECG interpretation in dialysis units.
Poulikakos, Dimitrios; Malik, Marek
Patients on hemodialysis (HD) suffer from high cardiovascular morbidity and mortality due to high rates of coronary artery disease and arrhythmias. Electrocardiography (ECG) is often performed in the dialysis units as part of routine clinical assessment. However, fluid and electrolyte changes have been shown to affect all ECG morphologies and intervals. ECG interpretation thus depends on the time of the recording in relation to the HD session. In addition, arrhythmias during HD are common, and dialysis-related ECG artifacts mimicking arrhythmias have been reported. Studies using advanced ECG analyses have examined the impact of the HD procedure on selected repolarization descriptors and heart rate variability indices. Despite the challenges related to the impact of the fluctuant fluid and electrolyte status on conventional and advanced ECG parameters, further research in ECG monitoring during dialysis has the potential to provide clinically meaningful and practically useful information for diagnostic and risk stratification purposes. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.
Fernlund, E; Liuba, P; Carlson, J; Platonov, P G; Schlegel, T T
2016-01-01
The conventional ECG is commonly used to screen for hypertrophic cardiomyopathy (HCM), but up to 25% of adults and possibly larger percentages of children with HCM have no distinctive abnormalities on the conventional ECG, whereas 5 to 15% of healthy young athletes do. Recently, a 5-min resting advanced 12-lead ECG test ("A-ECG score") showed superiority to pooled criteria from the strictly conventional ECG in correctly identifying adult HCM. The purpose of this study was to evaluate whether in children and young adults, A-ECG scoring could detect echocardiographic HCM associated with the MYBPC3 genetic mutation with greater sensitivity than conventional ECG criteria and distinguish healthy young controls and athletes from persons with MYBPC3 HCM with greater specificity. Five-minute 12-lead ECGs were obtained from 15 young patients (mean age 13.2years, range 0-30years) with MYBPC3 mutation and phenotypic HCM. The conventional and A-ECG results of these patients were compared to those of 198 healthy children and young adults (mean age 13.2, range 1month-30years) with unremarkable echocardiograms, and to those of 36 young endurance-trained athletes, 20 of whom had athletic (physiologic) left ventricular hypertrophy. Compared with commonly used, age-specific pooled criteria from the conventional ECG, a retrospectively generated A-ECG score incorporating results from just 2 derived vectorcardiographic parameters (spatial QRS-T angle and the change in the vectorcardiographic QRS azimuth angle from the second to the third eighth of the QRS interval) increased the sensitivity of ECG for identifying MYBPC3 HCM from 46% to 87% (p<0.05). Use of the same score also demonstrated superior specificity in a set of 198 healthy controls (94% vs. 87% for conventional ECG criteria; p<0.01) including in a subset of 36 healthy, young endurance-trained athletes (100% vs. 69% for conventional ECG criteria, p<0.001). In children and young adults, a 2-parameter 12-lead A-ECG score is retrospectively significantly more sensitive and specific than pooled, age-specific conventional ECG criteria for detecting MYBPC3-HCM and in distinguishing such patients from healthy controls, including endurance-trained athletes. Copyright © 2016 Elsevier Inc. All rights reserved.
Christov, Ivaylo I; Iliev, Georgi L
2005-03-15
A specific problem using the public access defibrillators (PADs) arises at the railway stations. Some countries as Germany, Austria, Switzerland, Norway and Sweden are using AC railroad net power-supply system with rated 16.7 Hz frequency modulated from 15.69 Hz to 17.36 Hz. The power supply frequency contaminates the electrocardiogram (ECG). It is difficult to be suppressed or eliminated due to the fact that it considerably overlaps the frequency spectra of the ECG. The interference impedes the automated decision of the PADs whether a patient should be (or should not be) shocked. The aim of this study is the suppression of the 16.7 Hz interference generated by the power supply of the railway systems. Software solution using adaptive filtering method was proposed for 16.7 Hz interference suppression. The optimal performance of the filter is achieved, embedding a reference channel in the PADs to record the interference. The method was tested with ECGs from AHA database. The method was tested with patients of normal sinus rhythms, symptoms of tachycardia and ventricular fibrillation. Simulated interference with frequency modulation from 15.69 Hz to 17.36 Hz changing at a rate of 2% per second was added to the ECGs, and then processed by the suggested adaptive filtering. The method totally suppresses the noise with no visible distortions of the original signals. The proposed adaptive filter for noise suppression generated by the power supply of the railway systems has a simple structure requiring a low level of computational resources, but a good reference signal as well.
State of the art techniques for preservation and reuse of hard copy electrocardiograms.
Lobodzinski, Suave M; Teppner, Ulrich; Laks, Michael
2003-01-01
Baseline examinations and periodic reexaminations in longitudinal population studies, together with ongoing surveillance for morbidity and mortality, provide unique opportunities for seeking ways to enhance the value of electrocardiography (ECG) as an inexpensive and noninvasive tool for prognosis and diagnosis. We used newly developed optical ECG waveform recognition (OEWR) technique capable of extracting raw waveform data from legacy hard copy ECG recording. Hardcopy ECG recordings were scanned and processed by the OEWR algorithm. The extracted ECG datasets were formatted into a newly proposed, vendor-neutral, ECG XML data format. Oracle database was used as a repository for ECG records in XML format. The proposed technique for XML encapsulation of OEWR processed hard copy records resulted in an efficient method for inclusion of paper ECG records into research databases, thus providing their preservation, reuse and accession.
Wearable ECG Based on Impulse-Radio-Type Human Body Communication.
Wang, Jianqing; Fujiwara, Takuya; Kato, Taku; Anzai, Daisuke
2016-09-01
Human body communication (HBC) provides a promising physical layer for wireless body area networks (BANs) in healthcare and medical applications, because of its low propagation loss and high security characteristics. In this study, we have developed a wearable electrocardiogram (ECG) which employs impulse radio (IR)-type HBC technology for transmitting vital signals on the human body in a wearable BAN scenario. The HBC-based wearable ECG has two excellent features. First, the wideband performance of the IR scheme contributed to very low radiation power so that the transceiver is easy to satisfy the extremely weak radio laws, which does not need a license. This feature can provide big convenience in the use and spread of the wearable ECG. Second, the realization of common use of sensing and transmitting electrodes based on time sharing and capacitive coupling largely simplified the HBC-based ECG structure and contributed to its miniaturization. To verify the validity of the HBC-based ECG, we evaluated its communication performance and ECG acquisition performance. The measured bit error rate, smaller than 10 -3 at 1.25 Mb/s, showed a good physical layer communication performance, and the acquired ECG waveform and various heart-rate variability parameters in time and frequency domains exhibited good agreement with a commercially available radio-frequency ECG and a Holter ECG. These results sufficiently showed the validity and feasibility of the HBC-based ECG for healthcare applications. This should be the first time to have realized a real-time ECG transmission by using the HBC technology.
Kim, Chul-Hee; Ko, Kwan-Ho; Park, Seong-Wook; Park, Joong-Yeol; Lee, Ki-Up
2010-01-01
Background/Aims Resting electrocardiogram (ECG) abnormalities have been strongly associated with cardiovascular disease mortality. Little is known, however, about the association between individual components of metabolic syndrome and ECG abnormalities, especially in Asian populations. Methods We examined clinical and laboratory data from 31,399 subjects (age 20 to 89 years) who underwent medical check-ups. ECG abnormalities were divided into minor and major abnormalities based on Novacode criteria. Ischemic ECG findings were separately identified and analyzed. Results The overall prevalence rates of ECG abnormalities were significantly higher in subjects with than in those without metabolic syndrome (p < 0.01). Ischemic ECG was strongly associated with metabolic syndrome in all age groups of both sexes, except for younger women. In multiple logistic regression analysis, metabolic syndrome was independently associated with ischemic ECG (odds ratio, 2.30 [2.04 to 2.62]; p < 0.01), after adjusting for sex, age, smoking, and family history of cardiovascular disease. Of the metabolic syndrome components, hyperglycemia in younger subjects and hypertension in elderly subjects were major factors for ischemic ECG changes, whereas hypertriglyceridemia was not an independent risk factor in any age group. The association between ischemic ECG findings and central obesity was weaker in women than in men. Conclusions Metabolic syndrome was strongly associated with ECG abnormalities, especially ischemic ECG findings, in Koreans. The association between each component of metabolic syndrome and ECG abnormalities varied according to age and sex. PMID:20526391
Are ECG abnormalities in Noonan syndrome characteristic for the syndrome?
Raaijmakers, R; Noordam, C; Noonan, J A; Croonen, E A; van der Burgt, C J A M; Draaisma, J M T
2008-12-01
Of all patients with Noonan syndrome, 50-90% have one or more congenital heart defects. The most frequent occurring are pulmonary stenosis (PS) and hypertrophic cardiomyopathy. The electrocardiogram (ECG) of a patient with Noonan syndrome often shows a characteristic pattern, with a left axis deviation, abnormal R/S ratio over the left precordium, and an abnormal Q wave. The objective of this study was to determine if these ECG characteristics are an independent feature of the Noonan syndrome or if they are related to the congenital heart defect. A cohort study was performed with 118 patients from two university hospitals in the United States and in The Netherlands. All patients were diagnosed with definite Noonan syndrome and had had an ECG and echocardiography. Sixty-nine patients (58%) had characteristic abnormalities of the ECG. In the patient group without a cardiac defect (n = 21), ten patients had a characteristic ECG abnormality. There was no statistical relationship between the presence of a characteristic ECG abnormality and the presence of a cardiac defect (p = 0.33). Patients with hypertrophic cardiomyopathy had more ECG abnormalities in total (p = 0.05), without correlation with a specific ECG abnormality. We conclude that the ECG features in patients with Noonan syndrome are characteristic for the syndrome and are not related to a specific cardiac defect. An ECG is very useful in the diagnosis of Noonan syndrome; every child with a Noonan phenotype should have an ECG and echocardiogram for evaluation.
Methods for Improving the Diagnosis of a Brugada ECG Pattern.
Gottschalk, Byron H; Garcia-Niebla, Javier; Anselm, Daniel D; Glover, Benedict; Baranchuk, Adrian
2016-03-01
Brugada syndrome (BrS) is an inherited channelopathy that predisposes individuals to malignant arrhythmias and can lead to sudden cardiac death. The condition is characterized by two electrocardiography (ECG) patterns: the type-1 or "coved" ECG and the type-2 or "saddleback" ECG. Although the type-1 Brugada ECG pattern is diagnostic for the condition, the type-2 Brugada ECG pattern requires differential diagnosis from conditions that produce a similar morphology. In this article, we present a case that is suspicious but not diagnostic for BrS and discuss the application of ECG methodologies for increasing or decreasing suspicion for a diagnosis of BrS. © 2015 Wiley Periodicals, Inc.
Experimental characterization and analysis of the BITalino platforms against a reference device.
Batista, Diana; Silva, Hugo; Fred, Ana
2017-07-01
Low-cost hardware platforms for biomedical engineering are becoming increasingly available, which empower the research community in the development of new projects in a wide range of areas related with physiological data acquisition. Building upon previous work by our group, this work compares the quality of the data acquired by means of two different versions of the multimodal physiological computing platform BITalino, with a device that can be considered a reference. We acquired data from 5 sensors, namely Accelerometry (ACC), Electrocardiography (ECG), Electroencephalography (EEG), Electrodermal Activity (EDA) and Electromyography (EMG). Experimental evaluation shows that ACC, ECG and EDA data are highly correlated with the reference in what concerns the raw waveforms. When compared by means of their commonly used features, EEG and EMG data are also quite similar across the different devices.
A biotechnological T-shirt monitors the patient's heart during hemodialysis.
Lacquaniti, Antonio; Donato, Valentina; Lucisano, Silvia; Buemi, Antoine; Buemi, Michele
2012-01-01
Uremic patients are characterized by a "pro-arrhythmic substrate." Arrhythmia appearance during hemodialysis (HD) is an unexpected event with a high incidence of mortality and morbidity and difficult to record in patients repeatedly checked using electrocardiogram (ECG). Furthermore the carrying out of this important examination by classical devices during HD is uncomfortable and sometimes stressful for the patient. It may be very useful to monitor the patient's cardiac activity during the whole HD session. We tried to overcome these difficulties using Whealthy(®) (Wearable Health Care System), a wearable system in a T-shirt composed of conductors and piezoresistive materials, integrated to form fibers and threads connected to tissular sensors, electrodes, and connectors. ECG and pneumographic impedance signals are acquired by the electrodes in the tissue, and the data are registered by a small computer and transmitted via GPRS or Bluetooth.
Wolff-Parkinson-White (WPW) syndrome: the detection of delta wave in an electrocardiogram (ECG).
Mahamat, Hassan Adam; Jacquir, Sabir; Khalil, Cliff; Laurent, Gabriel; Binczak, Stephane
2016-08-01
The delta wave remains an important indicator to diagnose the WPW syndrome. In this paper, a new method of detection of delta wave in an ECG signal is proposed. Firstly, using the continuous wavelet transform, the P wave, the QRS complex and the T wave are detected, then their durations are computed after determination of the boundary location (onsets and offsets of the P, QRS and T waves). Secondly, the PR duration, the QRS duration and the upstroke of the QRS complex are used to determine the presence or absence of the delta wave. This algorithm has been tested on the Physionel database (ptbdb) in order to evaluate its robustness. It has been applied to clinical signals from patients affected by WPW syndrome. This method can provide assistance to practitioners in order to detect the WPW syndrome.
Feasibility of in utero telemetric fetal ECG monitoring in a lamb model.
Hermans, Bart; Lewi, Liesbeth; Jani, Jacques; De Buck, Frederik; Deprest, Jan; Puers, Robert
2008-01-01
If fetal ECG (fECG) devices could be miniaturized sufficiently, one could consider their implantation at the time of fetal surgery to allow permanent monitoring of the fetus and timely intervention in the viable period. We set up an experiment to evaluate the feasibility of in utero direct fECG monitoring and telemetric transmission using a small implantable device in a lamb model. A 2-lead miniature ECG sensor (volume 1.9 cm(3); weight 3.9 g) was subcutaneously implanted in 2 fetal lambs at 122 days gestation (range 119-125; term 145 days). The ECG sensor can continuously register and transmit fECG. The signal is captured by an external receiving antenna taped to the maternal abdominal wall. We developed dedicated software running on a commercial laptop for on-line analysis of the transmitted fECG signal. This was a noninterventional study, i.e. daily readings of the fECG signal were done without clinical consequences to the observations. fECG could be successfully registered, transmitted by telemetry and analyzed from the moment of implantation till term birth in one case (24 days). In the second case, unexplained in utero fetal death occurred 12 days after implantation. In this subject, agonal fECG changes were recorded. An implanted miniature (<2 ml) ECG sensor can be used to retrieve, process and transmit continuously a qualitative fECG signal in third-trimester fetal lambs. The telemetric signal could be picked up by an external antenna located within a 20-cm range. In this experiment, this was achieved through taping the external receiver to the maternal abdomen. Any acquired signal could be transmitted to a commercially available laptop that could perform on-line analysis of the signal. (c) 2008 S. Karger AG, Basel.
Female False Positive Exercise Stress ECG Testing - Fact Verses Fiction.
Fitzgerald, Benjamin T; Scalia, William M; Scalia, Gregory M
2018-03-07
Exercise stress testing is a well validated cardiovascular investigation. Accuracy for treadmill stress electrocardiograph (ECG) testing has been documented at 60%. False positive stress ECGs (exercise ECG changes with non-obstructive disease on anatomical testing) are common, especially in women, limiting the effectiveness of the test. This study investigates the incidence and predictors of false positive stress ECG findings, referenced against stress echocardiography (SE) as a standard. Stress echocardiography was performed using the Bruce treadmill protocol. False positive stress ECG tests were defined as greater than 1mm of ST depression on ECG during exertion, without pain, with a normal SE. Potential causes for false positive tests were recorded before the test. Three thousand consecutive negative stress echocardiograms (1036 females, 34.5%) were analysed (age 59+/-14 years. False positive (F+) stress ECGs were documented in 565/3000 tests (18.8%). F+ stress ECGs were equally prevalent in females (194/1036, 18.7%) and males (371/1964, 18.9%, p=0.85 for the difference). Potential causes (hypertension, left ventricular hypertrophy, known coronary disease, arrhythmia, diabetes mellitus, valvular heart disease) were recorded in 36/194 (18.6%) of the female F+ ECG tests and 249/371 (68.2%) of the male F+ ECG tests (p<0.0001 for the difference). These data suggest that F+ stress ECG tests are frequent and equally common in women and men. However, most F+ stress ECGs in men can be predicted before the test, while most in women cannot. Being female may be a risk factor in itself. These data reinforce the value of stress imaging, particularly in women. Copyright © 2018 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). All rights reserved.
Development of a portable wireless system for bipolar concentric ECG recording
NASA Astrophysics Data System (ADS)
Prats-Boluda, G.; Ye-Lin, Y.; Bueno Barrachina, J. M.; Senent, E.; Rodriguez de Sanabria, R.; Garcia-Casado, J.
2015-07-01
Cardiovascular diseases (CVDs) remain the biggest cause of deaths worldwide. ECG monitoring is a key tool for early diagnosis of CVDs. Conventional monitors use monopolar electrodes resulting in poor spatial resolution surface recordings and requiring extensive wiring. High-spatial resolution surface electrocardiographic recordings provide valuable information for the diagnosis of a wide range of cardiac abnormalities, including infarction and arrhythmia. The aim of this work was to develop and test a wireless recording system for acquiring high spatial resolution ECG signals, based on a flexible tripolar concentric electrode (TCE) without cable wiring or external reference electrode which would make more comnfortable its use in clinical practice. For this, a portable, wireless sensor node for analogue conditioning, digitalization and transmission of a bipolar concentric ECG signal (BC-ECG) using a TCE and a Mason-likar Lead-I ECG (ML-Lead-I ECG) signal was developed. Experimental results from a total of 32 healthy volunteers showed that the ECG fiducial points in the BC-ECG signals, recorded with external and internal reference electrode, are consistent with those of simultaneous ML-Lead-I ECG. No statistically significant difference was found in either signal amplitude or morphology, regardless of the reference electrode used, being the signal-to-noise similar to that of ML-Lead-I ECG. Furthermore, it has been observed that BC-ECG signals contain information that could not available in conventional records, specially related to atria activity. The proposed wireless sensor node provides non-invasive high-local resolution ECG signals using only a TCE without additional wiring, which would have great potential in medical diagnosis of diseases such as atrial or ventricular fibrillations or arrhythmias that currently require invasive diagnostic procedures (catheterization).
Bedside identification of patients at risk for PVC-induced cardiomyopathy: Is ECG useful?
Garster, Noelle C; Henrikson, Charles A
2017-07-01
Premature ventricular complexes (PVCs) are an underrecognized cause of cardiomyopathy. Standard 12-lead electrocardiogram (ECG) has potential to direct attention toward at-risk patients. We performed a single-center, retrospective chart review of 1,240 patients who completed ECG and Holter monitoring at Oregon Health and Science University Hospital between January 1, 2011 and December 31, 2013 to investigate the relationship of PVC frequency on ECG with burden on Holter. Primary outcome measures included PVC quantity on ECG, mean PVC quantity on Holter, and percentage of total beats on Holter recorded as PVCs. High PVC burden was defined as ≥10% of total beats. Weighted mean percentages of total beats on Holter monitor recorded as PVCs were calculated for 0, 1, 2, and ≥3 PVCs on ECG and found to be 1.4% (n = 1,128), 3.5% (n = 32), 4.3% (n = 25), and 16.6% (n = 55), respectively, which represent statistically significant differences (P < 0.001). The positive predictive value of at least three PVCs on ECG for ≥10% PVC Holter burden was 58%. Negative predictive value for 0 PVCs on ECG was 98%. The sensitivity and specificity of ECG to identify high PVC burden on Holter was 72% and 93.6%, respectively, when utilizing a positive ECG result as one PVC or more, and 44% and 98.9%, respectively, with ≥3 PVCs on ECG. The positive likelihood ratio corresponding to ≥3 PVCs on ECG was 40. These findings demonstrate that the number of PVCs on ECG can be utilized for quick bedside estimation of high PVC burden. © 2017 Wiley Periodicals, Inc.
Rawshani, Nina; Rawshani, Araz; Gelang, Carita; Herlitz, Johan; Bång, Angela; Andersson, Jan-Otto; Gellerstedt, Martin
2017-12-01
In the assessment of patients with chest pain, there is support for the use of pre-hospital ECG in the literature and in the care guidelines. Using propensity score methods, we aim to examine whether the mere acquisition of a pre-hospital ECG among patients with chest pain affects the outcome (30-day mortality). The association between pre-hospital ECG and 30-day mortality was studied in the overall cohort (n=13151), as well as in the one-to-one matched cohort with 2524 patients not examined with pre-hospital ECG and 2524 patients examined with pre-hospital ECG. In the overall cohort, 21% (n=2809) did not undergo an ECG tracing in the pre-hospital setting. Among those who had pain during transport, 14% (n=1159) did not undergo a pre-hospital ECG while 32% (n=1135) of those who did not have pain underwent an ECG tracing. In the overall cohort, the OR for 30-day mortality in patients who had a pre-hospital ECG, as compared with those who did not, was 0.63 (95% CI 0.05-0.79; p<0.001). In the matched cohort, the OR was 0.65 (95% CI 0.49-0.85; p<0.001). Using the propensity score, in the overall cohort, the corresponding HR was 0.65 (95% CI 0.58-0.74). Using propensity score methods, we provide real-world data demonstrating that the adjusted risk of death was considerably lower among the cases in whoma pre-hospital ECG was used. The PH-ECG is underused among patients with chest discomfort and the mere acquisition of a pre-hospital ECG may reduce mortality. Copyright © 2017 Elsevier B.V. All rights reserved.
Physician attitudes about prehospital 12-lead ECGs in chest pain patients.
Brainard, Andrew H; Froman, Philip; Alarcon, Maria E; Raynovich, Bill; Tandberg, Dan
2002-01-01
The prehospital 12-lead electrocardiogram (ECG) has become a standard of care. For the prehospital 12-lead ECG to be useful clinically, however, cardiologists and emergency physicians (EP) must view the test as useful. This study measured physician attitudes about the prehospital 12-lead ECG. This study tested the hypothesis that physicians had "no opinion" regarding the prehospital 12-lead ECG. An anonymous survey was conducted to measure EP and cardiologist attitudes toward prehospital 12-lead ECGs. Hypothesis tests against "no opinion" (VAS = 50 mm) were made with 95% confidence intervals (CIs), and intergroup comparisons were made with the Student's t-test. Seventy-one of 87 (81.6%) surveys were returned. Twenty-five (67.6%) cardiologists responded and 45 (90%) EPs responded. Both groups of physicians viewed prehospital 12-lead ECGs as beneficial (mean = 69 mm; 95% CI = 65-74 mm). All physicians perceived that ECGs positively influence preparation of staff (mean = 63 mm; 95% CI = 60-72 mm) and that ECGs transmitted to hospitals would be beneficial (mean = 66 mm; 95% CI = 60-72 mm). Cardiologists had more favorable opinions than did EPs. The ability of paramedics to interpret ECGs was not seen as important (mean = 50 mm; 95% CI = 43-56 mm). The justifiable increase in field time was perceived to be 3.2 minutes (95% CI = 2.7-3.8 minutes), with 23 (32.8%) preferring that it be done on scene, 46 (65.7%) during transport, and one (1.4%) not at all. Prehospital 12-lead ECGs generally are perceived as worthwhile by cardiologists and EPs. Cardiologists have a higher opinion of the value and utility of field ECGs. Since the reduction in mortality from the 12-lead ECG is small, it is likely that positive physician attitudes are attributable to other factors.
NASA Astrophysics Data System (ADS)
Ragulskaya, Maria; Obridko, Vladimir; Samsonov, Sergey; Vitaliy, Vishnevskey; Grigoryev, Pavel; Valeriy, Pipin; Khabarova, Olga
We discuss the results of the long-term telecommunicative biogeophysical monitoring "Geliomed" (2003-2010). The purpose is to explore the effects of spatial and temporal variations in space weather and climatic factors on the human health state. The monitoring is carried out simultaneously at the different geographical areas that covers the different latitudes. The project developed in the joint collaboration the Ukrainian National Academy of Science and the Russian Academy of Science. The experiment carried out simultaneously in Moscow, Yakutsk, Kiev and Simferopol. The principal components of the experiment can be summarized as follows: 1. Equipments and data gathering methods are the same for all the scientific cen-ters which are involved in experiment. Research centers working with the same equipment and using the same protocols with on-line registration of current data on same portal server (http//geliomed.immsp.kiev.ua) 2. The groups of patients involved in the program are kept the same for the whole observational period of time. 3. The daily registered parameters in-clude: psycho-emotional tests and 1-st lead ECG (contain 25 000 measurements for the whole period), arterial pressure (100 000 measurements), variability cardiac contraction (25000 mea-surements), electric conduction of bioactive points on skin (more than 500 000 measurements for the whole period ). 4. The every patient in the monitoring group is examined at the 4 functional states. Registration is done at rest, after standard psychology test, Roufiet test, and after 10 min relax. 5. The data of the ECG measurements are analyzed in the phase space constructed from the signal and its derivative. 6. The results time series were compared with daily values of space weather and geomagnetic parameters. Results. In the all monitoring centers all the patients involved in the monitoring show the same type of changes in the cardiac activity parameters during an isolated magnetic storm. Such a change of the ECG parameters occurs nearly simultaneously for all the centers. The higher latitude, the greater amplitude of the ECG parameters change. The properties of the detected phenomena can be summarized as follows: -The dynamics of adaptation programs changes during the storm. The maximum amplitude of change is observed for the healthy patients. -The number of none-typical ECG beats increase; -There are no clear evidences for variations of RR intervals during geomagnetic storms. -Man are more sensitive to magnetic storms, while endogenous rhythms predominate for females; Additionally, we find, that the embedding of ECG time series in 3D phase space can be considered as a mix of a few states. At the rest, the occurrence of the basic ECG state compare to additional ones is about 8:2. The occurrence of the basic state increases after the stress. Thus, the external stress may change the relative disorder of the system. To understand the origin of the standard cardio-cycle changes we reconstruct of the dynamical model of the individual cardiac beat. The reconstruction reveals that the typical evolution of the cardiac rhythm includes the drift of attractor in the embedding space and the sudden change between a few basic patterns of attractor. However one of pattern is always dominating. These several pattern of ECG beat attractor can be ascribed to a several states of the system. Qualitatively, the nonlinear ECG dynamics is defined by the stationary points, which are inside into Q and T waves. Conclusions: many-year telecommunication heliomedical monitoring in different lat-itudes showed, that space and geophysical factor act as a training factor for the adaptation-resistant member of the population. It serve as a channel for rejection of nonviable members of the population, synchronize the total populations rhythms, create conditions for generation of new information in the process of evolution adaptation of biological systems in general.
Sparse Matrix for ECG Identification with Two-Lead Features.
Tseng, Kuo-Kun; Luo, Jiao; Hegarty, Robert; Wang, Wenmin; Haiting, Dong
2015-01-01
Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods.
Koplay, M; Kizilca, O; Cimen, D; Sivri, M; Erdogan, H; Guvenc, O; Oc, M; Oran, B
2016-11-01
The goal of this study was to investigate the radiation dose and diagnostic efficacy of cardiac computed tomography angiography (CCTA) using prospective ECG-gated high-pitch dual-source computed tomography (DSCT) in the diagnosis of congenital cardiovascular abnormalities in pediatric population. One hundred five pediatric patients who were clinically diagnosed with congenital heart disease with suspected extracardiac vascular abnormalities were included in the study. All CCTAs were performed on a 128×2-section DSCT scanner. CCTA findings were compared with surgical and/or conventional cardiac angiography findings. Dose-length product (DLP) and effective doses (ED) were calculated for each patient. Patients were divided into 4 groups by age, and ED and DLP values were compared among groups. The image quality was evaluated using a five-point scale. CCTA showed 173 abnormalities in 105 patients. There were 2 patients with false positive and 3 with false negative findings. The sensitivity and specificity of CCTA were 98.3% and 99.9%, respectively. The positive predictive value and negative predictive value of CCT were 98.9% and 99.9%, respectively. The average DLP and ED values were 15.6±9.6 (SD) mGy.cm and 0.34±0.10 (SD) mSv, respectively. The mean image quality score was 4.8±0.5 (SD) in all patients. The inter-observer agreement for the image quality scores was good (κ=0.80). CCTA is an excellent imaging modality for evaluation of cardiovascular abnormalities and provides excellent image quality with very low radiation exposure when low-dose prospective ECG-triggered high-pitch DSCT is used. Copyright © 2016 Editions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.
Shiotani, Masataka; Ogawa, Masato; Watanabe, Ryo; Shinohara, Tamotsu
2012-01-01
Multi detector-row computed tomography with 64 data acquisition systems are widely used for coronary CT angiography with an electrocardiograph (ECG) gated helical scan (HS). Step and shoot with ECG gated non-helical scan (snap shot pulse: SSP) could reduce exposure dose but banding artifact-like discontinuity was observed between adjacent slabs on volume rendering (VR) and curved planner reconstruction (CPR). Therefore, we investigated the factors that influence continuity of VR and CPR images by calculating image properties of Z-axis direction of slab. The observer performance studies were performed for evaluating continuity of simulated blood vessels of VR and CPR images at simulated heart rates: 50, 55, 57 and 60 beat per minute (bpm). As a result, the value of SD at both slab edges in SSP were 20.5% lower than middle part of slab and differences of value of SD were up to 4.4 between adjacent slab edges. Slice thickness of both slab edges were 20.3% thinner than that of the peripheral part of slab. At the border of the adjacent slab, the position of the simulated blood vessel was shifted. VR images of SSP at 57 bpm was indicated as the highest score and HS was significantly superior to SSP at 55 and 60 bpm (p<0.05). In CPR images, there were no significant differences at all simulated heart rates. In conclusion, we considered that VR images of SSP were influenced heart rates except 57 bpm (resonance case) and there was little difference of visibility for discontinuity of both CPR images obtained by SSP and HS.
New ideas for teaching electrocardiogram interpretation and improving classroom teaching content.
Zeng, Rui; Yue, Rong-Zheng; Tan, Chun-Yu; Wang, Qin; Kuang, Pu; Tian, Pan-Wen; Zuo, Chuan
2015-01-01
Interpreting an electrocardiogram (ECG) is not only one of the most important parts of diagnostics but also one of the most difficult areas to teach. Owing to the abstract nature of the basic theoretical knowledge of the ECG, its scattered characteristics, and tedious and difficult-to-remember subject matter, teaching how to interpret ECGs is as difficult for teachers to teach as it is for students to learn. In order to enable medical students to master basic knowledge of ECG interpretation skills in a limited teaching time, we modified the content used for traditional ECG teaching and now propose a new ECG teaching method called the "graphics-sequence memory method." A prospective randomized controlled study was designed to measure the actual effectiveness of ECG learning by students. Two hundred students were randomly placed under a traditional teaching group and an innovative teaching group, with 100 participants in each group. The teachers in the traditional teaching group utilized the traditional teaching outline, whereas the teachers in the innovative teaching group received training in line with the proposed teaching method and syllabus. All the students took an examination in the final semester by analyzing 20 ECGs from real clinical cases and submitted their ECG reports. The average ECG reading time was 32 minutes for the traditional teaching group and 18 minutes for the innovative teaching group. The average ECG accuracy results were 43% for the traditional teaching group and 77% for the innovative teaching group. Learning to accurately interpret ECGs is an important skill in the cardiac discipline, but the ECG's mechanisms are intricate and the content is scattered. Textbooks tend to make the students feel confused owing to the restrictions of the length and the format of the syllabi, apart from many other limitations. The graphics-sequence memory method was found to be a useful method for ECG teaching.
... A telltale abnormality — called a type 1 Brugada ECG pattern — is detected by an electrocardiogram (ECG) test. Brugada syndrome is much more common in ... syndrome is an abnormal pattern on an electrocardiogram (ECG) called a type 1 Brugada ECG pattern. You ...
Image-guided optimization of the ECG trace in cardiac MRI.
Barnwell, James D; Klein, J Larry; Stallings, Cliff; Sturm, Amanda; Gillespie, Michael; Fine, Jason; Hyslop, W Brian
2012-03-01
Improper electrocardiogram (ECG) lead placement resulting in suboptimal gating may lead to reduced image quality in cardiac magnetic resonance imaging (CMR). A patientspecific systematic technique for rapid optimization of lead placement may improve CMR image quality. A rapid 3 dimensional image of the thorax was used to guide the realignment of ECG leads relative to the cardiac axis of the patient in forty consecutive adult patients. Using our novel approach and consensus reading of pre- and post-correction ECG traces, seventy-three percent of patients had a qualitative improvement in their ECG tracings, and no patient had a decrease in quality of their ECG tracing following the correction technique. Statistically significant improvement was observed independent of gender, body mass index, and cardiac rhythm. This technique provides an efficient option to improve the quality of the ECG tracing in patients who have a poor quality ECG with standard techniques.
Identifying UMLS concepts from ECG Impressions using KnowledgeMap
Denny, Joshua C.; Spickard, Anderson; Miller, Randolph A; Schildcrout, Jonathan; Darbar, Dawood; Rosenbloom, S. Trent; Peterson, Josh F.
2005-01-01
Electrocardiogram (ECG) impressions represent a wealth of medical information for potential decision support and drug-effect discovery. Much of this information is inaccessible to automated methods in the free-text portion of the ECG report. We studied the application of the KnowledgeMap concept identifier (KMCI) to map Unified Medical Language System (UMLS) concepts from ECG impressions. ECGs were processed by KMCI and the results scored for accuracy by multiple raters. Reviewers also recorded unidentified concepts through the scoring interface. Overall, KMCI correctly identified 1059 out of 1171 concepts for a recall of 0.90. Precision, indicating the proportion of ECG concepts correctly identified, was 0.94. KMCI was particularly effective at identifying ECG rhythms (330/333), perfusion changes (65/66), and noncardiac medical concepts (11/11). In conclusion, KMCI is an effective method for mapping ECG impressions to UMLS concepts. PMID:16779029
NASA Astrophysics Data System (ADS)
Agung, Mochammad Anugrah; Basari
2017-02-01
Electrocardiogram (ECG) devices measure electrical activity of the heart muscle to determine heart conditions. ECG signal quality is the key factor in determining the diseases of the heart. This paper presents the design of 3-lead acquistion on single channel wireless ECG device developed on AD8232 chip platform using microcontroller. To make the system different from others, monopole antenna 2.4 GHz is used in order to send and receive ECG signal. The results show that the system still can receive ECG signal up to 15 meters by line of sight (LOS) condition. The shape of ECG signals is precisely similar with the expected signal, although some delays occur between two consecutive pulses. For further step, the system will be applied with on-body antenna in order to investigate body to body communication that will give variation in connectivity from the others.
Multiscale permutation entropy analysis of electrocardiogram
NASA Astrophysics Data System (ADS)
Liu, Tiebing; Yao, Wenpo; Wu, Min; Shi, Zhaorong; Wang, Jun; Ning, Xinbao
2017-04-01
To make a comprehensive nonlinear analysis to ECG, multiscale permutation entropy (MPE) was applied to ECG characteristics extraction to make a comprehensive nonlinear analysis of ECG. Three kinds of ECG from PhysioNet database, congestive heart failure (CHF) patients, healthy young and elderly subjects, are applied in this paper. We set embedding dimension to 4 and adjust scale factor from 2 to 100 with a step size of 2, and compare MPE with multiscale entropy (MSE). As increase of scale factor, MPE complexity of the three ECG signals are showing first-decrease and last-increase trends. When scale factor is between 10 and 32, complexities of the three ECG had biggest difference, entropy of the elderly is 0.146 less than the CHF patients and 0.025 larger than the healthy young in average, in line with normal physiological characteristics. Test results showed that MPE can effectively apply in ECG nonlinear analysis, and can effectively distinguish different ECG signals.
Multi-purpose ECG telemetry system.
Marouf, Mohamed; Vukomanovic, Goran; Saranovac, Lazar; Bozic, Miroslav
2017-06-19
The Electrocardiogram ECG is one of the most important non-invasive tools for cardiac diseases diagnosis. Taking advantage of the developed telecommunication infrastructure, several approaches that address the development of telemetry cardiac devices were introduced recently. Telemetry ECG devices allow easy and fast ECG monitoring of patients with suspected cardiac issues. Choosing the right device with the desired working mode, signal quality, and the device cost are still the main obstacles to massive usage of these devices. In this paper, we introduce design, implementation, and validation of a multi-purpose telemetry system for recording, transmission, and interpretation of ECG signals in different recording modes. The system consists of an ECG device, a cloud-based analysis pipeline, and accompanied mobile applications for physicians and patients. The proposed ECG device's mechanical design allows laypersons to easily record post-event short-term ECG signals, using dry electrodes without any preparation. Moreover, patients can use the device to record long-term signals in loop and holter modes, using wet electrodes. In order to overcome the problem of signal quality fluctuation due to using different electrodes types and different placements on subject's chest, customized ECG signal processing and interpretation pipeline is presented for each working mode. We present the evaluation of the novel short-term recorder design. Recording of an ECG signal was performed for 391 patients using a standard 12-leads golden standard ECG and the proposed patient-activated short-term post-event recorder. In the validation phase, a sample of validation signals followed peer review process wherein two experts annotated the signals in terms of signal acceptability for diagnosis.We found that 96% of signals allow detecting arrhythmia and other signal's abnormal changes. Additionally, we compared and presented the correlation coefficient and the automatic QRS delineation results of both short-term post-event recorder and 12-leads golden standard ECG recorder. The proposed multi-purpose ECG device allows physicians to choose the working mode of the same device according to the patient status. The proposed device was designed to allow patients to manage the technical requirements of both working modes. Post-event short-term ECG recording using the proposed design provide physicians reliable three ECG leads with direct symptom-rhythm correlation.
A novel biometric authentication approach using ECG and EMG signals.
Belgacem, Noureddine; Fournier, Régis; Nait-Ali, Amine; Bereksi-Reguig, Fethi
2015-05-01
Security biometrics is a secure alternative to traditional methods of identity verification of individuals, such as authentication systems based on user name and password. Recently, it has been found that the electrocardiogram (ECG) signal formed by five successive waves (P, Q, R, S and T) is unique to each individual. In fact, better than any other biometrics' measures, it delivers proof of subject's being alive as extra information which other biometrics cannot deliver. The main purpose of this work is to present a low-cost method for online acquisition and processing of ECG signals for person authentication and to study the possibility of providing additional information and retrieve personal data from an electrocardiogram signal to yield a reliable decision. This study explores the effectiveness of a novel biometric system resulting from the fusion of information and knowledge provided by ECG and EMG (Electromyogram) physiological recordings. It is shown that biometrics based on these ECG/EMG signals offers a novel way to robustly authenticate subjects. Five ECG databases (MIT-BIH, ST-T, NSR, PTB and ECG-ID) and several ECG signals collected in-house from volunteers were exploited. A palm-based ECG biometric system was developed where the signals are collected from the palm of the subject through a minimally intrusive one-lead ECG set-up. A total of 3750 ECG beats were used in this work. Feature extraction was performed on ECG signals using Fourier descriptors (spectral coefficients). Optimum-Path Forest classifier was used to calculate the degree of similarity between individuals. The obtained results from the proposed approach look promising for individuals' authentication.
Digitization of Electrocardiogram From Telemetry Prior to In-hospital Cardiac Arrest: A Pilot Study.
Attin, Mina; Wang, Lu; Soroushmehr, S M Reza; Lin, Chii-Dean; Lemus, Hector; Spadafore, Maxwell; Najarian, Kayvan
2016-03-01
Analyzing telemetry electrocardiogram (ECG) data over an extended period is often time-consuming because digital records are not widely available at hospitals. Investigating trends and patterns in the ECG data could lead to establishing predictors that would shorten response time to in-hospital cardiac arrest (I-HCA). This study was conducted to validate a novel method of digitizing paper ECG tracings from telemetry systems in order to facilitate the use of heart rate as a diagnostic feature prior to I-HCA. This multicenter study used telemetry to investigate full-disclosure ECG papers of 44 cardiovascular patients obtained within 1 hr of I-HCA with initial rhythms of pulseless electrical activity and asystole. Digital ECGs were available for seven of these patients. An algorithm to digitize the full-disclosure ECG papers was developed using the shortest path method. The heart rate was measured manually (averaging R-R intervals) for ECG papers and automatically for digitized and digital ECGs. Significant correlations were found between manual and automated measurements of digitized ECGs (p < .001) and between digitized and digital ECGs (p < .001). Bland-Altman methods showed bias = .001 s, SD = .0276 s, lower and upper 95% limits of agreement for digitized and digital ECGs = .055 and -.053 s, and percentage error = 0.22%. Root mean square (rms), percentage rms difference, and signal to noise ratio values were in acceptable ranges. The digitization method was validated. Digitized ECG provides an efficient and accurate way of measuring heart rate over an extended period of time. © The Author(s) 2015.
Ishikawa, Joji; Ishikawa, Shizukiyo; Kario, Kazuomi
2015-03-01
We attempted to evaluate whether subjects who exhibit prolonged corrected QT (QTc) interval (≥440 ms in men and ≥460 ms in women) on ECG, with and without ECG-diagnosed left ventricular hypertrophy (ECG-LVH; Cornell product, ≥244 mV×ms), are at increased risk of stroke. Among the 10 643 subjects, there were a total of 375 stroke events during the follow-up period (128.7±28.1 months; 114 142 person-years). The subjects with prolonged QTc interval (hazard ratio, 2.13; 95% confidence interval, 1.22-3.73) had an increased risk of stroke even after adjustment for ECG-LVH (hazard ratio, 1.71; 95% confidence interval, 1.22-2.40). When we stratified the subjects into those with neither a prolonged QTc interval nor ECG-LVH, those with a prolonged QTc interval but without ECG-LVH, and those with ECG-LVH, multivariate-adjusted Cox proportional hazards analysis demonstrated that the subjects with prolonged QTc intervals but not ECG-LVH (1.2% of all subjects; incidence, 10.7%; hazard ratio, 2.70, 95% confidence interval, 1.48-4.94) and those with ECG-LVH (incidence, 7.9%; hazard ratio, 1.83; 95% confidence interval, 1.31-2.57) had an increased risk of stroke events, compared with those with neither a prolonged QTc interval nor ECG-LVH. In conclusion, prolonged QTc interval was associated with stroke risk even among patients without ECG-LVH in the general population. © 2014 American Heart Association, Inc.
Extraction of ECG signal with adaptive filter for hearth abnormalities detection
NASA Astrophysics Data System (ADS)
Turnip, Mardi; Saragih, Rijois. I. E.; Dharma, Abdi; Esti Kusumandari, Dwi; Turnip, Arjon; Sitanggang, Delima; Aisyah, Siti
2018-04-01
This paper demonstrates an adaptive filter method for extraction ofelectrocardiogram (ECG) feature in hearth abnormalities detection. In particular, electrocardiogram (ECG) is a recording of the heart's electrical activity by capturing a tracingof cardiac electrical impulse as it moves from the atrium to the ventricles. The applied algorithm is to evaluate and analyze ECG signals for abnormalities detection based on P, Q, R and S peaks. In the first phase, the real-time ECG data is acquired and pre-processed. In the second phase, the procured ECG signal is subjected to feature extraction process. The extracted features detect abnormal peaks present in the waveform. Thus the normal and abnormal ECG signal could be differentiated based on the features extracted.
Electrocardiogram findings in emergency department patients with syncope.
Quinn, James; McDermott, Daniel
2011-07-01
To determine the sensitivity and specificity of the San Francisco Syncope Rule (SFSR) electrocardiogram (ECG) criteria for determining cardiac outcomes and to define the specific ECG findings that are the most important in patients with syncope. A consecutive cohort of emergency department (ED) patients with syncope or near syncope was considered. The treating emergency physicians assessed 50 predictor variables, including an ECG and rhythm assessment. For the ECG assessment, the physicians were asked to categorize the ECG as normal or abnormal based on any changes that were old or new. They also did a separate rhythm assessment and could use any of the ECGs or available monitoring strips, including prehospital strips, when making this assessment. All patients were followed up to determine a broad composite study outcome. The final ECG criterion for the SFSR was any nonsinus rhythm or new ECG changes. In this specific study, the initial assessments in the database were used to determine only cardiac-related outcomes (arrhythmia, myocardial infarction, structural, sudden death) based on set criteria, and the authors determined the sensitivity and specificity of the ECG criteria for cardiac outcomes only. All ECGs classified as "abnormal" by the study criteria were compared to the official cardiology reading to determine specific findings on the ECG. Univariate and multivariate analysis were used to determine important specific ECG and rhythm findings. A total of 684 consecutive patients were considered, with 218 having positive ECG criteria and 42 (6%) having important cardiac outcomes. ECG criteria predicted 36 of 42 patients with cardiac outcomes, with a sensitivity of 86% (95% confidence interval [CI] = 71% to 94%), a specificity of 70% (95% CI = 66% to 74%), and a negative predictive value of 99% (95% CI = 97% to 99%). Regarding specific ECG findings, any nonsinus rhythm from any source and any left bundle conduction problem (i.e., any left bundle branch block, left anterior fascicular block, left posterior fascicular block, or QRS widening) were 2.5 and 3.5 times more likely associated with significant cardiac outcomes. The ECG criteria from the SFSR are relatively simple, and if used correctly can help predict which patients are at risk of cardiac outcomes. Furthermore, any left bundle branch block conduction problems or any nonsinus rhythms found during the ED stay should be especially concerning for physicians caring for patients presenting with syncope. © 2011 by the Society for Academic Emergency Medicine.
Electrocardiogram interpretation and arrhythmia management: a primary and secondary care survey.
Begg, Gordon; Willan, Kathryn; Tyndall, Keith; Pepper, Chris; Tayebjee, Muzahir
2016-05-01
There is increasing desire among service commissioners to treat arrhythmia in primary care. Accurate interpretation of the electrocardiogram (ECG) is fundamental to this. ECG interpretation has previously been shown to vary widely but there is little recent data. To examine the interpretation of ECGs in primary and secondary care. A cross-sectional survey of participants' interpretation of six ECGs and hypothetical management of patients based on those ECGs, at primary care educational events, and a cardiology department in Leeds. A total of 262 primary care clinicians and 20 cardiology clinicians were surveyed via questionnaire. Answers were compared with expert electrophysiologist opinion. In primary care, abnormal ECGs were interpreted as normal by 23% of responders. ST elevation and prolonged QT were incorrectly interpreted as normal by 1% and 22%, respectively. In cardiology, abnormal ECGs were interpreted as normal by 3%. ECG provision and interpretation remains inconsistent in both primary and secondary care. Primary care practitioners are less experienced and less confident with ECG interpretation than cardiologists, and require support in this area. © British Journal of General Practice 2016.
FastICA peel-off for ECG interference removal from surface EMG.
Chen, Maoqi; Zhang, Xu; Chen, Xiang; Zhu, Mingxing; Li, Guanglin; Zhou, Ping
2016-06-13
Multi-channel recording of surface electromyographyic (EMG) signals is very likely to be contaminated by electrocardiographic (ECG) interference, specifically when the surface electrode is placed on muscles close to the heart. A novel fast independent component analysis (FastICA) based peel-off method is presented to remove ECG interference contaminating multi-channel surface EMG signals. Although demonstrating spatial variability in waveform shape, the ECG interference in different channels shares the same firing instants. Utilizing the firing information estimated from FastICA, ECG interference can be separated from surface EMG by a "peel off" processing. The performance of the method was quantified with synthetic signals by combining a series of experimentally recorded "clean" surface EMG and "pure" ECG interference. It was demonstrated that the new method can remove ECG interference efficiently with little distortion to surface EMG amplitude and frequency. The proposed method was also validated using experimental surface EMG signals contaminated by ECG interference. The proposed FastICA peel-off method can be used as a new and practical solution to eliminating ECG interference from multichannel EMG recordings.
Design Document. EKG Interpretation Program.
ERIC Educational Resources Information Center
Webb, Sandra M.
This teaching plan is designed to assist nursing instructors assigned to advanced medical surgical nursing courses in acquainting students with the basic skills needed to perform electrocardiographic (ECG or EKG) interpretations. The first part of the teaching plan contains a statement of purpose; audience recommendations; a flow chart detailing…
2010-10-27
This practical, pocket-book approach to ECG interpretation accompanies the well-known text Making Sense of the ECG, by the same authors. It is also designed to be used alone to test knowledge of ECG interpretation and to make clinical decisions based on presented scenarios.
2011-02-10
This practical pocket-book approach to electrocardiogram (ECG) interpretation accompanies Making sense of the eCg by the same authors. it is also designed to be used alone to test knowledge of ECG interpretation and to make clinical decisions based on presented scenarios.
The Development of a Portable ECG Monitor Based on DSP
NASA Astrophysics Data System (ADS)
Nan, CHI Jian; Tao, YAN Yan; Meng Chen, LIU; Li, YANG
With the advent of global information, researches of Smart Home system are in the ascendant, the ECG real-time detection, and wireless transmission of ECG become more useful. In order to achieve the purpose we developed a portable ECG monitor which achieves the purpose of cardiac disease remote monitoring, and will be used in the physical and psychological disease surveillance in smart home system, we developed this portable ECG Monitor, based on the analysis of existing ECG Monitor, using TMS320F2812 as the core controller, which complete the signal collection, storage, processing, waveform display and transmission.
Govindan, R B; Kota, Srinivas; Al-Shargabi, Tareq; Massaro, An N; Chang, Taeun; du Plessis, Adre
2016-09-01
Electroencephalogram (EEG) signals are often contaminated by the electrocardiogram (ECG) interference, which affects quantitative characterization of EEG. We propose null-coherence, a frequency-based approach, to attenuate the ECG interference in EEG using simultaneously recorded ECG as a reference signal. After validating the proposed approach using numerically simulated data, we apply this approach to EEG recorded from six newborns receiving therapeutic hypothermia for neonatal encephalopathy. We compare our approach with an independent component analysis (ICA), a previously proposed approach to attenuate ECG artifacts in the EEG signal. The power spectrum and the cortico-cortical connectivity of the ECG attenuated EEG was compared against the power spectrum and the cortico-cortical connectivity of the raw EEG. The null-coherence approach attenuated the ECG contamination without leaving any residual of the ECG in the EEG. We show that the null-coherence approach performs better than ICA in attenuating the ECG contamination without enhancing cortico-cortical connectivity. Our analysis suggests that using ICA to remove ECG contamination from the EEG suffers from redistribution problems, whereas the null-coherence approach does not. We show that both the null-coherence and ICA approaches attenuate the ECG contamination. However, the EEG obtained after ICA cleaning displayed higher cortico-cortical connectivity compared with that obtained using the null-coherence approach. This suggests that null-coherence is superior to ICA in attenuating the ECG interference in EEG for cortico-cortical connectivity analysis. Copyright © 2016 Elsevier B.V. All rights reserved.
[ECG for non-competitive sports in childhood: strengths and disputes].
Poggi, Elena; Giannattasio, Alessandro; Bolloli, Sara; Beccaria, Andrea; Mezzano, Paola; Rocca, Paola; Del Vecchio, Cecilia
2016-11-01
Sport is very important for health promotion and conservation. Active lifestyle and regular exercise reduce cardiovascular disease incidence. The Italian Ministry of Health issued the Law Decree no. 243 (10/18/2014) concerning "guidelines for certification about non-competitive sports" to promote safety in sports. This regulation defines the activities for which a certificate is required, the professional actors involved and the clinical exams to be performed according to the patient's health status. In particular, the Law Decree recommends to perform an electrocardiogram (ECG) "at least once in a lifetime", introducing much greater news into pediatric practice. We proposed a survey evaluating frequency of ECG implementation for non-competitive sports and cardiovascular diseases incidence was administered to 7 Ligurian pediatricians. The number of ECG/year for pediatrician increased from 10 ECG/year to 50 ECG/year with an indication of suitability to non-competitive sports. One case of QT prolongation and 2 cases of type 1 Brugada ECG pattern were diagnosed. In addition, 3 patients had an atrial septal defect and 3 children had a ventricular septal defect. Forty-three percent of the pediatricians considered useful performing the ECG. ECG in children has enhanced the positive effects on the community health. However, it remains to be defined in agreement with scientific societies the age at which to perform ECG, the sports for which ECG is required and the cost-benefit ratio for the National Health System and families.
One-Dimensional Signal Extraction Of Paper-Written ECG Image And Its Archiving
NASA Astrophysics Data System (ADS)
Zhang, Zhi-ni; Zhang, Hong; Zhuang, Tian-ge
1987-10-01
A method for converting paper-written electrocardiograms to one dimensional (1-D) signals for archival storage on floppy disk is presented here. Appropriate image processing techniques were employed to remove the back-ground noise inherent to ECG recorder charts and to reconstruct the ECG waveform. The entire process consists of (1) digitization of paper-written ECGs with an image processing system via a TV camera; (2) image preprocessing, including histogram filtering and binary image generation; (3) ECG feature extraction and ECG wave tracing, and (4) transmission of the processed ECG data to IBM-PC compatible floppy disks for storage and retrieval. The algorithms employed here may also be used in the recognition of paper-written EEG or EMG and may be useful in robotic vision.
Pit-a-Pat: A Smart Electrocardiogram System for Detecting Arrhythmia.
Park, Juyoung; Lee, Kuyeon; Kang, Kyungtae
2015-10-01
Electrocardiogram (ECG) telemonitoring is one of the most promising applications of medical telemetry. However, previous approaches to ECG telemonitoring have largely relied on public databases of ECG results. In this article we propose a smart ECG system called Pit-a-Pat, which extracts features from ECG signals and detects arrhythmia. It is designed to run on an Android™ (Google, Mountain View, CA) device, without requiring modifications to other software. We implemented the Pit-a-Pat system using a commercial ECG device, and the experimental results demonstrate the effectiveness and accuracy of Pit-a-Pat for monitoring the ECG signal and analyzing the cardiac activity of a mobile patient. The proposed system allows monitoring of cardiac activity with automatic analysis, thereby providing a convenient, inexpensive, and ubiquitous adjunct to personal healthcare.
[The relationship of ECG and pregnancy outcome of older pregnant woman in late pregnancy].
Zhao, Xiao-Qin; Wang, Chun-Guang; Song, Yu-Xia; Jiao, Hong
2014-01-01
To observe the changes of electrocardiogram (ECG) and pregnancy outcome of the late pregnancy women. Late pregnancy women were divided into two groups by age: over 35 group and under 35 group. The incidence of abnormal electrocardiogram was recorded when the patients were subjected to routine ECG examination. Then the pregnancy, delivery outcome and if there's low birth weight newborn were recorded later. The incidence of abnormal ECG in over 35 group was significantly higher than that in under 35 group (P < 0.05). And the incidence of ST segment changes, arrhythmia in the group of former was higher than that in the group of latter (P < 0.05). Among the different type of arrhythmia, the incidence of sinus bradycardia and ventricular premature beat in the group of former were higher than those in the group of latter (P < 0.05). But the incidence of sinus tachycardia in the former group was obviously lower than that in the latter group (P < 0.05). The incidence of pregnancy loss in over 35 with abnormal ECG group was significantly higher than that in under 35 with normal or abnormal ECG groups (P < 0.05). The incidence of premature birth in over 35 with abnormal ECG group was significantly higher than that in over 35 with normal ECG group (P < 0.05). The incidence of low body weight in over 35 with abnormal ECG group was significantly higher than that in under 35 with normal ECG group (P < 0.05). The late pregnancy women with the age of over 35 are more likely to have ECG abnormalities, such as arrhythmia, myocardial ischemia and so on. The older pregnant women with abnormal ECG easily suffer from pregnancy losing, premature birth and having a low birth weight baby.
Differences in alarm events between disposable and reusable electrocardiography lead wires.
Albert, Nancy M; Murray, Terri; Bena, James F; Slifcak, Ellen; Roach, Joel D; Spence, Jackie; Burkle, Alicia
2015-01-01
Disposable electrocardiographic lead wires (ECG-LWs) may not be as durable as reusable ones. To examine differences in alarm events between disposable and reusable ECG-LWs. Two cardiac telemetry units were randomized to reusable ECG-LWs, and 2 units alternated between disposable and reusable ECG-LWs for 4 months. A remote monitoring team, blinded to ECG-LW type, assessed frequency and type of alarm events by using total counts and rates per 100 patient days. Event rates were compared by using generalized linear mixed-effect models for differences and noninferiority between wire types. In 1611 patients and 9385.5 patient days of ECG monitoring, patient characteristics were similar between groups. Rates of alarms for no telemetry, leads fail, or leads off were lower in disposable ECG-LWs (adjusted relative risk [95% CI], 0.71 [0.53-0.96]; noninferiority P < .001; superiority P = .03) and monitoring (artifact) alarms were significantly noninferior (adjusted relative risk [95% CI]: 0.88, [0.62-1.24], P = .02; superiority P = .44). No between-group differences existed in false or true crisis alarms. Disposable ECG-LWs were noninferior to reusable ECG-LWs for all false-alarm events (N [rate per 100 patient days], disposable 2029 [79.1] vs reusable 6673 [97.9]; adjusted relative risk [95% CI]: 0.81 [0.63-1.06], P = .002; superiority P = .12.) Disposable ECG-LWs with patented push-button design had superior performance in reducing alarms created by no telemetry, leads fail, or leads off and significant noninferiority in all false-alarm rates compared with reusable ECG-LWs. Fewer ECG alarms may save nurses time, decrease alarm fatigue, and improve patient safety. ©2015 American Association of Critical-Care Nurses.
Punn, Rajesh; Hanisch, Debra; Motonaga, Kara S; Rosenthal, David N; Ceresnak, Scott R; Dubin, Anne M
2016-02-01
Cardiac resynchronization therapy indications and management are well described in adults. Echocardiography (ECHO) has been used to optimize mechanical synchrony in these patients; however, there are issues with reproducibility and time intensity. Pediatric patients add challenges, with diverse substrates and limited capacity for cooperation. Electrocardiographic (ECG) methods to assess electrical synchrony are expeditious but have not been extensively studied in children. We sought to compare ECHO and ECG CRT optimization in children. Prospective, pediatric, single-center cross-over trial comparing ECHO and ECG optimization with CRT. Patients were assigned to undergo either ECHO or ECG optimization, followed for 6 months, and crossed-over to the other assignment for another 6 months. ECHO pulsed-wave tissue Doppler and 12-lead ECG were obtained for 5 VV delays. ECG optimization was defined as the shortest QRSD and ECHO optimization as the lowest dyssynchrony index. ECHOs/ECGs were interpreted by readers blinded to optimization technique. After each 6 month period, these data were collected: ejection fraction, velocimetry-derived cardiac index, quality of life, ECHO-derived stroke distance, M-mode dyssynchrony, study cost, and time. Outcomes for each optimization method were compared. From June 2012 to December 2013, 19 patients enrolled. Mean age was 9.1 ± 4.3 years; 14 (74%) had structural heart disease. The mean time for optimization was shorter using ECG than ECHO (9 ± 1 min vs. 68 ± 13 min, P < 0.01). Mean cost for charges was $4,400 ± 700 less for ECG. No other outcome differed between groups. ECHO optimization of synchrony was not superior to ECG optimization in this pilot study. ECG optimization required less time and cost than ECHO optimization. © 2015 Wiley Periodicals, Inc.
The effect of sport on computerized electrocardiogram measurements in college athletes.
Gademan, Maaike G J; Uberoi, Abhimanyu; Le, Vy-Van; Mandic, Sandra; van Oort, Eddy R; Myers, Jonathan; Froelicher, Victor F
2012-02-01
Broad criteria for abnormal electrocardiogram (ECG) findings, requiring additional testing, have been recommended for preparticipation exams (PPE) of athletes. As these criteria have not considered the sport in which athletes participate, we examined the effect of sports on the computerized ECG measurements obtained in college athletes. During the Stanford 2007 PPE, computerized 12-lead ECGs (Schiller AG) were obtained in 641 athletes (350 male/291 female, age 19.5 ± 2 years). Athletes were engaged in 22 different sports and were grouped into 16 categories: baseball/softball, basketball, crew, crosscountry, fencing, field events, football linemen, football other positions, golf, gymnastics, racquet sports, sailing, track/field, volleyball, water sports, and wrestling. The analysis focused on ECG leads V2, aVF and V5 which provide a three-dimensional representation of the heart's electrical activity. As marked ECG differences exist between males and females, the data are presented by gender. In males, ANOVA analysis yielded significant ECG differences between sports for heart rate, QRS duration, QTc, J-amplitude in V2 and V5, spatial vector length (SVL) of the P wave, SVL R wave, and SVL T wave, and RS(sum) (p < 0.05). In females ECG differences between sports were found for heart rate, QRS duration, QRS axis and SVL T wave (p < 0.05). Poor correlations were found between body dimensions and ECG measurements (r < 0.50). Significant ECG changes exist between college athletes participating in different sports, and these differences were more apparent in males than females. Therefore, sport-specific ECG criteria for abnormal ECG findings should be developed to obtain a more useful approach to ECG screening in athletes.
Cheng, Yih-Chun; Tsai, Pei-Yun; Huang, Ming-Hao
2016-05-19
Low-complexity compressed sensing (CS) techniques for monitoring electrocardiogram (ECG) signals in wireless body sensor network (WBSN) are presented. The prior probability of ECG sparsity in the wavelet domain is first exploited. Then, variable orthogonal multi-matching pursuit (vOMMP) algorithm that consists of two phases is proposed. In the first phase, orthogonal matching pursuit (OMP) algorithm is adopted to effectively augment the support set with reliable indices and in the second phase, the orthogonal multi-matching pursuit (OMMP) is employed to rescue the missing indices. The reconstruction performance is thus enhanced with the prior information and the vOMMP algorithm. Furthermore, the computation-intensive pseudo-inverse operation is simplified by the matrix-inversion-free (MIF) technique based on QR decomposition. The vOMMP-MIF CS decoder is then implemented in 90 nm CMOS technology. The QR decomposition is accomplished by two systolic arrays working in parallel. The implementation supports three settings for obtaining 40, 44, and 48 coefficients in the sparse vector. From the measurement result, the power consumption is 11.7 mW at 0.9 V and 12 MHz. Compared to prior chip implementations, our design shows good hardware efficiency and is suitable for low-energy applications.
IEEE-802.15.4-based low-power body sensor node with RF energy harvester.
Tran, Thang Viet; Chung, Wan-Young
2014-01-01
This paper proposes the design and implementation of a low-voltage and low-power body sensor node based on the IEEE 802.15.4 standard to collect electrocardiography (ECG) and photoplethysmography (PPG) signals. To achieve compact size, low supply voltage, and low power consumption, the proposed platform is integrated into a ZigBee mote, which contains a DC-DC booster, a PPG sensor interface module, and an ECG front-end circuit that has ultra-low current consumption. The input voltage of the proposed node is very low and has a wide range, from 0.65 V to 3.3 V. An RF energy harvester is also designed to charge the battery during the working mode or standby mode of the node. The power consumption of the proposed node reaches 14 mW in working mode to prolong the battery lifetime. The software is supported by the nesC language under the TinyOS environment, which enables the proposed node to be easily configured to function as an individual health monitoring node or a node in a wireless body sensor network (BSN). The proposed node is used to set up a wireless BSN that can simultaneously collect ECG and PPG signals and monitor the results on the personal computer.
A mobile device system for early warning of ECG anomalies.
Szczepański, Adam; Saeed, Khalid
2014-06-20
With the rapid increase in computational power of mobile devices the amount of ambient intelligence-based smart environment systems has increased greatly in recent years. A proposition of such a solution is described in this paper, namely real time monitoring of an electrocardiogram (ECG) signal during everyday activities for identification of life threatening situations. The paper, being both research and review, describes previous work of the authors, current state of the art in the context of the authors' work and the proposed aforementioned system. Although parts of the solution were described in earlier publications of the authors, the whole concept is presented completely for the first time along with the prototype implementation on mobile device-a Windows 8 tablet with Modern UI. The system has three main purposes. The first goal is the detection of sudden rapid cardiac malfunctions and informing the people in the patient's surroundings, family and friends and the nearest emergency station about the deteriorating health of the monitored person. The second goal is a monitoring of ECG signals under non-clinical conditions to detect anomalies that are typically not found during diagnostic tests. The third goal is to register and analyze repeatable, long-term disturbances in the regular signal and finding their patterns.
Explicitly-correlated Gaussian geminals in electronic structure calculations
NASA Astrophysics Data System (ADS)
Szalewicz, Krzysztof; Jeziorski, Bogumił
2010-11-01
Explicitly correlated functions have been used since 1929, but initially only for two-electron systems. In 1960, Boys and Singer showed that if the correlating factor is of Gaussian form, many-electron integrals can be computed for general molecules. The capability of explicitly correlated Gaussian (ECG) functions to accurately describe many-electron atoms and molecules was demonstrated only in the early 1980s when Monkhorst, Zabolitzky and the present authors cast the many-body perturbation theory (MBPT) and coupled cluster (CC) equations as a system of integro-differential equations and developed techniques of solving these equations with two-electron ECG functions (Gaussian-type geminals, GTG). This work brought a new accuracy standard to MBPT/CC calculations. In 1985, Kutzelnigg suggested that the linear r 12 correlating factor can also be employed if n-electron integrals, n > 2, are factorised with the resolution of identity. Later, this factor was replaced by more general functions f (r 12), most often by ? , usually represented as linear combinations of Gaussian functions which makes the resulting approach (called F12) a special case of the original GTG expansion. The current state-of-art is that, for few-electron molecules, ECGs provide more accurate results than any other basis available, but for larger systems the F12 approach is the method of choice, giving significant improvements over orbital calculations.
[Experience in the use of equipment for ECG system analysis in municipal polyclinics].
Bondarenko, A A
2006-01-01
Two electrocardiographs, an analog-digital electrocardiograph with preliminary analog filtering of signal and a smart cardiograph implemented as a PC-compatible device without preliminary analog filtering, are considered. Advantages and disadvantages of ECG systems based on artificial intelligence are discussed. ECG interpretation modes provided by the two electrocardiographs are considered. The reliability of automatic ECG interpretation is assessed. Problems of rational use of automated ECG processing systems are discussed.
Textile Concentric Ring Electrodes for ECG Recording Based on Screen-Printing Technology
Ye-Lin, Yiyao; Garcia-Casado, Javier
2018-01-01
Among many of the electrode designs used in electrocardiography (ECG), concentric ring electrodes (CREs) are one of the most promising due to their enhanced spatial resolution. Their development has undergone a great push due to their use in recent years; however, they are not yet widely used in clinical practice. CRE implementation in textiles will lead to a low cost, flexible, comfortable, and robust electrode capable of detecting high spatial resolution ECG signals. A textile CRE set has been designed and developed using screen-printing technology. This is a mature technology in the textile industry and, therefore, does not require heavy investments. Inks employed as conductive elements have been silver and a conducting polymer (poly (3,4-ethylenedioxythiophene) polystyrene sulfonate; PEDOT:PSS). Conducting polymers have biocompatibility advantages, they can be used with flexible substrates, and they are available for several printing technologies. CREs implemented with both inks have been compared by analyzing their electric features and their performance in detecting ECG signals. The results reveal that silver CREs present a higher average thickness and slightly lower skin-electrode impedance than PEDOT:PSS CREs. As for ECG recordings with subjects at rest, both CREs allowed the uptake of bipolar concentric ECG signals (BC-ECG) with signal-to-noise ratios similar to that of conventional ECG recordings. Regarding the saturation and alterations of ECGs captured with textile CREs caused by intentional subject movements, silver CREs presented a more stable response (fewer saturations and alterations) than those of PEDOT:PSS. Moreover, BC-ECG signals provided higher spatial resolution compared to conventional ECG. This improved spatial resolution was manifested in the identification of P1 and P2 waves of atrial activity in most of the BC-ECG signals. It can be concluded that textile silver CREs are more suitable than those of PEDOT:PSS for obtaining BC-ECG records. These developed textile electrodes bring the use of CREs closer to the clinical environment. PMID:29361722
Textile Concentric Ring Electrodes for ECG Recording Based on Screen-Printing Technology.
Lidón-Roger, José Vicente; Prats-Boluda, Gema; Ye-Lin, Yiyao; Garcia-Casado, Javier; Garcia-Breijo, Eduardo
2018-01-21
Among many of the electrode designs used in electrocardiography (ECG), concentric ring electrodes (CREs) are one of the most promising due to their enhanced spatial resolution. Their development has undergone a great push due to their use in recent years; however, they are not yet widely used in clinical practice. CRE implementation in textiles will lead to a low cost, flexible, comfortable, and robust electrode capable of detecting high spatial resolution ECG signals. A textile CRE set has been designed and developed using screen-printing technology. This is a mature technology in the textile industry and, therefore, does not require heavy investments. Inks employed as conductive elements have been silver and a conducting polymer (poly (3,4-ethylenedioxythiophene) polystyrene sulfonate; PEDOT:PSS). Conducting polymers have biocompatibility advantages, they can be used with flexible substrates, and they are available for several printing technologies. CREs implemented with both inks have been compared by analyzing their electric features and their performance in detecting ECG signals. The results reveal that silver CREs present a higher average thickness and slightly lower skin-electrode impedance than PEDOT:PSS CREs. As for ECG recordings with subjects at rest, both CREs allowed the uptake of bipolar concentric ECG signals (BC-ECG) with signal-to-noise ratios similar to that of conventional ECG recordings. Regarding the saturation and alterations of ECGs captured with textile CREs caused by intentional subject movements, silver CREs presented a more stable response (fewer saturations and alterations) than those of PEDOT:PSS. Moreover, BC-ECG signals provided higher spatial resolution compared to conventional ECG. This improved spatial resolution was manifested in the identification of P1 and P2 waves of atrial activity in most of the BC-ECG signals. It can be concluded that textile silver CREs are more suitable than those of PEDOT:PSS for obtaining BC-ECG records. These developed textile electrodes bring the use of CREs closer to the clinical environment.
Rossetti, Francesca; Pittiruti, Mauro; Lamperti, Massimo; Graziano, Ugo; Celentano, Davide; Capozzoli, Giuseppe
2015-01-01
The Italian Group for Venous Access Devices (GAVeCeLT) has carried out a multicenter study investigating the safety and accuracy of intracavitary electrocardiography (IC-ECG) in pediatric patients. We enrolled 309 patients (age 1 month-18 years) candidate to different central venous access devices (VAD) - 56 peripherally inserted central catheters (PICC), 178 short term centrally inserted central catheters (CICC), 65 long term VADs, 10 VADs for dialysis - in five Italian Hospitals. Three age groups were considered: A (<4 years, n = 157), B (4-11 years, n = 119), and C (12-18 years, n = 31). IC-ECG was applicable in 307 cases. The increase of the P wave on IC-ECG was detected in all cases but two. The tip of the catheter was positioned at the cavo-atrial junction (CAJ) (i.e., at the maximal height of the P wave on IC-ECG) and the position was checked during the procedure by fluoroscopy or chest x-ray, considering the CAJ at 1-2 cm (group A), 1.5-3 cm (group B), or 2-4 cm (group C) below the carina. There were no complications related to IC-ECG. The overall match between IC-ECG and x-ray was 95.8% (96.2% in group A, 95% in group B, and 96.8% in group C). In 95 cases, the IC-ECG was performed with a dedicated ECG monitor, specifically designed for IC-ECG (Nautilus, Romedex): in this group, the match between IC-ECG and x-ray was 98.8%. We conclude that the IC-ECG method is safe and accurate in the pediatric patients. The applicability of the method is 99.4% and its feasibility is 99.4%. The accuracy is 95.8% and even higher (98.8%) when using a dedicated ECG monitor.
A novel low-complexity digital filter design for wearable ECG devices
Mehrnia, Alireza
2017-01-01
Wearable and implantable Electrocardiograph (ECG) devices are becoming prevailing tools for continuous real-time personal health monitoring. The ECG signal can be contaminated by various types of noise and artifacts (e.g., powerline interference, baseline wandering) that must be removed or suppressed for accurate ECG signal processing. Limited device size, power consumption and cost are critical issues that need to be carefully considered when designing any portable health monitoring device, including a battery-powered ECG device. This work presents a novel low-complexity noise suppression reconfigurable finite impulse response (FIR) filter structure for wearable ECG and heart monitoring devices. The design relies on a recently introduced optimally-factored FIR filter method. The new filter structure and several of its useful features are presented in detail. We also studied the hardware complexity of the proposed structure and compared it with the state-of-the-art. The results showed that the new ECG filter has a lower hardware complexity relative to the state-of-the-art ECG filters. PMID:28384272
Designing ECG-based physical unclonable function for security of wearable devices.
Shihui Yin; Chisung Bae; Sang Joon Kim; Jae-Sun Seo
2017-07-01
As a plethora of wearable devices are being introduced, significant concerns exist on the privacy and security of personal data stored on these devices. Expanding on recent works of using electrocardiogram (ECG) as a modality for biometric authentication, in this work, we investigate the possibility of using personal ECG signals as the individually unique source for physical unclonable function (PUF), which eventually can be used as the key for encryption and decryption engines. We present new signal processing and machine learning algorithms that learn and extract maximally different ECG features for different individuals and minimally different ECG features for the same individual over time. Experimental results with a large 741-subject in-house ECG database show that the distributions of the intra-subject (same person) Hamming distance of extracted ECG features and the inter-subject Hamming distance have minimal overlap. 256-b random numbers generated from the ECG features of 648 (out of 741) subjects pass the NIST randomness tests.
A novel low-complexity digital filter design for wearable ECG devices.
Asgari, Shadnaz; Mehrnia, Alireza
2017-01-01
Wearable and implantable Electrocardiograph (ECG) devices are becoming prevailing tools for continuous real-time personal health monitoring. The ECG signal can be contaminated by various types of noise and artifacts (e.g., powerline interference, baseline wandering) that must be removed or suppressed for accurate ECG signal processing. Limited device size, power consumption and cost are critical issues that need to be carefully considered when designing any portable health monitoring device, including a battery-powered ECG device. This work presents a novel low-complexity noise suppression reconfigurable finite impulse response (FIR) filter structure for wearable ECG and heart monitoring devices. The design relies on a recently introduced optimally-factored FIR filter method. The new filter structure and several of its useful features are presented in detail. We also studied the hardware complexity of the proposed structure and compared it with the state-of-the-art. The results showed that the new ECG filter has a lower hardware complexity relative to the state-of-the-art ECG filters.
Nilsson, Ulf; Blomberg, Anders; Johansson, Bengt; Backman, Helena; Eriksson, Berne; Lindberg, Anne
2017-01-01
An abstract, including parts of the results, has been presented at an oral session at the European Respiratory Society International Conference, London, UK, September 2016. Cardiovascular comorbidity contributes to increased mortality among subjects with COPD. However, the prognostic value of ECG abnormalities in COPD has rarely been studied in population-based surveys. To assess the impact of ischemic ECG abnormalities (I-ECG) on mortality among individuals with COPD, compared to subjects with normal lung function (NLF), in a population-based study. During 2002-2004, all subjects with FEV 1 /VC <0.70 (COPD, n=993) were identified from population-based cohorts, together with age- and sex-matched referents without COPD. Re-examination in 2005 included interview, spirometry, and 12-lead ECG in COPD (n=635) and referents [n=991, whereof 786 had NLF]. All ECGs were Minnesota-coded. Mortality data were collected until December 31, 2010. I-ECG was equally common in COPD and NLF. The 5-year cumulative mortality was higher among subjects with I-ECG in both groups (29.6% vs 10.6%, P <0.001 and 17.1% vs 6.6%, P <0.001). COPD, but not NLF, with I-ECG had increased risk for death assessed as the mortality risk ratio [95% confidence interval (CI)] when compared with NLF without I-ECG, 2.36 (1.45-3.85) and 1.65 (0.94-2.90) when adjusted for common confounders. When analyzed separately among the COPD cohort, the increased risk for death associated with I-ECG persisted after adjustment for FEV 1 % predicted, 1.89 (1.20-2.99). A majority of those with I-ECG had no previously reported heart disease (74.2% in NLF and 67.3% in COPD) and the pattern was similar among them. I-ECG was associated with an increased risk for death in COPD, independent of common confounders and disease severity. I-ECG was of prognostic value also among those without previously known heart disease.
The history, hotspots, and trends of electrocardiogram.
Yang, Xiang-Lin; Liu, Guo-Zhen; Tong, Yun-Hai; Yan, Hong; Xu, Zhi; Chen, Qi; Liu, Xiang; Zhang, Hong-Hao; Wang, Hong-Bo; Tan, Shao-Hua
2015-07-01
The electrocardiogram (ECG) has broad applications in clinical diagnosis and prognosis of cardiovascular disease. Many researchers have contributed to its progressive development. To commemorate those pioneers, and to better study and promote the use of ECG, we reviewed and present here a systematic introduction about the history, hotspots, and trends of ECG. In the historical part, information including the invention, improvement, and extensive applications of ECG, such as in long QT syndrome (LQTS), angina, and myocardial infarction (MI), are chronologically presented. New technologies and applications from the 1990s are also introduced. In the second part, we use the bibliometric analysis method to analyze the hotspots in the field of ECG-related research. By using total citations and year-specific total citations as our main criteria, four key hotspots in ECG-related research were identified from 11 articles, including atrial fibrillation, LQTS, angina and MI, and heart rate variability. Recent studies in those four areas are also reported. In the final part, we discuss the future trends concerning ECG-related research. The authors believe that improvement of the ECG instrumentation, big data mining for ECG, and the accuracy of diagnosis and application will be areas of continuous concern.
Case report: an electrocardiogram of spontaneous pneumothorax mimicking arm lead reversal.
Wieters, J Scott; Carlin, Joseph P; Morris, Andrew
2014-05-01
There are several previously documented findings for electrocardiograms (ECGs) of spontaneous pneumothorax. These findings include axis deviation, T-wave inversion, and right bundle branch block. When an ECG has the arm leads incorrectly placed, the ECG will display right axis deviation and inversion of the P waves in lead I. There have been no previously published ECGs of spontaneous pneumothorax that have shown the same findings as reversal of the limb leads of an ECG. A possible finding of spontaneous pneumothorax is an identical finding to that of an ECG that has been flagged for limb lead reversal. A patient presented in the emergency setting with acute chest pain and shortness of breath caused by a tension pneumothorax. An ECG was administered; findings indicated reversal of the arm leads (right axis deviation and inverted P waves in lead I), but there was no actual limb lead reversal present. ECG findings resolved upon resolution of the pneumothorax. If a patient presents with chest pain and shortness of breath, and the patient's ECG is flagged for limb lead reversal despite being set up correctly, the physician should raise clinical suspicion for a possible spontaneous pneumothorax. Copyright © 2014 Elsevier Inc. All rights reserved.
The history, hotspots, and trends of electrocardiogram
Yang, Xiang-Lin; Liu, Guo-Zhen; Tong, Yun-Hai; Yan, Hong; Xu, Zhi; Chen, Qi; Liu, Xiang; Zhang, Hong-Hao; Wang, Hong-Bo; Tan, Shao-Hua
2015-01-01
The electrocardiogram (ECG) has broad applications in clinical diagnosis and prognosis of cardiovascular disease. Many researchers have contributed to its progressive development. To commemorate those pioneers, and to better study and promote the use of ECG, we reviewed and present here a systematic introduction about the history, hotspots, and trends of ECG. In the historical part, information including the invention, improvement, and extensive applications of ECG, such as in long QT syndrome (LQTS), angina, and myocardial infarction (MI), are chronologically presented. New technologies and applications from the 1990s are also introduced. In the second part, we use the bibliometric analysis method to analyze the hotspots in the field of ECG-related research. By using total citations and year-specific total citations as our main criteria, four key hotspots in ECG-related research were identified from 11 articles, including atrial fibrillation, LQTS, angina and MI, and heart rate variability. Recent studies in those four areas are also reported. In the final part, we discuss the future trends concerning ECG-related research. The authors believe that improvement of the ECG instrumentation, big data mining for ECG, and the accuracy of diagnosis and application will be areas of continuous concern. PMID:26345622
A wearable 12-lead ECG acquisition system with fabric electrodes.
Haoshi Zhang; Lan Tian; Huiyang Lu; Ming Zhou; Haiqing Zou; Peng Fang; Fuan Yao; Guanglin Li
2017-07-01
Continuous electrocardiogram (ECG) monitoring is significant for prevention of heart disease and is becoming an important part of personal and family health care. In most of the existing wearable solutions, conventional metal sensors and corresponding chips are simply integrated into clothes and usually could only collect few leads of ECG signals that could not provide enough information for diagnosis of cardiac diseases such as arrhythmia and myocardial ischemia. In this study, a wearable 12-lead ECG acquisition system with fabric electrodes was developed and could simultaneously process 12 leads of ECG signals. By integrating the fabric electrodes into a T-shirt, the wearable system would provide a comfortable and convenient user interface for ECG recording. For comparison, the proposed fabric electrode and the gelled traditional metal electrodes were used to collect ECG signals on a subject, respectively. The approximate entropy (ApEn) of ECG signals from both types of electrodes were calculated. The experimental results show that the fabric electrodes could achieve similar performance as the gelled metal electrodes. This preliminary work has demonstrated that the developed ECG system with fabric electrodes could be utilized for wearable health management and telemedicine applications.
A review on digital ECG formats and the relationships between them.
Trigo, Jesús Daniel; Alesanco, Alvaro; Martínez, Ignacio; García, José
2012-05-01
A plethora of digital ECG formats have been proposed and implemented. This heterogeneity hinders the design and development of interoperable systems and entails critical integration issues for the healthcare information systems. This paper aims at performing a comprehensive overview on the current state of affairs of the interoperable exchange of digital ECG signals. This includes 1) a review on existing digital ECG formats, 2) a collection of applications and cardiology settings using such formats, 3) a compilation of the relationships between such formats, and 4) a reflection on the current situation and foreseeable future of the interoperable exchange of digital ECG signals. The objectives have been approached by completing and updating previous reviews on the topic through appropriate database mining. 39 digital ECG formats, 56 applications, tools or implantation experiences, 47 mappings/converters, and 6 relationships between such formats have been found in the literature. The creation and generalization of a single standardized ECG format is a desirable goal. However, this unification requires political commitment and international cooperation among different standardization bodies. Ongoing ontology-based approaches covering ECG domain have recently emerged as a promising alternative for reaching fully fledged ECG interoperability in the near future.
Moustafa, Abdelmoniem; Abi-Saleh, Bernard; El-Baba, Mohammad; Hamoui, Omar; AlJaroudi, Wael
2016-02-01
In patients presenting with non-ST-elevation myocardial infarction (NSTEMI), left anterior descending (LAD) coronary artery and three-vessel disease are the most commonly encountered culprit lesions in the presence of ST depression, while one third of patients with left circumflex (LCX) artery related infarction have normal ECG. We sought to determine the predictors of presence of culprit lesion in NSTEMI patients based on ECG, echocardiographic, and clinical characteristics. Patients admitted to the coronary care unit with the diagnosis of NSTEMI between June 2012 and December 2013 were retrospectively identified. Admission ECG was interpreted by an electrophysiologist that was blinded to the result of the coronary angiogram. Patients were dichotomized into either normal or abnormal ECG group. The primary endpoint was presence of culprit lesion. Secondary endpoints included length of stay, re-hospitalization within 60 days, and in-hospital mortality. A total of 118 patients that were identified; 47 with normal and 71 with abnormal ECG. At least one culprit lesion was identified in 101 patients (86%), and significantly more among those with abnormal ECG (91.5% vs. 76.6%, P=0.041).The LAD was the most frequently detected culprit lesion in both groups. There was a higher incidence of two and three-vessel disease in the abnormal ECG group (P=0.041).On the other hand, there was a trend of higher LCX involvement (25% vs. 13.8%, P=0.18) and more normal coronary arteries in the normal ECG group (23.4% vs. 8.5%, P=0.041). On multivariate analysis, prior history of coronary artery disease (CAD) [odds ratio (OR) 6.4 (0.8-52)], male gender [OR 5.0 (1.5-17)], and abnormal admission ECG [OR 3.6 (1.12-12)], were independent predictors of a culprit lesion. There was no difference in secondary endpoints between those with normal and abnormal ECG. Among patients presenting with NSTEMI, prior history of CAD, male gender and abnormal admission ECG were independent predictors of a culprit lesion. An abnormal ECG was significantly associated with two and three-vessel disease, while normal ECG was more associated with LCX involvement or normal angiogram. Admission ECG did not impact secondary outcomes.
A survey of paediatricians on the use of electrocardiogram for pre-participation sports screening.
Patel, Angira; Webster, Gregory; Ward, Kendra; Lantos, John
2017-07-01
Aim The aim of the present study was to determine general paediatrician knowledge, practices, and attitudes towards electrocardiogram (ECG) screening in school athletes during pre-participation screening exam (PPSE). Paediatricians affiliated with a tertiary children's hospital completed a survey about ECGs for PPSE. In total, 205/498 (41%) responded; 92% of the paediatricians did not include an ECG as part of PPSE; 56% were aware of a case in which a student athlete in their own community had died of sudden unexplained death; 4% had an athlete in their practice die. Only 16% of paediatricians perform all 12 American Heart Association recommended elements of the PPSE. If any of these screening elements are abnormal, 69% obtain an ECG, 36% an echocardiogram, and 30% restrict patients from sports activity; 73% of them refer the patient to a cardiologist. Most of the general paediatricians surveyed did not currently perform ECGs for PPSE. In addition, there was a low rate of adherence to performing the 12 screening elements recommended by the American Heart Association. They have trouble obtaining timely, accurate ECG interpretations, worry about potential unnecessary exercise restrictions, and cost-effectiveness. The practical hurdles to ECG implementation emphasise the need for a fresh look at PPSE, and not just ECG screening. Improvements in ECG performance/interpretation would be necessary for ECGs to be a useful part of PPSE.
Individual Biometric Identification Using Multi-Cycle Electrocardiographic Waveform Patterns.
Lee, Wonki; Kim, Seulgee; Kim, Daeeun
2018-03-28
The electrocardiogram (ECG) waveform conveys information regarding the electrical property of the heart. The patterns vary depending on the individual heart characteristics. ECG features can be potentially used for biometric recognition. This study presents a new method using the entire ECG waveform pattern for matching and demonstrates that the approach can potentially be employed for individual biometric identification. Multi-cycle ECG signals were assessed using an ECG measuring circuit, and three electrodes can be patched on the wrists or fingers for considering various measurements. For biometric identification, our-fold cross validation was used in the experiments for assessing how the results of a statistical analysis will generalize to an independent data set. Four different pattern matching algorithms, i.e., cosine similarity, cross correlation, city block distance, and Euclidean distances, were tested to compare the individual identification performances with a single channel of ECG signal (3-wire ECG). To evaluate the pattern matching for biometric identification, the ECG recordings for each subject were partitioned into training and test set. The suggested method obtained a maximum performance of 89.9% accuracy with two heartbeats of ECG signals measured on the wrist and 93.3% accuracy with three heartbeats for 55 subjects. The performance rate with ECG signals measured on the fingers improved up to 99.3% with two heartbeats and 100% with three heartbeats of signals for 20 subjects.
Ubiquitous health monitoring and real-time cardiac arrhythmias detection: a case study.
Li, Jian; Zhou, Haiying; Zuo, Decheng; Hou, Kun-Mean; De Vaulx, Christophe
2014-01-01
As the symptoms and signs of heart diseases that cause sudden cardiac death, cardiac arrhythmia has attracted great attention. Due to limitations in time and space, traditional approaches to cardiac arrhythmias detection fail to provide a real-time continuous monitoring and testing service applicable in different environmental conditions. Integrated with the latest technologies in ECG (electrocardiograph) analysis and medical care, the pervasive computing technology makes possible the ubiquitous cardiac care services, and thus brings about new technical challenges, especially in the formation of cardiac care architecture and realization of the real-time automatic ECG detection algorithm dedicated to care devices. In this paper, a ubiquitous cardiac care prototype system is presented with its architecture framework well elaborated. This prototype system has been tested and evaluated in all the clinical-/home-/outdoor-care modes with a satisfactory performance in providing real-time continuous cardiac arrhythmias monitoring service unlimitedly adaptable in time and space.
International recommendations for electrocardiographic interpretation in athletes.
Sharma, Sanjay; Drezner, Jonathan A; Baggish, Aaron; Papadakis, Michael; Wilson, Mathew G; Prutkin, Jordan M; La Gerche, Andre; Ackerman, Michael J; Borjesson, Mats; Salerno, Jack C; Asif, Irfan M; Owens, David S; Chung, Eugene H; Emery, Michael S; Froelicher, Victor F; Heidbuchel, Hein; Adamuz, Carmen; Asplund, Chad A; Cohen, Gordon; Harmon, Kimberly G; Marek, Joseph C; Molossi, Silvana; Niebauer, Josef; Pelto, Hank F; Perez, Marco V; Riding, Nathan R; Saarel, Tess; Schmied, Christian M; Shipon, David M; Stein, Ricardo; Vetter, Victoria L; Pelliccia, Antonio; Corrado, Domenico
2018-04-21
Sudden cardiac death (SCD) is the leading cause of mortality in athletes during sport. A variety of mostly hereditary, structural, or electrical cardiac disorders are associated with SCD in young athletes, the majority of which can be identified or suggested by abnormalities on a resting 12-lead electrocardiogram (ECG). Whether used for diagnostic or screening purposes, physicians responsible for the cardiovascular care of athletes should be knowledgeable and competent in ECG interpretation in athletes. However, in most countries a shortage of physician expertise limits wider application of the ECG in the care of the athlete. A critical need exists for physician education in modern ECG interpretation that distinguishes normal physiological adaptations in athletes from distinctly abnormal findings suggestive of underlying pathology. Since the original 2010 European Society of Cardiology recommendations for ECG interpretation in athletes, ECG standards have evolved quickly over the last decade; pushed by a growing body of scientific data that both tests proposed criteria sets and establishes new evidence to guide refinements. On 26-27 February 2015, an international group of experts in sports cardiology, inherited cardiac disease, and sports medicine convened in Seattle, Washington, to update contemporary standards for ECG interpretation in athletes. The objective of the meeting was to define and revise ECG interpretation standards based on new and emerging research and to develop a clear guide to the proper evaluation of ECG abnormalities in athletes. This statement represents an international consensus for ECG interpretation in athletes and provides expert opinion-based recommendations linking specific ECG abnormalities and the secondary evaluation for conditions associated with SCD.
Leigh, J. Adam; O’Neal, Wesley T.; Soliman, Elsayed Z.
2016-01-01
Left ventricular hypertrophy (LVH) diagnosed by electrocardiography (ECG-LVH) and echocardiography (echo-LVH) are independently associated with an increased risk of cardiovascular disease (CVD) events. However, it is unknown if ECG-LVH retains its predictive properties independent of left ventricular anatomy. We compared the risk of CVD associated with ECG-LVH and echo-LVH in 4,076 participants (41% male, 86% white) from the Cardiovascular Health Study (CHS), who were free of baseline CVD. ECG-LVH was defined with Minnesota ECG Classification criteria from baseline ECG data. Echo-LVH was defined by sex-specific left ventricular mass values normalized to body surface area (male: >102 g/m2; female: >88 g/m2). ECG-LVH was detected in 144 (3.5%) participants and echo-LVH in 430 (11%) participants. Over a median follow-up of 10.6 years, 2,274 CVD events occurred. In a multivariable Cox regression analysis adjusted for common CVD risk factors, ECG-LVH (HR=1.84, 95%CI=1.51, 2.24) and echo-LVH (HR=1.35, 95%CI=1.19, 1.54) were associated with an increased risk for CVD events. The association between ECG-LVH and CVD events was not substantively altered with further adjustment for echo-LVH (HR=1.76, 95%CI=1.45, 2.15). In conclusion, the association of ECG-LVH with CVD events is not dependent on echo-LVH. This finding provides support to the concept that ECG-LVH is an electrophysiologic marker with predictive properties independent of left ventricular anatomy. PMID:27067620
Smartphone ECG for evaluation of STEMI: results of the ST LEUIS Pilot Study.
Muhlestein, Joseph Boone; Le, Viet; Albert, David; Moreno, Fidela Ll; Anderson, Jeffrey L; Yanowitz, Frank; Vranian, Robert B; Barsness, Gregory W; Bethea, Charles F; Severance, Harry W; Ramo, Barry; Pierce, John; Barbagelata, Alejandro; Muhlestein, Joseph Brent
2015-01-01
12-lead ECG is a critical component of initial evaluation of cardiac ischemia, but has traditionally been limited to large, dedicated equipment in medical care environments. Smartphones provide a potential alternative platform for the extension of ECG to new care settings and to improve timeliness of care. To gain experience with smartphone electrocardiography prior to designing a larger multicenter study evaluating standard 12-lead ECG compared to smartphone ECG. 6 patients for whom the hospital STEMI protocol was activated were evaluated with traditional 12-lead ECG followed immediately by a smartphone ECG using right (VnR) and left (VnL) limb leads for precordial grounding. The AliveCor™ Heart Monitor was utilized for this study. All tracings were taken prior to catheterization or immediately after revascularization while still in the catheterization laboratory. The smartphone ECG had excellent correlation with the gold standard 12-lead ECG in all patients. Four out of six tracings were judged to meet STEMI criteria on both modalities as determined by three experienced cardiologists, and in the remaining two, consensus indicated a non-STEMI ECG diagnosis. No significant difference was noted between VnR and VnL. Smartphone based electrocardiography is a promising, developing technology intended to increase availability and speed of electrocardiographic evaluation. This study confirmed the potential of a smartphone ECG for evaluation of acute ischemia and the feasibility of studying this technology further to define the diagnostic accuracy, limitations and appropriate use of this new technology. Copyright © 2015 Elsevier Inc. All rights reserved.
Wess, G; Schulze, A; Geraghty, N; Hartmann, K
2010-01-01
Ventricular premature contractions (VPCs) are common in the occult stage of cardiomyopathy in Doberman Pinschers. Although the gold standard for detecting arrhythmia is the 24-hour ambulatory electrocardiography (ECG) (Holter), this method is more expensive, time-consuming and often not as readily available as common ECG. Comparison of 5-minute ECGs with Holter examinations. Eight hundred and seventy-five 5-minute ECGs and Holter examinations of 431 Doberman Pinschers. Each examination included a 5-minute ECG and Holter examination. A cut-off value of > 100 VPCs/24 hours using Holter was considered diagnostic for the presence of cardiomyopathy. Statistical evaluation included calculation of sensitivity, specificity, positive predictive value, and negative predictive value. Holter examinations revealed > 100 VPCs/24 hours in 204/875 examinations. At least 1 VPC during a 5-minute ECG was detected in 131 (64.2%) of these 204 examinations. No VPCs were found in the 5-minute ECG in 73 (35.8%) examinations of affected Doberman Pinschers. A 5-minute ECG with at least 1 VPC as cut-off had a sensitivity of 64.2%, a specificity of 96.7%, a positive predictive value of 85.6% and a negative predictive value of 89.9% for the presence of > 100 VPCs/24 hours. A 5-minute ECG is a rather insensitive method for detecting arrhythmias in Doberman Pinschers. However, the occurrence of at least 1 VPC in 5 minutes strongly warrants further examination of the dog, because specificity (96.7%) and positive predictive value (85.6%) are high and could suggest occult cardiomyopathy.
NASA Astrophysics Data System (ADS)
Gontier, Camille
2017-11-01
The purpose of this study is to detect mind-wandering in an Extra-Vehicular Activity (EVA) context during a long supervision task. Detection is realized using an electro-cardiogram and measures of heart rate variability. Experienced by everyone, mind-wandering depicts the state of mind where thoughts are not related to the current action. Its deleterious aspect regarding performance suggests a need to take mind-wandering seriously as an impediment to manned space missions' safety. Previous research confirmed the hypothesis according to which several physiological responses can be used to track down mind-wandering. ECG recordings are both easy to obtain and analyze, statistically related to mind-wandering, and easy to record during extra-vehicular activities. Data analyzed in this paper have been recorded during a Mars-analog mission (MDRS 164), from February 20 to March 6, 2016 at the Mars Desert Research Station (Utah). During various cognitive tasks, the subject had his ECG and awareness levels monitored at the same time to see if a correlation between these two measures can be used in a Mars-mission environment. At different time intervals, the subject was interrupted using the thought probe method to inquire about his thoughts. Heart Rate Variability (HRV, which power in high frequencies is related to the parasympathetic system and is expected to vary with mind-wandering) was then computed from recorded data, and its statistical changes during on-task and off-task thoughts were assessed. Although data revealed no significant differences nor coherent trends in HRV-related metrics between the two conditions, results are paving the way towards a better understanding of ECG-recordings and their use during space-analog missions.
Selvester scoring in patients with strict LBBB using the QUARESS software.
Xia, Xiaojuan; Chaudhry, Uzma; Wieslander, Björn; Borgquist, Rasmus; Wagner, Galen S; Strauss, David G; Platonov, Pyotr; Ugander, Martin; Couderc, Jean-Philippe
2015-01-01
Estimation of the infarct size from body-surface ECGs in post-myocardial infarction patients has become possible using the Selvester scoring method. Automation of this scoring has been proposed in order to speed-up the measurement of the score and improving the inter-observer variability in computing a score that requires strong expertise in electrocardiography. In this work, we evaluated the quality of the QuAReSS software for delivering correct Selvester scoring in a set of standard 12-lead ECGs. Standard 12-lead ECGs were recorded in 105 post-MI patients prescribed implantation of an implantable cardiodefibrillator (ICD). Amongst the 105 patients with standard clinical left bundle branch block (LBBB) patterns, 67 had a LBBB pattern meeting the strict criteria. The QuAReSS software was applied to these 67 tracings by two independent groups of cardiologists (from a clinical group and an ECG core laboratory) to measure the Selvester score semi-automatically. Using various level of agreement metrics, we compared the scores between groups and when automatically measured by the software. The average of the absolute difference in Selvester scores measured by the two independent groups was 1.4±1.5 score points, whereas the difference between automatic method and the two manual adjudications were 1.2±1.2 and 1.3±1.2 points. Eighty-two percent score agreement was observed between the two independent measurements when the difference of score was within two point ranges, while 90% and 84% score agreements were reached using the automatic method compared to the two manual adjudications. The study confirms that the QuAReSS software provides valid measurements of the Selvester score in patients with strict LBBB with minimal correction from cardiologists. Copyright © 2015 Elsevier Inc. All rights reserved.
Christov, Ivaylo I; Iliev, Georgi L
2005-01-01
Background A specific problem using the public access defibrillators (PADs) arises at the railway stations. Some countries as Germany, Austria, Switzerland, Norway and Sweden are using AC railroad net power-supply system with rated 16.7 Hz frequency modulated from 15.69 Hz to 17.36 Hz. The power supply frequency contaminates the electrocardiogram (ECG). It is difficult to be suppressed or eliminated due to the fact that it considerably overlaps the frequency spectra of the ECG. The interference impedes the automated decision of the PADs whether a patient should be (or should not be) shocked. The aim of this study is the suppression of the 16.7 Hz interference generated by the power supply of the railway systems. Methods Software solution using adaptive filtering method was proposed for 16.7 Hz interference suppression. The optimal performance of the filter is achieved, embedding a reference channel in the PADs to record the interference. The method was tested with ECGs from AHA database. Results The method was tested with patients of normal sinus rhythms, symptoms of tachycardia and ventricular fibrillation. Simulated interference with frequency modulation from 15.69 Hz to 17.36 Hz changing at a rate of 2% per second was added to the ECGs, and then processed by the suggested adaptive filtering. The method totally suppresses the noise with no visible distortions of the original signals. Conclusion The proposed adaptive filter for noise suppression generated by the power supply of the railway systems has a simple structure requiring a low level of computational resources, but a good reference signal as well. PMID:15766390
ECG Identification System Using Neural Network with Global and Local Features
ERIC Educational Resources Information Center
Tseng, Kuo-Kun; Lee, Dachao; Chen, Charles
2016-01-01
This paper proposes a human identification system via extracted electrocardiogram (ECG) signals. Two hierarchical classification structures based on global shape feature and local statistical feature is used to extract ECG signals. Global shape feature represents the outline information of ECG signals and local statistical feature extracts the…
[Implementation of ECG Monitoring System Based on Internet of Things].
Lu, Liangliang; Chen, Minya
2015-11-01
In order to expand the capabilities of hospital's traditional ECG device and enhance medical staff's work efficiency, an ECG monitoring system based on internet of things is introduced. The system can monitor ECG signals in real time and analyze data using ECG sensor, PDA, Web servers, which embeds C language, Android systems, .NET, wireless network and other technologies. After experiments, it can be showed that the system has high reliability and stability and can bring the convenience to medical staffs.
Development of a Multi-Channel, High Frequency QRS Electrocardiograph
NASA Technical Reports Server (NTRS)
DePalma, Jude L.
2003-01-01
With the advent of the ISS era and the potential requirement for increased cardiovascular monitoring of crewmembers during extended EVAs, NASA flight surgeons would stand to benefit from an evolving technology that allows for a more rapid diagnosis of myocardial ischemia compared to standard electrocardiography. Similarly, during the astronaut selection process, NASA flight surgeons and other physicians would also stand to benefit from a completely noninvasive technology that, either at rest or during maximal exercise tests, is more sensitive than standard ECG in identifying the presence of ischemia. Perhaps most importantly, practicing cardiologists and emergency medicine physicians could greatly benefit from such a device as it could augment (or even replace) standard electrocardiography in settings where the rapid diagnosis of myocardial ischemia (or the lack thereof) is required for proper clinical decision-making. A multi-channel, high-frequency QRS electrocardiograph is currently under development in the Life Sciences Research Laboratories at JSC. Specifically the project consisted of writing software code, some of which contained specially-designed digital filters, which will be incorporated into an existing commercial software program that is already designed to collect, plot and analyze conventional 12-lead ECG signals on a desktop, portable or palm PC. The software will derive the high-frequency QRS signals, which will be analyzed (in numerous ways) and plotted alongside of the conventional ECG signals, giving the PC-viewing clinician advanced diagnostic information that has never been available previously in all 12 ECG leads simultaneously. After the hardware and software for the advanced digital ECG monitor have been fully integrated, plans are to use the monitor to begin clinical studies both on healthy subjects and on patients with known coronary artery disease in both the outpatient and hospital settings. The ultimate goal is to get the technology out into the clinical world, where it has the potential to save lives.
Shavadia, Jay S; French, William; Hellkamp, Anne S; Thomas, Laine; Bates, Eric R; Manoukian, Steven V; Kontos, Michael C; Suter, Robert; Henry, Timothy D; Dauerman, Harold L; Roe, Matthew T
2018-03-01
Assessing hospital-related network-level primary percutaneous coronary intervention (PCI) performance for ST-segment elevation myocardial infarction (STEMI) is challenging due to differential time-to-treatment metrics based on location of diagnostic electrocardiogram (ECG) for STEMI. STEMI patients undergoing primary PCI at 588 PCI-capable hospitals in AHA Mission: Lifeline (2008-2013) were categorized by initial STEMI identification location: PCI-capable hospitals (Group 1); pre-hospital setting (Group 2); and non-PCI-capable hospitals (Group 3). Patient-specific time-to-treatment categories were converted to minutes ahead of or behind their group-specific mean; average time-to-treatment difference for all patients at a given hospital was termed comprehensive ECG-to-device time. Hospitals were then stratified into tertiles based on their comprehensive ECG-to-device times with negative values below the mean representing shorter (faster) time intervals. Of 117,857 patients, the proportion in Groups 1, 2, and 3 were 42%, 33%, and 25%, respectively. Lower rates of heart failure and cardiac arrest at presentation are noted within patients presenting to high-performing hospitals. Median comprehensive ECG-to-device time was shortest at -9 minutes (25th, 75th percentiles: -13, -6) for the high-performing hospital tertile, 1 minute (-1, 3) for middle-performing, and 11 minutes (7, 16) for low-performing. Unadjusted rates of in-hospital mortality were 2.3%, 2.6%, and 2.7%, respectively, but the adjusted risk of in-hospital mortality was similar across tertiles. Comprehensive ECG-to-device time provides an integrated hospital-related network-level assessment of reperfusion timing metrics for primary PCI, regardless of the location for STEMI identification; further validation will delineate how this metric can be used to facilitate STEMI care improvements. Copyright © 2017 Elsevier Inc. All rights reserved.
Warmerdam, G; Vullings, R; Van Pul, C; Andriessen, P; Oei, S G; Wijn, P
2013-01-01
Non-invasive fetal electrocardiography (ECG) can be used for prolonged monitoring of the fetal heart rate (FHR). However, the signal-to-noise-ratio (SNR) of non-invasive ECG recordings is often insufficient for reliable detection of the FHR. To overcome this problem, source separation techniques can be used to enhance the fetal ECG. This study uses a physiology-based source separation (PBSS) technique that has already been demonstrated to outperform widely used blind source separation techniques. Despite the relatively good performance of PBSS in enhancing the fetal ECG, PBSS is still susceptible to artifacts. In this study an augmented PBSS technique is developed to reduce the influence of artifacts. The performance of the developed method is compared to PBSS on multi-channel non-invasive fetal ECG recordings. Based on this comparison, the developed method is shown to outperform PBSS for the enhancement of the fetal ECG.
Application of exercise ECG stress test in the current high cost modern-era healthcare system.
Vaidya, Gaurang Nandkishor
Exercise electrocardiogram (ECG) tests boasts of being more widely available, less resource intensive, lower cost and absence of radiation. In the presence of a normal baseline ECG, an exercise ECG test is able to generate a reliable and reproducible result almost comparable to Technitium-99m sestamibi perfusion imaging. Exercise ECG changes when combined with other clinical parameters obtained during the test has the potential to allow effective redistribution of scarce resources by excluding low risk patients with significant accuracy. As we look towards a future of rising healthcare costs, increased prevalence of cardiovascular disease and the need for proper allocation of limited resources; exercise ECG test offers low cost, vital and reliable disease interpretation. This article highlights the physiology of the exercise ECG test, patient selection, effective interpretation, describe previously reported scores and their clinical application in today's clinical practice. Copyright © 2017. Published by Elsevier B.V.
Left arm/left leg lead reversals at the cable junction box: A cause for an epidemic of errors.
Velagapudi, Poonam; Turagam, Mohit K; Ritter, Sherry; Dohrmann, Mary L
Medical errors, especially due to misinterpretation of electrocardiograms (ECG), are extremely common in patients admitted to the hospital and significantly account for increased morbidity, mortality and health care costs in the United States. Inaccurate performance of an ECG can lead to invalid interpretation and in turn may lead to costly cardiovascular evaluation. We report a retrospective series of 58 sequential cases of ECG limb lead reversals in the ER due to inadvertent interchange in the lead cables at the point where they insert into the cable junction box of one ECG machine. This case series highlights recognition of ECG lead reversal originating in the ECG machine itself. This case series also demonstrates an ongoing need for education regarding standardization of ECG testing and for recognizing technical anomalies to deliver appropriate care for the patient. Copyright © 2016. Published by Elsevier Inc.
Performance study of the wearable one-lead wireless electrocardiographic monitoring system.
Hong, Sungyoup; Yang, Yougmo; Kim, Seunghwan; Shin, Seungcheol; Lee, Inbum; Jang, Yongwon; Kim, Kiseong; Yi, Hwayeon
2009-03-01
This study attempts to compare and assess the performance of a wearable electrocardiogram (ECG) using a sensing fabric electrode and a Bluetooth network with a conventional ECG. A one-lead ECG examination was performed using Bioshirt and an iWorx 214 while walking or running at 3, 6, and 9 km per hour. A correlation coefficient of a heart rate variability (HRV) between these two devices was higher than 0.96 and power spectral density of HRV measured also showed an excellent agreement. Thus, both of these two ECG devices showed similar detection capability for R peaks. The measured values for wave duration and intervals of both devices concur with each other. The intensity of noise is controversial. The ECG device using a sensing fabric electrode and a wireless network showed an ECG signal detection and transmission capability similar to that of a conventional ECG device.
Adaptive Fourier decomposition based ECG denoising.
Wang, Ze; Wan, Feng; Wong, Chi Man; Zhang, Liming
2016-10-01
A novel ECG denoising method is proposed based on the adaptive Fourier decomposition (AFD). The AFD decomposes a signal according to its energy distribution, thereby making this algorithm suitable for separating pure ECG signal and noise with overlapping frequency ranges but different energy distributions. A stop criterion for the iterative decomposition process in the AFD is calculated on the basis of the estimated signal-to-noise ratio (SNR) of the noisy signal. The proposed AFD-based method is validated by the synthetic ECG signal using an ECG model and also real ECG signals from the MIT-BIH Arrhythmia Database both with additive Gaussian white noise. Simulation results of the proposed method show better performance on the denoising and the QRS detection in comparing with major ECG denoising schemes based on the wavelet transform, the Stockwell transform, the empirical mode decomposition, and the ensemble empirical mode decomposition. Copyright © 2016 Elsevier Ltd. All rights reserved.
Edla, Shwetha; Kovvali, Narayan; Papandreou-Suppappola, Antonia
2012-01-01
Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can be used for automated disease classification, is of great importance in precluding manual annotation and providing prompt diagnosis of cardiac diseases. ECG signals consist of several segments with different morphologies (namely the P wave, QRS complex and the T wave) in a single heart beat, which can vary across individuals and diseases. Also, existing statistical ECG models exhibit a reliance upon obtaining a priori information from the ECG data by using preprocessing algorithms to initialize the filter parameters, or to define the user-specified model parameters. In this paper, we propose an ECG modeling technique using the sequential Markov chain Monte Carlo (SMCMC) filter that can perform simultaneous model selection, by adaptively choosing from different representations depending upon the nature of the data. Our results demonstrate the ability of the algorithm to track various types of ECG morphologies, including intermittently occurring ECG beats. In addition, we use the estimated model parameters as the feature set to classify between ECG signals with normal sinus rhythm and four different types of arrhythmia.
Surface 12 lead electrocardiogram recordings using smart phone technology.
Baquero, Giselle A; Banchs, Javier E; Ahmed, Shameer; Naccarelli, Gerald V; Luck, Jerry C
2015-01-01
AliveCor ECG is an FDA approved ambulatory cardiac rhythm monitor that records a single channel (lead I) ECG rhythm strip using an iPhone. In the past few years, the use of smartphones and tablets with health related applications has significantly proliferated. In this initial feasibility trial, we attempted to reproduce the 12 lead ECG using the bipolar arrangement of the AliveCor monitor coupled to smart phone technology. We used the AliveCor heart monitor coupled with an iPhone cellular phone and the AliveECG application (APP) in 5 individuals. In our 5 individuals, recordings from both a standard 12 lead ECG and the AliveCor generated 12 lead ECG had the same interpretation. This study demonstrates the feasibility of creating a 12 lead ECG with a smart phone. The validity of the recordings would seem to suggest that this technology could become an important useful tool for clinical use. This new hand held smart phone 12 lead ECG recorder needs further development and validation. Copyright © 2015 Elsevier Inc. All rights reserved.
Teaching crucial skills: An electrocardiogram teaching module for medical students.
Chudgar, Saumil M; Engle, Deborah L; Grochowski, Colleen O'Connor; Gagliardi, Jane P
2016-01-01
Medical student performance in electrocardiogram (ECG) interpretation at our institution could be improved. Varied resources exist to teach students this essential skill. We created an ECG teaching module (ECGTM) of 75 cases representing 15 diagnoses to improve medical students' performance and confidence in ECG interpretation. Students underwent pre- and post-clerkship testing to assess ECG interpretation skills and confidence and also end-of-clinical-year testing in ECG and laboratory interpretation. Performance was compared for the years before and during ECGTM availability. Eighty-four percent of students (total n=101) reported using the ECGTM; 98% of those who used it reported it was useful. Students' performance and confidence were higher on the post-test. Students with access to the ECGTM (n=101) performed significantly better than students from the previous year (n=90) on the end-of-year ECG test. The continuous availability of an ECGTM was associated with improved confidence and ability in ECG interpretation. The ECGTM may be another available tool to help students as they learn to read ECGs. Copyright © 2016 Elsevier Inc. All rights reserved.
Electrocardiogram signal denoising based on empirical mode decomposition technique: an overview
NASA Astrophysics Data System (ADS)
Han, G.; Lin, B.; Xu, Z.
2017-03-01
Electrocardiogram (ECG) signal is nonlinear and non-stationary weak signal which reflects whether the heart is functioning normally or abnormally. ECG signal is susceptible to various kinds of noises such as high/low frequency noises, powerline interference and baseline wander. Hence, the removal of noises from ECG signal becomes a vital link in the ECG signal processing and plays a significant role in the detection and diagnosis of heart diseases. The review will describe the recent developments of ECG signal denoising based on Empirical Mode Decomposition (EMD) technique including high frequency noise removal, powerline interference separation, baseline wander correction, the combining of EMD and Other Methods, EEMD technique. EMD technique is a quite potential and prospective but not perfect method in the application of processing nonlinear and non-stationary signal like ECG signal. The EMD combined with other algorithms is a good solution to improve the performance of noise cancellation. The pros and cons of EMD technique in ECG signal denoising are discussed in detail. Finally, the future work and challenges in ECG signal denoising based on EMD technique are clarified.
Standard-compliant real-time transmission of ECGs: harmonization of ISO/IEEE 11073-PHD and SCP-ECG.
Trigo, Jesús D; Chiarugi, Franco; Alesanco, Alvaro; Martínez-Espronceda, Miguel; Chronaki, Catherine E; Escayola, Javier; Martínez, Ignacio; García, José
2009-01-01
Ambient assisted living and integrated care in an aging society is based on the vision of the lifelong Electronic Health Record calling for HealthCare Information Systems and medical device interoperability. For medical devices this aim can be achieved by the consistent implementation of harmonized international interoperability standards. The ISO/IEEE 11073 (x73) family of standards is a reference standard for medical device interoperability. In its Personal Health Device (PHD) version several devices have been included, but an ECG device specialization is not yet available. On the other hand, the SCP-ECG standard for short-term diagnostic ECGs (EN1064) has been recently approved as an international standard ISO/IEEE 11073-91064:2009. In this paper, the relationships between a proposed x73-PHD model for an ECG device and the fields of the SCP-ECG standard are investigated. A proof-of-concept implementation of the proposed x73-PHD ECG model is also presented, identifying open issues to be addressed by standards development for the wider interoperability adoption of x73-PHD standards.
A novel algorithm for Bluetooth ECG.
Pandya, Utpal T; Desai, Uday B
2012-11-01
In wireless transmission of ECG, data latency will be significant when battery power level and data transmission distance are not maintained. In applications like home monitoring or personalized care, to overcome the joint effect of previous issues of wireless transmission and other ECG measurement noises, a novel filtering strategy is required. Here, a novel algorithm, identified as peak rejection adaptive sampling modified moving average (PRASMMA) algorithm for wireless ECG is introduced. This algorithm first removes error in bit pattern of received data if occurred in wireless transmission and then removes baseline drift. Afterward, a modified moving average is implemented except in the region of each QRS complexes. The algorithm also sets its filtering parameters according to different sampling rate selected for acquisition of signals. To demonstrate the work, a prototyped Bluetooth-based ECG module is used to capture ECG with different sampling rate and in different position of patient. This module transmits ECG wirelessly to Bluetooth-enabled devices where the PRASMMA algorithm is applied on captured ECG. The performance of PRASMMA algorithm is compared with moving average and S-Golay algorithms visually as well as numerically. The results show that the PRASMMA algorithm can significantly improve the ECG reconstruction by efficiently removing the noise and its use can be extended to any parameters where peaks are importance for diagnostic purpose.
Marker, Ryan J; Maluf, Katrina S
2014-12-01
Electromyography (EMG) recordings from the trapezius are often contaminated by the electrocardiography (ECG) signal, making it difficult to distinguish low-level muscle activity from muscular rest. This study investigates the influence of ECG contamination on EMG amplitude and frequency estimations in the upper trapezius during muscular rest and low-level contractions. A new method of ECG contamination removal, filtered template subtraction (FTS), is described and compared to 30 Hz high-pass filter (HPF) and averaged template subtraction (ATS) methods. FTS creates a unique template of each ECG artifact using a low-pass filtered copy of the contaminated signal, which is subtracted from contaminated periods in the original signal. ECG contamination results in an over-estimation of EMG amplitude during rest in the upper trapezius, with negligible effects on amplitude and frequency estimations during low-intensity isometric contractions. FTS and HPF successfully removed ECG contamination from periods of muscular rest, yet introduced errors during muscle contraction. Conversely, ATS failed to fully remove ECG contamination during muscular rest, yet did not introduce errors during muscle contraction. The relative advantages and disadvantages of different ECG contamination removal methods should be considered in the context of the specific motor tasks that require analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.
QRS Detection Algorithm for Telehealth Electrocardiogram Recordings.
Khamis, Heba; Weiss, Robert; Xie, Yang; Chang, Chan-Wei; Lovell, Nigel H; Redmond, Stephen J
2016-07-01
QRS detection algorithms are needed to analyze electrocardiogram (ECG) recordings generated in telehealth environments. However, the numerous published QRS detectors focus on clean clinical data. Here, a "UNSW" QRS detection algorithm is described that is suitable for clinical ECG and also poorer quality telehealth ECG. The UNSW algorithm generates a feature signal containing information about ECG amplitude and derivative, which is filtered according to its frequency content and an adaptive threshold is applied. The algorithm was tested on clinical and telehealth ECG and the QRS detection performance is compared to the Pan-Tompkins (PT) and Gutiérrez-Rivas (GR) algorithm. For the MIT-BIH Arrhythmia database (virtually artifact free, clinical ECG), the overall sensitivity (Se) and positive predictivity (+P) of the UNSW algorithm was >99%, which was comparable to PT and GR. When applied to the MIT-BIH noise stress test database (clinical ECG with added calibrated noise) after artifact masking, all three algorithms had overall Se >99%, and the UNSW algorithm had higher +P (98%, p < 0.05) than PT and GR. For 250 telehealth ECG records (unsupervised recordings; dry metal electrodes), the UNSW algorithm had 98% Se and 95% +P which was superior to PT (+P: p < 0.001) and GR (Se and +P: p < 0.001). This is the first study to describe a QRS detection algorithm for telehealth data and evaluate it on clinical and telehealth ECG with superior results to published algorithms. The UNSW algorithm could be used to manage increasing telehealth ECG analysis workloads.
Gu, Jiwei; Andreasen, Jan J; Melgaard, Jacob; Lundbye-Christensen, Søren; Hansen, John; Schmidt, Erik B; Thorsteinsson, Kristinn; Graff, Claus
2017-02-01
To investigate if electrocardiogram (ECG) markers from routine preoperative ECGs can be used in combination with clinical data to predict new-onset postoperative atrial fibrillation (POAF) following cardiac surgery. Retrospective observational case-control study. Single-center university hospital. One hundred consecutive adult patients (50 POAF, 50 without POAF) who underwent coronary artery bypass grafting, valve surgery, or combinations. Retrospective review of medical records and registration of POAF. Clinical data and demographics were retrieved from the Western Denmark Heart Registry and patient records. Paper tracings of preoperative ECGs were collected from patient records, and ECG measurements were read by two independent readers blinded to outcome. A subset of four clinical variables (age, gender, body mass index, and type of surgery) were selected to form a multivariate clinical prediction model for POAF and five ECG variables (QRS duration, PR interval, P-wave duration, left atrial enlargement, and left ventricular hypertrophy) were used in a multivariate ECG model. Adding ECG variables to the clinical prediction model significantly improved the area under the receiver operating characteristic curve from 0.54 to 0.67 (with cross-validation). The best predictive model for POAF was a combined clinical and ECG model with the following four variables: age, PR-interval, QRS duration, and left atrial enlargement. ECG markers obtained from a routine preoperative ECG may be helpful in predicting new-onset POAF in patients undergoing cardiac surgery. Copyright © 2017 Elsevier Inc. All rights reserved.
ECG findings in comparison to cardiovascular MR imaging in viral myocarditis.
Deluigi, Claudia C; Ong, Peter; Hill, Stephan; Wagner, Anja; Kispert, Eva; Klingel, Karin; Kandolf, Reinhard; Sechtem, Udo; Mahrholdt, Heiko
2013-04-30
We sought (1) to assess prevalence and type of ECG abnormalities in patients with biopsy proven myocarditis and signs of myocardial damage indicated by LGE, and (2) to evaluate whether ECG abnormalities are related to the pattern of myocardial damage. Prevalence and type of ECG abnormalities in patients presenting biopsy proven myocarditis, as well as any relation between ECG abnormalities and the in vivo pattern of myocardial damage are unknown. Eighty-four consecutive patients fulfilled the following criteria: (1) newly diagnosed biopsy proven viral myocarditis, and (2) non-ischemic LGE, and (3) standard 12-lead-ECG upon admission. Sixty-five patients with biopsy proven myocarditis had abnormal ECGs upon admission (77%). In this group, ST-abnormalities were detected most frequently (69%), followed by bundle-branch-block in 26%, and Q-waves in 8%. Atrial fibrillation was present in 6%, and AV-Block in two patients. In patients with septal LGE ST-abnormalities were more frequently located in anterolateral leads compared to patients with lateral LGE, in whom ST-abnormalities were most frequently observed in inferolateral leads. Bundle-branch-block occurred more often in patients with septal LGE (11/17). Four of five patients with Q-waves had severe and almost transmural LGE in the lateral wall. ECG abnormalities can be found in most patients with biopsy proven viral myocarditis at initial presentation. However, similar to suspected acute myocardial infarction, a normal ECG does not rule out myocarditis. ECG findings are related to the amount and area of damage as indicated by LGE, which confirms the important clinical role of ECG. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Contreras-Villarreal, Viridiana; Meza-Herrera, César A; Rivas-Muñoz, Raymundo; Angel-Garcia, Oscar; Luna-Orozco, Juan R; Carrillo, Evaristo; Mellado, Miguel; Véliz-Deras, Francisco G
2016-06-01
Adult goats (n = 32) were randomly assigned to one of four treatments (n = 8, each): (i) progesterone (P4 ) + equine chorionic gonadotropin (eCG), treated with 25 mg progesterone intramuscularly (i.m.) + 250 IU eCG 24 h later; (ii) cronolone + eCG, treated with vaginal sponges - 20 mg cronolone × 7 days + 250 IU eCG at pessary removal; (ii) P4 + estradiol (E2 ), treated with 25 mg progesterone i.m. + 1 mg estradiol 24 h later; (iv) cronolone + E2 , treated with vaginal sponges - 20 mg cronolone × 7 days + 1 mg of estradiol i.m. at pessary removal. Goats were tested for estrus throughout the presence of a buck. Seven days prior and after treatment, an ovarian ultrasonographic scanning was performed to determine ovarian function and structures. An ultrasonographic pregnancy diagnosis was performed on day 30 post-service. In all groups, 100% estrus response was observed within 96 h post-treatment. While ovulation occurred in 100% of P4 + eCG and cronolone + eCG treated goats, the other groups only depicted 50% ovulatory activity (P < 0.05). Pregnancy rate was higher (P <0.05) in the P4 + eCG and cronolone + eCG groups (88 and 100%, respectively), compared with 38% in P4 + E2 and cronolone + E2 groups. The best treatments were those in which eCG was applied. The P4 + eCG treatment was a pessary-free, cheaper and effective protocol to induce ovulation in goats during the seasonal anovulatory period. © 2015 Japanese Society of Animal Science.
Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation.
Sidek, Khairul Azami; Khalil, Ibrahim
2013-01-01
Electrocardiogram (ECG) based biometric matching suffers from high misclassification error with lower sampling frequency data. This situation may lead to an unreliable and vulnerable identity authentication process in high security applications. In this paper, quality enhancement techniques for ECG data with low sampling frequency has been proposed for person identification based on piecewise cubic Hermite interpolation (PCHIP) and piecewise cubic spline interpolation (SPLINE). A total of 70 ECG recordings from 4 different public ECG databases with 2 different sampling frequencies were applied for development and performance comparison purposes. An analytical method was used for feature extraction. The ECG recordings were segmented into two parts: the enrolment and recognition datasets. Three biometric matching methods, namely, Cross Correlation (CC), Percent Root-Mean-Square Deviation (PRD) and Wavelet Distance Measurement (WDM) were used for performance evaluation before and after applying interpolation techniques. Results of the experiments suggest that biometric matching with interpolated ECG data on average achieved higher matching percentage value of up to 4% for CC, 3% for PRD and 94% for WDM. These results are compared with the existing method when using ECG recordings with lower sampling frequency. Moreover, increasing the sample size from 56 to 70 subjects improves the results of the experiment by 4% for CC, 14.6% for PRD and 0.3% for WDM. Furthermore, higher classification accuracy of up to 99.1% for PCHIP and 99.2% for SPLINE with interpolated ECG data as compared of up to 97.2% without interpolation ECG data verifies the study claim that applying interpolation techniques enhances the quality of the ECG data. Crown Copyright © 2012. Published by Elsevier Ireland Ltd. All rights reserved.
Subcutaneous ICD screening with the Boston Scientific ZOOM programmer versus a 12-lead ECG machine.
Chang, Shu C; Patton, Kristen K; Robinson, Melissa R; Poole, Jeanne E; Prutkin, Jordan M
2018-02-24
The subcutaneous implantable cardioverter-defibrillator (S-ICD) requires preimplant screening to ensure appropriate sensing and reduce risk of inappropriate shocks. Screening can be performed using either an ICD programmer or a 12-lead electrocardiogram (ECG) machine. It is unclear whether differences in signal filtering and digital sampling change the screening success rate. Subjects were recruited if they had a transvenous single-lead ICD without pacing requirements or were candidates for a new ICD. Screening was performed using both a Boston Scientific ZOOM programmer (Marlborough, MA, USA) and General Electric MAC 5000 ECG machine (Fairfield, CT, USA). A pass was defined as having at least one lead that fit within the screening template in both supine and sitting positions. A total of 69 subjects were included and 27 sets of ECG leads had differing screening results between the two machines (7%). Of these sets, 22 (81%) passed using the ECG machine but failed using the programmer and five (19%) passed using the ECG machine but failed using the programmer (P < 0.001). Four subjects (6%) passed screening using the ECG machine but failed using the programmer. No subject passed screening with the programmer but failed with the ECG machine. There can be occasional disagreement in S-ICD patient screening between an ICD programmer and ECG machine, all of whom passed with the ECG machine but failed using the programmer. On a per lead basis, the ECG machine passes more subjects. It is unknown what the inappropriate shock rate would be if an S-ICD was implanted. Clinical judgment should be used in borderline cases. © 2018 Wiley Periodicals, Inc.
Potential Cost-Effectiveness of Ambulatory Cardiac Rhythm Monitoring After Cryptogenic Stroke.
Yong, Jean Hai Ein; Thavorn, Kednapa; Hoch, Jeffrey S; Mamdani, Muhammad; Thorpe, Kevin E; Dorian, Paul; Sharma, Mike; Laupacis, Andreas; Gladstone, David J
2016-09-01
Prolonged ambulatory ECG monitoring after cryptogenic stroke improves detection of covert atrial fibrillation, but its long-term cost-effectiveness is uncertain. We estimated the cost-effectiveness of noninvasive ECG monitoring in patients aged ≥55 years after a recent cryptogenic stroke and negative 24-hour ECG. A Markov model used observed rates of atrial fibrillation detection and anticoagulation from a randomized controlled trial (EMBRACE) and the published literature to predict lifetime costs and effectiveness (ischemic strokes, hemorrhages, life-years, and quality-adjusted life-years [QALYs]) for 30-day ECG (primary analysis) and 7-day or 14-day ECG (secondary analysis), when compared with a repeat 24-hour ECG. Prolonged ECG monitoring (7, 14, or 30 days) was predicted to prevent more ischemic strokes, decrease mortality, and improve QALYs. If anticoagulation reduced stroke risk by 50%, 30-day ECG (at a cost of USD $447) would be highly cost-effective ($2000 per QALY gained) for patients with a 4.5% annual ischemic stroke recurrence risk. Cost-effectiveness was sensitive to stroke recurrence risk and anticoagulant effectiveness, which remain uncertain, especially at higher costs of monitoring. Shorter duration (7 or 14 days) monitoring was cost saving and more effective than an additional 24-hour ECG; its cost-effectiveness was less sensitive to changes in ischemic stroke risk and treatment effect. After a cryptogenic stroke, 30-day ECG monitoring is likely cost-effective for preventing recurrent strokes; 14-day monitoring is an attractive value alternative, especially for lower risk patients. These results strengthen emerging recommendations for prolonged ECG monitoring in secondary stroke prevention. Cost-effectiveness in practice will depend on careful patient selection. © 2016 American Heart Association, Inc.
Wang, Jing; Yang, Bing; Chen, Hongwu; Ju, Weizhu; Chen, Kai; Zhang, Fengxiang; Cao, Kejiang; Chen, Minglong
2010-01-01
We analyzed the shape and distribution of epsilon waves by 3 various methods of electrocardiographic recording in patients with arrhythmogenic right ventricular cardiomyopathy. Thirty-two patients who met recognized diagnostic criteria for arrhythmogenic right ventricular cardiomyopathy were included in this study (24 men and 8 women; mean age, 42.3 ± 12.9 yr). Epsilon waves were detected by standard 12-lead electrocardiography (S-ECG), right-sided precordial lead electrocardiography (R-ECG), and Fontaine bipolar precordial lead electrocardiography (F-ECG). We found 3 types of epsilon waves: wiggle waves, small spike waves, and smooth potential waves that formed an atypical prolonged R' wave. The most common configuration was small spiked waves. In some circumstances, epsilon waves were evident in some leads (especially in leads V1 through V3), but notches were recorded in the other leads during the corresponding phase. These waves could be detected only by S-ECG in 1 patient, R-ECG in 3 patients, and F-ECG in 5 patients; the rates of epsilon-wave detection by these 3 methods were 38% (12/32), 38% (12/32), and 50% (16/32), respectively. However, the detection rate using combined methods was significantly higher than that by S-ECG alone (SF-ECG 56% vs S-ECG 38%, P = 0.0312; and SRF-ECG 66% vs S-ECG 38%, P = 0.0039). In addition, the rate of widespread T-wave inversion (exceeding V3) was significantly higher in patients with epsilon waves than in those without (48% vs 9%, P = 0.029), as was ventricular tachycardia (95% vs 64%, P = 0.019). These 3 electrocardiographic recording methods should be used in combination to improve the detection rate of epsilon waves. PMID:20844612
Orphanidou, Christina
2017-02-01
A new method for extracting the respiratory rate from ECG and PPG obtained via wearable sensors is presented. The proposed technique employs Ensemble Empirical Mode Decomposition in order to identify the respiration "mode" from the noise-corrupted Heart Rate Variability/Pulse Rate Variability and Amplitude Modulation signals extracted from ECG and PPG signals. The technique was validated with respect to a Respiratory Impedance Pneumography (RIP) signal using the mean absolute and the average relative errors for a group ambulatory hospital patients. We compared approaches using single respiration-induced modulations on the ECG and PPG signals with approaches fusing the different modulations. Additionally, we investigated whether the presence of both the simultaneously recorded ECG and PPG signals provided a benefit in the overall system performance. Our method outperformed state-of-the-art ECG- and PPG-based algorithms and gave the best results over the whole database with a mean error of 1.8bpm for 1min estimates when using the fused ECG modulations, which was a relative error of 10.3%. No statistically significant differences were found when comparing the ECG-, PPG- and ECG/PPG-based approaches, indicating that the PPG can be used as a valid alternative to the ECG for applications using wearable sensors. While the presence of both the ECG and PPG signals did not provide an improvement in the estimation error, it increased the proportion of windows for which an estimate was obtained by at least 9%, indicating that the use of two simultaneously recorded signals might be desirable in high-acuity cases where an RR estimate is required more frequently. Copyright © 2016 Elsevier Ltd. All rights reserved.
Jangra, Kiran; Grover, Vinod K; Bhagat, Hemant; Bhardwaj, Avanish; Tewari, Manoj K; Kumar, Bhupesh; Panda, Nidhi B; Sahu, Seelora
2017-07-01
Electrocardiographic (ECG) and echocardiographic changes that are subsequent to aneurysmal subarachnoid hemorrhage (a-SAH) are commonly observed with a prevalence varying from 27% to 100% and 13% to 18%, respectively. There are sparse data in the literature about the pattern of ECG and echocardiographic changes in patients with SAH after clipping of the aneurysm. Hence, we observed the effect of aneurysmal clipping on ECG and echocardiographic changes during the first week after surgery, and the impact of these changes on outcome at the end of 1 year. This prospective, observational study was conducted in 100 consecutive patients with a-SAH undergoing clipping of ruptured aneurysm. ECG and echocardiographic changes were recorded preoperatively and every day after surgery until 7 days. Outcome was evaluated using the Glasgow outcome scale at the end of 1 year. Of 100 patients, 75 had ECG changes and 17 had echocardiographic changes preoperatively. The ECG changes observed were QTc prolongation, conduction defects, ST-wave and T-wave abnormalities, tachyarrhythmias, and bradyarrhythmias. The echocardiography changes included global hypokinesia and regional wall motion abnormalities. Both echocardiographic and ECG changes showed significant recovery on the first postoperative day. Patients presenting with both echocardiographic and ECG changes were found to require higher ionotropic support to maintain the desired blood pressure, and were associated with poor outcome (Glasgow outcome scale, 1 to 2) at 1 year after surgery. There was no association of ECG and echocardiographic changes with mortality (both in-hospital or at 1 year). The ECG changes, such as QTc prolongation, bradycardia, conduction abnormality, and echocardiographic changes, recover on postoperative day-1, in most of the cases after clipping. Patients with combined ECG and echocardiographic changes tend to have poor neurological outcome at the end of 1 year.
Leigh, J Adam; O'Neal, Wesley T; Soliman, Elsayed Z
2016-06-01
Left ventricular hypertrophy (LVH) diagnosed by electrocardiography (ECG-LVH) and echocardiography (echo-LVH) are independently associated with an increased risk of cardiovascular disease (CVD) events. However, it is unknown if ECG-LVH retains its predictive properties independent of LV anatomy. We compared the risk of CVD associated with ECG-LVH and echo-LVH in 4,076 participants (41% men, 86% white) from the Cardiovascular Health Study, who were free of baseline CVD. ECG-LVH was defined with Minnesota ECG Classification criteria from baseline ECG data. Echo-LVH was defined by gender-specific LV mass values normalized to body surface area (male: >102 g/m(2); female: >88 g/m(2)). ECG-LVH was detected in 144 participants (3.5%) and echo-LVH in 430 participants (11%). Over a median follow-up of 10.6 years, 2,274 CVD events occurred. In a multivariate Cox regression analysis adjusted for common CVD risk factors, ECG-LVH (hazard ratio [HR] 1.84, 95% CI 1.51 to 2.24) and echo-LVH (HR 1.35, 95% CI 1.19 to 1.54) were associated with an increased risk for CVD events. The association between ECG-LVH and CVD events was not substantively altered with further adjustment for echo-LVH (HR 1.76, 95% CI 1.45 to 2.15). In conclusion, the association of ECG-LVH with CVD events is not dependent on echo-LVH. This finding provides support to the concept that ECG-LVH is an electrophysiological marker with predictive properties independent of LV anatomy. Copyright © 2016 Elsevier Inc. All rights reserved.
Exercise ECG; ECG - exercise treadmill; EKG - exercise treadmill; Stress ECG; Exercise electrocardiography; Stress test - exercise treadmill; CAD - treadmill; Coronary artery disease - treadmill; Chest pain - treadmill; Angina - treadmill; ...
Self-gated golden angle spiral cine MRI for coronary endothelial function assessment.
Bonanno, Gabriele; Hays, Allison G; Weiss, Robert G; Schär, Michael
2018-08-01
Depressed coronary endothelial function (CEF) is a marker for atherosclerotic disease, an independent predictor of cardiovascular events, and can be quantified non-invasively with ECG-triggered spiral cine MRI combined with isometric handgrip exercise (IHE). However, MRI-CEF measures can be hindered by faulty ECG-triggering, leading to prolonged breath-holds and degraded image quality. Here, a self-gated golden angle spiral method (SG-GA) is proposed to eliminate the need for ECG during cine MRI. SG-GA was tested against retrospectively ECG-gated golden angle spiral MRI (ECG-GA) and gold-standard ECG-triggered spiral cine MRI (ECG-STD) in 10 healthy volunteers. CEF data were obtained from cross-sectional images of the proximal right and left coronary arteries in a 3T scanner. Self-gating heart rates were compared to those from simultaneous ECG-gating. Coronary vessel sharpness and cross-sectional area (CSA) change with IHE were compared among the 3 methods. Self-gating precision, accuracy, and correlation-coefficient were 7.7 ± 0.5 ms, 9.1 ± 0.7 ms, and 0.93 ± 0.01, respectively (mean ± standard error). Vessel sharpness by SG-GA was equal or higher than ECG-STD (rest: 63.0 ± 1.7% vs. 61.3 ± 1.3%; exercise: 62.6 ± 1.3% vs. 56.7 ± 1.6%, P < 0.05). CSA changes were in agreement among the 3 methods (ECG-STD = 8.7 ± 4.0%, ECG-GA = 9.6 ± 3.1%, SG-GA = 9.1 ± 3.5%, P = not significant). CEF measures can be obtained with the proposed self-gated high-quality cine MRI method even when ECG is faulty or not available. Magn Reson Med 80:560-570, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Identifying QT prolongation from ECG impressions using a general-purpose Natural Language Processor
Denny, Joshua C.; Miller, Randolph A.; Waitman, Lemuel Russell; Arrieta, Mark; Peterson, Joshua F.
2009-01-01
Objective Typically detected via electrocardiograms (ECGs), QT interval prolongation is a known risk factor for sudden cardiac death. Since medications can promote or exacerbate the condition, detection of QT interval prolongation is important for clinical decision support. We investigated the accuracy of natural language processing (NLP) for identifying QT prolongation from cardiologist-generated, free-text ECG impressions compared to corrected QT (QTc) thresholds reported by ECG machines. Methods After integrating negation detection to a locally-developed natural language processor, the KnowledgeMap concept identifier, we evaluated NLP-based detection of QT prolongation compared to the calculated QTc on a set of 44,318 ECGs obtained from hospitalized patients. We also created a string query using regular expressions to identify QT prolongation. We calculated sensitivity and specificity of the methods using manual physician review of the cardiologist-generated reports as the gold standard. To investigate causes of “false positive” calculated QTc, we manually reviewed randomly selected ECGs with a long calculated QTc but no mention of QT prolongation. Separately, we validated the performance of the negation detection algorithm on 5,000 manually-categorized ECG phrases for any medical concept (not limited to QT prolongation) prior to developing the NLP query for QT prolongation. Results The NLP query for QT prolongation correctly identified 2,364 of 2,373 ECGs with QT prolongation with a sensitivity of 0.996 and a positive predictive value of 1.000. There were no false positives. The regular expression query had a sensitivity of 0.999 and positive predictive value of 0.982. In contrast, the positive predictive value of common QTc thresholds derived from ECG machines was 0.07–0.25 with corresponding sensitivities of 0.994–0.046. The negation detection algorithm had a recall of 0.973 and precision of 0.982 for 10,490 concepts found within ECG impressions. Conclusions NLP and regular expression queries of cardiologists’ ECG interpretations can more effectively identify QT prolongation than the automated QTc intervals reported by ECG machines. Future clinical decision support could employ NLP queries to detect QTc prolongation and other reported ECG abnormalities. PMID:18938105
Jørgensen, Peter G; Jensen, Jan S; Appleyard, Merete; Jensen, Gorm B; Mogelvang, Rasmus
2015-12-15
Though the electrocardiogram(ECG) and plasma pro-brain-natriuretic-peptide (pro-BNP) are widely used markers of subclinical cardiac injury and can be used to predict future cardiovascular disease(CVD), they could merely be markers of the same underlying pathology. We aimed to determine if ECG changes and pro-BNP are independent predictors of CVD and if the combination improves risk prediction in persons without known heart disease. Pro-BNP and ECG were obtained on 5454 persons without known heart disease from the 4th round of the Copenhagen City Heart Study, a prospective cohort study. Median follow-up was 10.4 years. High pro-BNP was defined as above 90th percentile of age and sex adjusted levels. The end-points were all-cause mortality and the combination of admission with ischemic heart disease, heart failure or CVD death. ECG changes were present in 907 persons and were associated with high levels of pro-BNP. In a fully adjusted model both high pro-BNP and ECG changes remained significant predictors: all-cause mortality(high pro-BNP, no ECG changes: HR: 1.43(1.12-1.82);P=0.005, low pro-BNP, ECG changes: HR: 1.22(1.05-1.42);P=0.009, and both high pro-BNP and ECG changes: HR: 1.99(1.54-2.59);P<0.001), CVD event(high pro-BNP, no ECG changes: HR: 1.94(1.45-2.58);P<0.001, low pro-BNP, ECG changes: HR: 1.55(1.29-1.87);P<0.001, and both high pro-BNP and ECG changes: HR: 3.86(2.94-5.08);P<0.001). Adding the combination of pro-BNP and ECG changes to a fully adjusted model correctly reclassified 33.9%(26.5-41.3);P<0.001 on the continuous net reclassification scale for all-cause mortality and 49.7%(41.1-58.4);P<0.001 for CVD event. Combining ECG changes and pro-BNP improves risk prediction in persons without known heart disease. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Fearnot, N E; Kitoh, O; Fujita, T; Okamura, H; Smith, H J; Calderini, M
1989-05-01
The effectiveness of using blood temperature change as an indicator to automatically vary heart rate physiologically was evaluated in 3 patients implanted with Model Sensor Kelvin 500 (Cook Pacemaker Corporation, Leechburg, PA, USA) pacemakers. Each patient performed two block-randomized treadmill exercise tests: one while programmed for temperature-based, rate-modulated pacing and the other while programmed without rate modulation. In 1 pacemaker patient and 4 volunteers, heart rates were recorded during exposure to a hot water bath. Blood temperature measured at 10 sec intervals and pacing rate measured at 1 min intervals were telemetered to a diagnostic programmer and data collector for storage and transfer to a computer. Observation comments and ECG-derived heart rates were manually recorded. The temperature-based pacemaker was shown to respond promptly not only to physical exertion but also to emotionally caused stress and submersion in a hot bath. These events cause increased heart rate in the normal heart. Using a suitable algorithm to process the measurement of blood temperature, it was possible to produce appropriate pacing rates in paced patients.
Accurate Interpretation of the 12-Lead ECG Electrode Placement: A Systematic Review
ERIC Educational Resources Information Center
Khunti, Kirti
2014-01-01
Background: Coronary heart disease (CHD) patients require monitoring through ECGs; the 12-lead electrocardiogram (ECG) is considered to be the non-invasive gold standard. Examples of incorrect treatment because of inaccurate or poor ECG monitoring techniques have been reported in the literature. The findings that only 50% of nurses and less than…
Kim, Hyejung; Van Hoof, Chris; Yazicioglu, Refet Firat
2011-01-01
This paper describes a mixed-signal ECG processing platform with an 12-bit ADC architecture that can adapt its sampling rate according to the input signals rate of change. This enables the sampling of ECG signals with significantly reduced data rate without loss of information. The presented adaptive sampling scheme reduces the ADC power consumption, enables the processing of ECG signals with lower power consumption, and reduces the power consumption of the radio while streaming the ECG signals. The test results show that running a CWT-based R peak detection algorithm using the adaptively sampled ECG signals consumes only 45.6 μW and it leads to 36% less overall system power consumption.
ECG Signal Analysis and Arrhythmia Detection using Wavelet Transform
NASA Astrophysics Data System (ADS)
Kaur, Inderbir; Rajni, Rajni; Marwaha, Anupma
2016-12-01
Electrocardiogram (ECG) is used to record the electrical activity of the heart. The ECG signal being non-stationary in nature, makes the analysis and interpretation of the signal very difficult. Hence accurate analysis of ECG signal with a powerful tool like discrete wavelet transform (DWT) becomes imperative. In this paper, ECG signal is denoised to remove the artifacts and analyzed using Wavelet Transform to detect the QRS complex and arrhythmia. This work is implemented in MATLAB software for MIT/BIH Arrhythmia database and yields the sensitivity of 99.85 %, positive predictivity of 99.92 % and detection error rate of 0.221 % with wavelet transform. It is also inferred that DWT outperforms principle component analysis technique in detection of ECG signal.
Kellogg, Adam R.; Coute, Ryan A.; Garra, Gregory
2015-01-01
Background Fatigue and sleepiness contribute to medical errors, although the effect of circadian disruption and fatigue on diagnostic reasoning skills is largely unknown. Objective To determine whether circadian disruption and fatigue negatively affect the emergency medicine (EM) resident's ability to make important clinical decisions based on electrocardiogram (ECG) interpretation. Methods Senior EM residents at 2 programs completed a questionnaire consisting of various measures of fatigue followed by an ECG test packet of ST-segment elevation myocardial infarction (STEMI) and STEMI mimics. Participants were asked to examine each ECG and determine whether cardiac catheterization laboratory activation (CLA) was indicated, and to report their confidence in their decision making on an 11-point, numeric rating scale. The primary outcome measured was a pairwise difference in accuracy of CLA between daytime and overnight testing. Results A total of 23 residents were enrolled in 2011 and 2012. Subjects demonstrated significant differences in multiple measures of sleepiness and fatigue during overnight periods. The median (interquartile range [IQR]) accuracy of CLA was not significantly different between daytime and overnight (70% [IQR, 50–80] versus 70% [IQR, 60–70], P = .82). There were no significant differences in the median number of overcalls (CLA when not a STEMI) and undercalls (no CLA when a STEMI was present; P = .57 and .37, respectively). Diagnostic confidence and confidence in CLA were not statistically different between daytime and overnight. Conclusions Despite a measurable degree of fatigue, senior EM residents experienced no decrease in their ability to accurately make CLA decisions based on ECG interpretation. PMID:26217418
Kellogg, Adam R; Coute, Ryan A; Garra, Gregory
2015-03-01
Fatigue and sleepiness contribute to medical errors, although the effect of circadian disruption and fatigue on diagnostic reasoning skills is largely unknown. To determine whether circadian disruption and fatigue negatively affect the emergency medicine (EM) resident's ability to make important clinical decisions based on electrocardiogram (ECG) interpretation. Senior EM residents at 2 programs completed a questionnaire consisting of various measures of fatigue followed by an ECG test packet of ST-segment elevation myocardial infarction (STEMI) and STEMI mimics. Participants were asked to examine each ECG and determine whether cardiac catheterization laboratory activation (CLA) was indicated, and to report their confidence in their decision making on an 11-point, numeric rating scale. The primary outcome measured was a pairwise difference in accuracy of CLA between daytime and overnight testing. A total of 23 residents were enrolled in 2011 and 2012. Subjects demonstrated significant differences in multiple measures of sleepiness and fatigue during overnight periods. The median (interquartile range [IQR]) accuracy of CLA was not significantly different between daytime and overnight (70% [IQR, 50-80] versus 70% [IQR, 60-70], P = .82). There were no significant differences in the median number of overcalls (CLA when not a STEMI) and undercalls (no CLA when a STEMI was present; P = .57 and .37, respectively). Diagnostic confidence and confidence in CLA were not statistically different between daytime and overnight. Despite a measurable degree of fatigue, senior EM residents experienced no decrease in their ability to accurately make CLA decisions based on ECG interpretation.
Cardiovascular preparticipation screening practices of college team physicians.
Asplund, Chad A; Asif, Irfan M
2014-07-01
Determine the cardiovascular screening practices of college team physicians. Cross-sectional survey. Electronic mail with a link to a 9-item survey. American Medical Society for Sports Medicine college team physicians. Screening practices survey administered to college team physicians. Cardiovascular preparticipation screening practices including noninvasive cardiac screening (NICS) such as electrocardiogram (ECG) or echocardiogram. Two hundred twenty-four of 613 AMSSM members identifying themselves as college team physicians (36.5%) responded: National Collegiate Athletic Association Division I: 146, Division II: 41, Division III: 27, National Association of Intercollegiate Athletics: 8, and Junior College: 2. The majority (78%) of schools conducted the American Heart Association (AHA) 12-element history and physical examination. Division I institutions were more likely to add an ECG and/or echocardiogram (30%) to their preparticipation examination (PPE) compared with lower divisions (P < 0.0001). Those Division I schools using NICS were more likely to do so for all athletes (P < 0.001) or revenue generating sports (P < 0.001), whereas other institutions did so only for high-risk subgroups (P < 0.01). Lower division schools would consider adding ECG if it cost less (P = 0.01) or if there were more local expertise in athlete-specific interpretation standards (P = 0.04). Many National Collegiate Athletic Association Athletes Division I programs already use NICS to screen athletes, whereas a significant portion of lower division schools add ECG for athletes deemed high risk. Increased use of these modalities suggests limitations of traditional PPE screening methods. This is the first study to assess cardiac screening practices across all collegiate divisions and broadens our understanding of cardiac screening in high-level athletes.
Kaiser, W; Faber, T S; Findeis, M
1996-01-01
The authors developed a computer program that detects myocardial infarction (MI) and left ventricular hypertrophy (LVH) in two steps: (1) by extracting parameter values from a 10-second, 12-lead electrocardiogram, and (2) by classifying the extracted parameter values with rule sets. Every disease has its dedicated set of rules. Hence, there are separate rule sets for anterior MI, inferior MI, and LVH. If at least one rule is satisfied, the disease is said to be detected. The computer program automatically develops these rule sets. A database (learning set) of healthy subjects and patients with MI, LVH, and mixed MI+LVH was used. After defining the rule type, initial limits, and expected quality of the rules (positive predictive value, minimum number of patients), the program creates a set of rules by varying the limits. The general rule type is defined as: disease = lim1l < p1 < or = lim1u and lim2l < p2 < or = lim2u and ... limnl < pn < or = limnu. When defining the rule types, only the parameters (p1 ... pn) that are known as clinical electrocardiographic criteria (amplitudes [mV] of Q, R, and T waves and ST-segment; duration [ms] of Q wave; frontal angle [degrees]) were used. This allowed for submitting the learned rule sets to an independent investigator for medical verification. It also allowed the creation of explanatory texts with the rules. These advantages are not offered by the neurons of a neural network. The learned rules were checked against a test set and the following results were obtained: MI: sensitivity 76.2%, positive predictive value 98.6%; LVH: sensitivity 72.3%, positive predictive value 90.9%. The specificity ratings for MI are better than 98%; for LVH, better than 90%.
Aladmawi, Mohamed A; Pragliola, Claudio; Vriz, Olga; Galzerano, Domenico
2017-04-01
Obstruction of a mechanical aortic valve by pannus formation at the subvalvular level is a major long-term complication of aortic valve replacement (AVR). In fact, pannus is sometime difficult to differentiate from patient-prosthesis mismatch or valve thrombosis. In most cases cine-angiography and echocardiography, either transthoracic or transesophageal, cannot correctly visualize the complication when the leaflets show a normal mobility. Recent technological refinements made this difficult diagnosis possible by ECG-gated computed tomography (CT) scan which shows adequate images in 90% of the cases and can differentiate pannus from fresh and organized thrombus.
Pavletic, A J; Pao, M; Pine, D S; Luckenbaugh, D A; Rosing, D R
2014-01-01
While there is controversy regarding utility of screening electrocardiograms (ECGs) in competitive athletes and children exposed to psychostimulants, there is no data on the use of screening ECGs in psychiatric research. We aimed to examine the prevalence and clinical significance of ECG abnormalities and their impact on eligibility for studies. We analysed 500 consecutive ECG reports from physically healthy volunteers who had a negative cardiac history, normal cardiovascular examination and no other significant medical illnesses. For the purpose of this report, all ECGs were over-read by one cardiologist. The mean age of our cohort was 28.3 ± 8.0 years. A total of 112 (22.4%) ECGs were reported as abnormal (14.2%) or borderline (8.2%). These abnormalities were considered clinically insignificant in all but eight subjects (1.6%) who underwent evaluation with an echocardiogram. All echocardiograms were normal. No subject was excluded from studies. After the over-reading, no abnormalities or isolated bradycardia were present in 37 of 112 (33%) ECGs that were initially reported as abnormal or borderline, while minor abnormalities were found in 7 of 204 (3.4%) ECGs that were reported as normal. Although screening ECGs did not detect significant cardiac pathology or affect eligibility for our studies, over 20% of subjects were labelled as having an abnormal or borderline ECG which was incorrect in one-third of cases. Strategies to minimise unintended consequences of screening are discussed. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.
Validity of a heart rate monitor during work in the laboratory and on the Space Shuttle
NASA Technical Reports Server (NTRS)
Moore, A. D. Jr; Lee, S. M.; Greenisen, M. C.; Bishop, P.
1997-01-01
Accurate heart rate measurement during work is required for many industrial hygiene and ergonomics situations. The purpose of this investigation was to determine the validity of heart rate measurements obtained by a simple, lightweight, commercially available wrist-worn heart rate monitor (HRM) during work (cycle exercise) sessions conducted in the laboratory and also during the particularly challenging work environment of space flight. Three different comparisons were made. The first compared HRM data to simultaneous electrocardiogram (ECG) recordings of varying heart rates that were generated by an ECG simulator. The second compared HRM data to ECG recordings collected during work sessions of 14 subjects in the laboratory. Finally, ECG downlink and HRM data were compared in four astronauts who performed cycle exercise during space flight. The data were analyzed using regression techniques. The results were that the HRM recorded virtually identical heart rates compared with ECG recordings for the data set generated by an ECG simulator. The regression equation for the relationship between ECG versus HRM heart rate data during work in the laboratory was: ECG HR = 0.99 x (HRM) + 0.82 (r2 = 0.99). Finally, the agreement between ECG downlink data and HRM data during space flight was also very high, with the regression equation being: Downlink ECG HR = 1.05 x (HRM) -5.71 (r2 = 0.99). The results of this study indicate that the HRM provides accurate data and may be used to reliably obtain valid data regarding heart rate responses during work.
Kim, Dae-Weung; Kim, Myoung Hyoun; Kim, Chang Guhn
2016-03-01
Domain 5 of kinin-free high molecular weight kininogen inhibits the adhesion of many tumor cell lines, and it has been reported that the histidine-glycine-lysine (HGK)-rich region might be responsible for inhibition of cell adhesion. The authors developed HGK-containing hexapeptide, glutamic acid-cysteine-glycine (ECG)-HGK, and evaluated the utility of Tc-99m ECG-HGK for tumor imaging. Hexapeptide, ECG-HGK was synthesized using Fmoc solid-phase peptide synthesis. Radiolabeling efficiency was evaluated. The uptake of Tc-99m ECG-HGK within HT-1080 cells was evaluated in vitro. In HT-1080 tumor-bearing mice, gamma imaging and biodistribution studies were performed. The complexes Tc-99m ECG-HGK was prepared in high yield. The uptake of Tc-99m ECG-HGK within the HT-1080 tumor cells had been demonstrated by in vitro studies. The gamma camera imaging in the murine model showed that Tc-99m ECG-HGK was accumulated substantially in the HT-1080 tumor (tumor-to-muscle ratio = 5.7 ± 1.4 at 4 h), and the tumoral uptake was blocked by the co-injection of excess HGK (tumor-to-muscle ratio = 2.8 ± 0.6 at 4 h). In the present study, Tc-99m ECG-HGK was developed as a new tumor imaging agents. Our in vitro and in vivo studies revealed specific function of Tc-99m ECG-HGK for tumor imaging. Copyright © 2016 John Wiley & Sons, Ltd.
Diagnostic value of prehospital ECG in acute stroke patients.
Bobinger, Tobias; Kallmünzer, Bernd; Kopp, Markus; Kurka, Natalia; Arnold, Martin; Heider, Stefan; Schwab, Stefan; Köhrmann, Martin
2017-05-16
To investigate the diagnostic yield of prehospital ECG monitoring provided by emergency medical services in the case of suspected stroke. Consecutive patients with acute stroke admitted to our tertiary stroke center via emergency medical services and with available prehospital ECG were prospectively included during a 12-month study period. We assessed prehospital ECG recordings and compared the results to regular 12-lead ECG on admission and after continuous ECG monitoring at the stroke unit. Overall, 259 patients with prehospital ECG recording were included in the study (90.3% ischemic stroke, 9.7% intracerebral hemorrhage). Atrial fibrillation (AF) was detected in 25.1% of patients, second-degree or greater atrioventricular block in 5.4%, significant ST-segment elevation in 5.0%, and ventricular ectopy in 9.7%. In 18 patients, a diagnosis of new-onset AF with direct clinical consequences for the evaluation and secondary prevention of stroke was established by the prehospital recordings. In 2 patients, the AF episodes were limited to the prehospital period and were not detected by ECG on admission or during subsequent monitoring at the stroke unit. Of 126 patients (48.6%) with relevant abnormalities in the prehospital ECG, 16.7% received medical antiarrhythmic therapy during transport to the hospital, and 6.4% were transferred to a cardiology unit within the first 24 hours in the hospital. In a selected cohort of patients with stroke, the in-field recordings of the ECG detected a relevant rate of cardiac arrhythmia. The results can add to the in-hospital evaluation and should be considered in prehospital care of acute stroke. © 2017 American Academy of Neurology.
El B'charri, Oussama; Latif, Rachid; Elmansouri, Khalifa; Abenaou, Abdenbi; Jenkal, Wissam
2017-02-07
Since the electrocardiogram (ECG) signal has a low frequency and a weak amplitude, it is sensitive to miscellaneous mixed noises, which may reduce the diagnostic accuracy and hinder the physician's correct decision on patients. The dual tree wavelet transform (DT-WT) is one of the most recent enhanced versions of discrete wavelet transform. However, threshold tuning on this method for noise removal from ECG signal has not been investigated yet. In this work, we shall provide a comprehensive study on the impact of the choice of threshold algorithm, threshold value, and the appropriate wavelet decomposition level to evaluate the ECG signal de-noising performance. A set of simulations is performed on both synthetic and real ECG signals to achieve the promised results. First, the synthetic ECG signal is used to observe the algorithm response. The evaluation results of synthetic ECG signal corrupted by various types of noise has showed that the modified unified threshold and wavelet hyperbolic threshold de-noising method is better in realistic and colored noises. The tuned threshold is then used on real ECG signals from the MIT-BIH database. The results has shown that the proposed method achieves higher performance than the ordinary dual tree wavelet transform into all kinds of noise removal from ECG signal. The simulation results indicate that the algorithm is robust for all kinds of noises with varying degrees of input noise, providing a high quality clean signal. Moreover, the algorithm is quite simple and can be used in real time ECG monitoring.
Khush, Kiran K.; Menza, Rebecca; Nguyen, John; Goldstein, Benjamin A.; Zaroff, Jonathan G.; Drew, Barbara J.
2012-01-01
Background Current regulations require that all cardiac allograft offers for transplantation must include an interpreted 12-lead electrocardiogram (ECG). However, little is known about the expected ECG findings in potential organ donors, or the clinical significance of any identified abnormalities in terms of cardiac allograft function and suitability for transplantation. Methods and Results A single experienced reviewer interpreted the first ECG obtained after brainstem herniation in 980 potential organ donors managed by the California Transplant Donor Network from 2002-2007. ECG abnormalities were summarized, and associations between specific ECG findings and cardiac allograft utilization for transplantation were studied. ECG abnormalities were present in 51% of all cases reviewed. The most common abnormalities included voltage criteria for left ventricular hypertrophy (LVH), prolongation of the corrected QT interval (QTc), and repolarization changes (ST/T wave abnormalities). Fifty seven percent of potential cardiac allografts in this cohort were accepted for transplantation. LVH on ECG was a strong predictor of allograft non-utilization. No significant associations were seen between QTc prolongation, repolarization changes and allograft utilization for transplantation, after adjusting for donor clinical variables and echocardiographic findings. Conclusions We have performed the first comprehensive study of ECG findings in potential donors for cardiac transplantation. Many of the common ECG abnormalities seen in organ donors may result from the heightened state of sympathetic activation that occurs after brainstem herniation, and are not associated with allograft utilization for transplantation. PMID:22615333
Accuracy of pulse oximetry measurement of heart rate of newborn infants in the delivery room.
Kamlin, C Omar F; Dawson, Jennifer A; O'Donnell, Colm P F; Morley, Colin J; Donath, Susan M; Sekhon, Jasbir; Davis, Peter G
2008-06-01
To determine the accuracy of heart rate obtained by pulse oximetry (HR(PO)) relative to HR obtained by 3-lead electrocardiography (HR(ECG)) in newborn infants in the delivery room. Immediately after birth, a preductal PO sensor and ECG leads were applied. PO and ECG monitor displays were recorded by a video camera. Two investigators reviewed the videos. Every two seconds, 1 of the investigators recorded HR(PO) and indicators of signal quality from the oximeter while masked to ECG, whereas the other recorded HR(ECG) and ECG signal quality while masked to PO. HR(PO) and HR(ECG) measurements were compared using Bland-Altman analysis. We attended 92 deliveries; 37 infants were excluded due to equipment malfunction. The 55 infants studied had a mean (+/-standard deviation [SD]) gestational age of 35 (+/-3.7) weeks, and birth weight 2399 (+/-869) g. In total, we analyzed 5877 data pairs. The mean difference (+/-2 SD) between HR(ECG) and HR(PO) was -2 (+/-26) beats per minute (bpm) overall and -0.5 (+/-16) bpm in those infants who received positive-pressure ventilation and/or cardiac massage. The sensitivity and specificity of PO for detecting HR(ECG) <100 bpm was 89% and 99%, respectively. PO provided an accurate display of newborn infants' HR in the delivery room, including those infants receiving advanced resuscitation.
An effective and efficient compression algorithm for ECG signals with irregular periods.
Chou, Hsiao-Hsuan; Chen, Ying-Jui; Shiau, Yu-Chien; Kuo, Te-Son
2006-06-01
This paper presents an effective and efficient preprocessing algorithm for two-dimensional (2-D) electrocardiogram (ECG) compression to better compress irregular ECG signals by exploiting their inter- and intra-beat correlations. To better reveal the correlation structure, we first convert the ECG signal into a proper 2-D representation, or image. This involves a few steps including QRS detection and alignment, period sorting, and length equalization. The resulting 2-D ECG representation is then ready to be compressed by an appropriate image compression algorithm. We choose the state-of-the-art JPEG2000 for its high efficiency and flexibility. In this way, the proposed algorithm is shown to outperform some existing arts in the literature by simultaneously achieving high compression ratio (CR), low percent root mean squared difference (PRD), low maximum error (MaxErr), and low standard derivation of errors (StdErr). In particular, because the proposed period sorting method rearranges the detected heartbeats into a smoother image that is easier to compress, this algorithm is insensitive to irregular ECG periods. Thus either the irregular ECG signals or the QRS false-detection cases can be better compressed. This is a significant improvement over existing 2-D ECG compression methods. Moreover, this algorithm is not tied exclusively to JPEG2000. It can also be combined with other 2-D preprocessing methods or appropriate codecs to enhance the compression performance in irregular ECG cases.
Biometric and Emotion Identification: An ECG Compression Based Method.
Brás, Susana; Ferreira, Jacqueline H T; Soares, Sandra C; Pinho, Armando J
2018-01-01
We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.
Biometric and Emotion Identification: An ECG Compression Based Method
Brás, Susana; Ferreira, Jacqueline H. T.; Soares, Sandra C.; Pinho, Armando J.
2018-01-01
We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model. PMID:29670564
[An Algorithm to Eliminate Power Frequency Interference in ECG Using Template].
Shi, Guohua; Li, Jiang; Xu, Yan; Feng, Liang
2017-01-01
Researching an algorithm to eliminate power frequency interference in ECG. The algorithm first creates power frequency interference template, then, subtracts the template from the original ECG signals, final y, the algorithm gets the ECG signals without interference. Experiment shows the algorithm can eliminate interference effectively and has none side effect to normal signal. It’s efficient and suitable for practice.
[Lossless ECG compression algorithm with anti- electromagnetic interference].
Guan, Shu-An
2005-03-01
Based on the study of ECG signal features, a new lossless ECG compression algorithm is put forward here. We apply second-order difference operation with anti- electromagnetic interference to original ECG signals and then, compress the result by the escape-based coding model. In spite of serious 50Hz-interference, the algorithm is still capable of obtaining a high compression ratio.
Cleal, J K; Thomas, M; Hanson, M A; Paterson-Brown, S; Gardiner, H M; Green, L R
2010-03-01
To investigate whether a noninvasive fetal electrocardiography (fECG) system can identify cardiovascular responses to fetal hypoxaemia and validate the results using standard invasive fECG monitoring techniques. Prospective cohort study. Biological research facilities at The University of Southampton. Late gestation ovine fetuses; n = 5. Five fetal lambs underwent implantation of vascular catheters, umbilical cord occluder and invasive ECG chest electrodes under general anaesthesia (3% halothane/O(2)) at 119 days of gestation (term approximately 147 days of gestation). After 5 days of recovery blood pressure, blood gases, glucose and pH were monitored. At 124 and 125 days of gestation following a 10-minute baseline period a 90-second cord occlusion was applied. Noninvasive fetal ECG was recorded from maternal transabdominal electrodes using advanced signal-processing techniques, concurrently with invasive fECG recordings. Comparison of T:QRS ratios of the ECG waveform from noninvasive and invasive fECG monitoring systems. Our fECG monitoring system is able to demonstrate changes in waveforms during periods of hypoxaemia similar to those obtained invasively, which could indicate fetal distress. These findings may indicate a future use for noninvasive electrocardiography during human fetal monitoring both before and during labour in term and preterm pregnancies.
Flexible Graphene Electrodes for Prolonged Dynamic ECG Monitoring
Lou, Cunguang; Li, Ruikai; Li, Zhaopeng; Liang, Tie; Wei, Zihui; Run, Mingtao; Yan, Xiaobing; Liu, Xiuling
2016-01-01
This paper describes the development of a graphene-based dry flexible electrocardiography (ECG) electrode and a portable wireless ECG measurement system. First, graphene films on polyethylene terephthalate (PET) substrates and graphene paper were used to construct the ECG electrode. Then, a graphene textile was synthesized for the fabrication of a wearable ECG monitoring system. The structure and the electrical properties of the graphene electrodes were evaluated using Raman spectroscopy, scanning electron microscopy (SEM), and alternating current impedance spectroscopy. ECG signals were then collected from healthy subjects using the developed graphene electrode and portable measurement system. The results show that the graphene electrode was able to acquire the typical characteristics and features of human ECG signals with a high signal-to-noise (SNR) ratio in different states of motion. A week-long continuous wearability test showed no degradation in the ECG signal quality over time. The graphene-based flexible electrode demonstrates comfortability, good biocompatibility, and high electrophysiological detection sensitivity. The graphene electrode also combines the potential for use in long-term wearable dynamic cardiac activity monitoring systems with convenience and comfort for use in home health care of elderly and high-risk adults. PMID:27809270
Assurance of energy efficiency and data security for ECG transmission in BASNs.
Ma, Tao; Shrestha, Pradhumna Lal; Hempel, Michael; Peng, Dongming; Sharif, Hamid; Chen, Hsiao-Hwa
2012-04-01
With the technological advancement in body area sensor networks (BASNs), low cost high quality electrocardiographic (ECG) diagnosis systems have become important equipment for healthcare service providers. However, energy consumption and data security with ECG systems in BASNs are still two major challenges to tackle. In this study, we investigate the properties of compressed ECG data for energy saving as an effort to devise a selective encryption mechanism and a two-rate unequal error protection (UEP) scheme. The proposed selective encryption mechanism provides a simple and yet effective security solution for an ECG sensor-based communication platform, where only one percent of data is encrypted without compromising ECG data security. This part of the encrypted data is essential to ECG data quality due to its unequally important contribution to distortion reduction. The two-rate UEP scheme achieves a significant additional energy saving due to its unequal investment of communication energy to the outcomes of the selective encryption, and thus, it maintains a high ECG data transmission quality. Our results show the improvements in communication energy saving of about 40%, and demonstrate a higher transmission quality and security measured in terms of wavelet-based weighted percent root-mean-squared difference.
Tjolleng, Amir; Jung, Kihyo; Hong, Wongi; Lee, Wonsup; Lee, Baekhee; You, Heecheon; Son, Joonwoo; Park, Seikwon
2017-03-01
An artificial neural network (ANN) model was developed in the present study to classify the level of a driver's cognitive workload based on electrocardiography (ECG). ECG signals were measured on 15 male participants while they performed a simulated driving task as a primary task with/without an N-back task as a secondary task. Three time-domain ECG measures (mean inter-beat interval (IBI), standard deviation of IBIs, and root mean squared difference of adjacent IBIs) and three frequencydomain ECG measures (power in low frequency, power in high frequency, and ratio of power in low and high frequencies) were calculated. To compensate for individual differences in heart response during the driving tasks, a three-step data processing procedure was performed to ECG signals of each participant: (1) selection of two most sensitive ECG measures, (2) definition of three (low, medium, and high) cognitive workload levels, and (3) normalization of the selected ECG measures. An ANN model was constructed using a feed-forward network and scaled conjugate gradient as a back-propagation learning rule. The accuracy of the ANN classification model was found satisfactory for learning data (95%) and testing data (82%). Copyright © 2016 Elsevier Ltd. All rights reserved.
Electrocardiogram signal denoising based on a new improved wavelet thresholding
NASA Astrophysics Data System (ADS)
Han, Guoqiang; Xu, Zhijun
2016-08-01
Good quality electrocardiogram (ECG) is utilized by physicians for the interpretation and identification of physiological and pathological phenomena. In general, ECG signals may mix various noises such as baseline wander, power line interference, and electromagnetic interference in gathering and recording process. As ECG signals are non-stationary physiological signals, wavelet transform is investigated to be an effective tool to discard noises from corrupted signals. A new compromising threshold function called sigmoid function-based thresholding scheme is adopted in processing ECG signals. Compared with other methods such as hard/soft thresholding or other existing thresholding functions, the new algorithm has many advantages in the noise reduction of ECG signals. It perfectly overcomes the discontinuity at ±T of hard thresholding and reduces the fixed deviation of soft thresholding. The improved wavelet thresholding denoising can be proved to be more efficient than existing algorithms in ECG signal denoising. The signal to noise ratio, mean square error, and percent root mean square difference are calculated to verify the denoising performance as quantitative tools. The experimental results reveal that the waves including P, Q, R, and S waves of ECG signals after denoising coincide with the original ECG signals by employing the new proposed method.
NASA Astrophysics Data System (ADS)
Mishra, Puneet; Singla, Sunil Kumar
2013-01-01
In the modern world of automation, biological signals, especially Electroencephalogram (EEG) and Electrocardiogram (ECG), are gaining wide attention as a source of biometric information. Earlier studies have shown that EEG and ECG show versatility with individuals and every individual has distinct EEG and ECG spectrum. EEG (which can be recorded from the scalp due to the effect of millions of neurons) may contain noise signals such as eye blink, eye movement, muscular movement, line noise, etc. Similarly, ECG may contain artifact like line noise, tremor artifacts, baseline wandering, etc. These noise signals are required to be separated from the EEG and ECG signals to obtain the accurate results. This paper proposes a technique for the removal of eye blink artifact from EEG and ECG signal using fixed point or FastICA algorithm of Independent Component Analysis (ICA). For validation, FastICA algorithm has been applied to synthetic signal prepared by adding random noise to the Electrocardiogram (ECG) signal. FastICA algorithm separates the signal into two independent components, i.e. ECG pure and artifact signal. Similarly, the same algorithm has been applied to remove the artifacts (Electrooculogram or eye blink) from the EEG signal.
Unveiling the Biometric Potential of Finger-Based ECG Signals
Lourenço, André; Silva, Hugo; Fred, Ana
2011-01-01
The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications. PMID:21837235
Research of the Heart Information Monitoring Robert Based on the 3G Wireless Communication Platform
NASA Astrophysics Data System (ADS)
Zhang, Fuli; Yang, Huazhe; Li, Gensong; Hong, Yang; Hu, Qingzhe
Electrocardiogram (ECG) of a person can be recorded and the diagnostic results can be displayed through touching the heart information monitoring Robert. In addition, the heart rate, phonocardiogram (PCG) and the dynamic three-dimensional echocardiography can also be displayed synchronously. Then the difficult ECG can be transmitted to the service center through 3G wireless communication center, followed by diagnosing the ECG by doctors and transmitting the feedback diagnostic results. I-lead ECG of the person can be recorded by the amplification circuit with high gain and low noise. Then, the heart rate and output phonocardiogram are displayed and the model of heart beat are started to trace through the recognition of R wave. Finally, the difficult ECG is transmitted to the service center via 3G communication chips. The displayed ECG is clear, and the stimulated heart beat is synchronous with that of the person. Furthermore, ECG received by the service center is in accordance with the one recorded by the Robert.
A Real-Time Cardiac Arrhythmia Classification System with Wearable Sensor Networks
Hu, Sheng; Wei, Hongxing; Chen, Youdong; Tan, Jindong
2012-01-01
Long term continuous monitoring of electrocardiogram (ECG) in a free living environment provides valuable information for prevention on the heart attack and other high risk diseases. This paper presents the design of a real-time wearable ECG monitoring system with associated cardiac arrhythmia classification algorithms. One of the striking advantages is that ECG analog front-end and on-node digital processing are designed to remove most of the noise and bias. In addition, the wearable sensor node is able to monitor the patient's ECG and motion signal in an unobstructive way. To realize the real-time medical analysis, the ECG is digitalized and transmitted to a smart phone via Bluetooth. On the smart phone, the ECG waveform is visualized and a novel layered hidden Markov model is seamlessly integrated to classify multiple cardiac arrhythmias in real time. Experimental results demonstrate that the clean and reliable ECG waveform can be captured in multiple stressed conditions and the real-time classification on cardiac arrhythmia is competent to other workbenches. PMID:23112746
Effect of ECG filter settings on J-waves.
Nakagawa, Mikiko; Tsunemitsu, Chie; Katoh, Sayo; Kamiyama, Yukari; Sano, Nario; Ezaki, Kaori; Miyazaki, Hiroko; Teshima, Yasushi; Yufu, Kunio; Takahashi, Naohiko; Saikawa, Tetsunori
2014-01-01
While J-waves were observed in healthy populations, variations in their reported incidence may be partly explicable by the ECG filter setting. We obtained resting 12-lead ECG recordings in 665 consecutive patients and enrolled 112 (56 men, 56 women, mean age 59.3±16.1years) who manifested J-waves on ECGs acquired with a 150-Hz low-pass filter. We then studied the J-waves on individual ECGs to look for morphological changes when 25-, 35-, 75-, 100-, and 150Hz filters were used. The notching observed with the 150-Hz filter changed to slurring (42%) or was eliminated (28%) with the 25-Hz filter. Similarly, the slurring seen with the 150-Hz filter was eliminated on 71% of ECGs recorded with the 25-Hz filter. The amplitude of J-waves was significantly lower with 25- and 35-Hz than 75-, 100-, and 150-Hz filters (p<0.0001). The ECG filter setting significantly affects the J-wave morphology. © 2013.
Wiklund, Urban; Karlsson, Marcus; Ostlund, Nils; Berglin, Lena; Lindecrantz, Kaj; Karlsson, Stefan; Sandsjö, Leif
2007-06-01
Intermittent disturbances are common in ECG signals recorded with smart clothing: this is mainly because of displacement of the electrodes over the skin. We evaluated a novel adaptive method for spatio-temporal filtering for heartbeat detection in noisy multi-channel ECGs including short signal interruptions in single channels. Using multi-channel database recordings (12-channel ECGs from 10 healthy subjects), the results showed that multi-channel spatio-temporal filtering outperformed regular independent component analysis. We also recorded seven channels of ECG using a T-shirt with textile electrodes. Ten healthy subjects performed different sequences during a 10-min recording: resting, standing, flexing breast muscles, walking and pushups. Using adaptive multi-channel filtering, the sensitivity and precision was above 97% in nine subjects. Adaptive multi-channel spatio-temporal filtering can be used to detect heartbeats in ECGs with high noise levels. One application is heartbeat detection in noisy ECG recordings obtained by integrated textile electrodes in smart clothing.
Unveiling the biometric potential of finger-based ECG signals.
Lourenço, André; Silva, Hugo; Fred, Ana
2011-01-01
The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.
López, Débora N; Galante, Micaela; Alvarez, Estela M; Risso, Patricia H; Boeris, Valeria
2017-10-01
Model systems formed by sodium caseinate (NaCAS) and espina corona gum (ECG) were studied. There was no evidence of attractive interactions between NaCAS and ECG macromolecules. Aqueous mixtures of NaCAS and ECG phase-separate segregatively over a wide range of concentrations. According to the images obtained by confocal laser scanning microscopy, NaCAS particles form larger protein aggregates when ECG is present in the system. An increase in the hydrodynamic diameter of NaCAS particles, as a result of ECG addition, was also observed by light scattering in diluted systems. A depletion-flocculation phenomenon, in which ECG is excluded from NaCAS surface, is proposed to occur in the concentrated mixed systems, resulting in NaCAS aggregation. ECG raises the viscosity of NaCAS dispersions without affecting the Newtonian flow behaviour of NaCAS. These results contribute to improve the knowledge of a barely-studied hydrocolloid which may be useful in the development of innovative food systems. Copyright © 2017 Elsevier Ltd. All rights reserved.
[Leisure-time sport activities and cardiac outpatient therapy in coronary patients].
Heitkamp, Hans-Christian; Schimpf, Thomas M; Hipp, Arno; Niess, Andreas
2005-03-01
Exercise intensity in coronary patients is controlled by heart rate measurements. Very few investigations have compared the maximum heart rate in cardiac outpatient groups, in leisure-time sport activities, and especially in swimming. Within different exercise conditions 21 coronary patients, nine in well-compensated cardiac condition joining a training group and twelve joining the exercise group with lower intensity, without signs of heart failure, engaged in an incremental bicycle ergometry. A six-lead ECG was derived at the same time with a 24-h ECG. The performance tolerance was measured by the pulse limit derived in 20 patients; one patient failed to show signs of subjective or objective ischemia. During a 24-h ECG monitoring, the patients took part in a 1-h standardized cardiac outpatient program, a standardized swimming program 4 x 25 m, and a typical self-selected leisure-time activity. The patients showed a peak work capacity of 2.2 W/kg and a symptom-free work capacity of 1.3 W/kg. The derived upper heart rate limit was passed during swimming by 19, during leisure-time activity by 16, and during cardiac outpatient program by two patients. The maximum of the mean overriding the limit occurred in leisure-time activity. Signs of ischemia occurred during ergometry in 15, during swimming training in ten patients, during leisure-time activity in eight, and during cardiac outpatient therapy in one. Arrhythmia < Lown IVa was documented on the ergometer in 15, during leisure-time sport activity in 15, during cardiac outpatient therapy in 17, and during swimming in eight patients. Arrhythmia Lown IVa occurred in one patient each during ergometry, leisure sports, and during the night. Coronary patients are in danger to exercise beyond the pulse limit during swimming and other leisure-time sports and not during cardiac outpatient therapy. The upper heart rate limit should be observed during swimming and other endurance leisure-time activities, and is of little importance during cardiac outpatient therapy.
Güler, N; Bilge, M; Eryonucu, B; Cirak, B
2000-10-01
We report two cases of acute cervical angina and ECG changes induced by anteflexion of the head. Cervical angina is defined as chest pain that resembles true cardiac angina but originates from cervical discopathy with nerve root compression. In these patients, Prinzmetal's angina, valvular heart disease, congenital heart disease, left ventricular aneurysm, and cardiomyopathy were excluded. After all, the patient's chest pain was reproduced by anteflexion of head, at this time, their ECGs showed nonspecific ST-T changes in the inferior and anterior leads different from the basal ECG. ECG changes returned to normal when the patient's neck moved to the neutral position. To our knowledge, these are the first cases of cervical angina associated with acute ECG changes by neck motion.
[Development of a portable ambulatory ECG monitor based on embedded microprocessor unit].
Wang, Da-xiong; Wang, Guo-jun
2005-06-01
To develop a new kind of portable ambulatory ECG monitor. The hardware and software were designed based on RCA-CDP1802. New methods of ECG data compression and feature extraction of QRS complexes were applied to software design. A model for automatic arrhythmia analysis was established for real-time ambulatory ECG Data analysis. Compact, low power consumption and low cost were emphasized in the hardware design. This compact and light-weight monitor with low power consumption and high intelligence was capable of real-time monitoring arrhythmia for more than 48 h. More than ten types of arrhythmia could be detected, only the compressed abnormal ECG data was recorded and could be transmitted to the host if required. The monitor meets the design requirements and can be used for ambulatory ECG monitoring.
Noncontact ECG system for unobtrusive long-term monitoring.
McDonald, Neil J; Anumula, Harini A; Duff, Eric; Soussou, Walid
2012-01-01
This paper describes measurements made using an ECG system with QUASAR's capacitive bioelectrodes integrated into a pad system that is placed over a chair. QUASAR's capacitive bioelectrode has the property of measuring bioelectric potentials at a small separation from the body. This enables the measurement of ECG signals through fabric, without the removal of clothing or preparation of skin. The ECG was measured through the subject's clothing while the subject sat in the chair without any supporting action from the subject. The ECG pad system is an example of a high compliance system that places minimal requirements upon the subject and, consequently, can be used to generate a long-term record from ECG segments collected on a daily basis, providing valuable information on long-term trends in cardiac health.
Internet based ECG medical information system.
James, D A; Rowlands, D; Mahnovetski, R; Channells, J; Cutmore, T
2003-03-01
Physiological monitoring of humans for medical applications is well established and ready to be adapted to the Internet. This paper describes the implementation of a Medical Information System (MIS-ECG system) incorporating an Internet based ECG acquisition device. Traditionally clinical monitoring of ECG is largely a labour intensive process with data being typically stored on paper. Until recently, ECG monitoring applications have also been constrained somewhat by the size of the equipment required. Today's technology enables large and fixed hospital monitoring systems to be replaced by small portable devices. With an increasing emphasis on health management a truly integrated information system for the acquisition, analysis, patient particulars and archiving is now a realistic possibility. This paper describes recent Internet and technological advances and presents the design and testing of the MIS-ECG system that utilises those advances.
Angle-independent measure of motion for image-based gating in 3D coronary angiography
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lehmann, Glen C.; Holdsworth, David W.; Drangova, Maria
2006-05-15
The role of three-dimensional (3D) image guidance for interventional procedures and minimally invasive surgeries is increasing for the treatment of vascular disease. Currently, most interventional procedures are guided by two-dimensional x-ray angiography, but computed rotational angiography has the potential to provide 3D geometric information about the coronary arteries. The creation of 3D angiographic images of the coronary arteries requires synchronization of data acquisition with respect to the cardiac cycle, in order to minimize motion artifacts. This can be achieved by inferring the extent of motion from a patient's electrocardiogram (ECG) signal. However, a direct measurement of motion (from the 2Dmore » angiograms) has the potential to improve the 3D angiographic images by ensuring that only projections acquired during periods of minimal motion are included in the reconstruction. This paper presents an image-based metric for measuring the extent of motion in 2D x-ray angiographic images. Adaptive histogram equalization was applied to projection images to increase the sharpness of coronary arteries and the superior-inferior component of the weighted centroid (SIC) was measured. The SIC constitutes an image-based metric that can be used to track vessel motion, independent of apparent motion induced by the rotational acquisition. To evaluate the technique, six consecutive patients scheduled for routine coronary angiography procedures were studied. We compared the end of the SIC rest period ({rho}) to R-waves (R) detected in the patient's ECG and found a mean difference of 14{+-}80 ms. Two simultaneous angular positions were acquired and {rho} was detected for each position. There was no statistically significant difference (P=0.79) between {rho} in the two simultaneously acquired angular positions. Thus we have shown the SIC to be independent of view angle, which is critical for rotational angiography. A preliminary image-based gating strategy that employed the SIC was compared to an ECG-based gating strategy in a porcine model. The image-based gating strategy selected 61 projection images, compared to 45 selected by the ECG-gating strategy. Qualitative comparison revealed that although both the SIC-based and ECG-gated reconstructions decreased motion artifact compared to reconstruction with no gating, the SIC-based gating technique increased the conspicuity of smaller vessels when compared to ECG gating in maximum intensity projections of the reconstructions and increased the sharpness of a vessel cross section in multi-planar reformats of the reconstruction.« less
Electrocardiographic Findings in National Basketball Association Athletes.
Waase, Marc P; Mutharasan, R Kannan; Whang, William; DiTullio, Marco R; DiFiori, John P; Callahan, Lisa; Mancell, Jimmie; Phelan, Dermot; Schwartz, Allan; Homma, Shunichi; Engel, David J
2018-01-01
While it is known that long-term intensive athletic training is associated with cardiac structural changes that can be reflected on surface electrocardiograms (ECGs), there is a paucity of sport-specific ECG data. This study seeks to clarify the applicability of existing athlete ECG interpretation criteria to elite basketball players, an athlete group shown to develop significant athletic cardiac remodeling. To generate normative ECG data for National Basketball Association (NBA) athletes and to assess the accuracy of athlete ECG interpretation criteria in this population. The NBA has partnered with Columbia University Medical Center to annually perform a review of policy-mandated annual preseason ECGs and stress echocardiograms for all players and predraft participants. This observational study includes the preseason ECG examinations of NBA athletes who participated in the 2013-2014 and 2014-2015 seasons, plus all participants in the 2014 and 2015 NBA predraft combines. Examinations were performed from July 2013 to May 2015. Data analysis was performed between December 2015 and March 2017. Active roster or draft status in the NBA and routine preseason ECGs and echocardiograms. Baseline quantitative ECG variables were measured and ECG data qualitatively analyzed using 3 existing, athlete-specific interpretation criteria: Seattle (2012), refined (2014), and international (2017). Abnormal ECG findings were compared with matched echocardiographic data. Of 519 male athletes, 409 (78.8%) were African American, 96 (18.5%) were white, and the remaining 14 (2.7%) were of other races/ethnicities; 115 were predraft combine participants, and the remaining 404 were on active rosters of NBA teams. The mean (SD) age was 24.8 (4.3) years. Physiologic, training-related changes were present in 462 (89.0%) athletes in the study. Under Seattle criteria, 131 (25.2%) had abnormal findings, compared with 108 (20.8%) and 81 (15.6%) under refined and international criteria, respectively. Increased age and increased left ventricular relative wall thickness (RWT) on echocardiogram were highly associated with abnormal ECG classifications; 17 of 186 athletes (9.1%) in the youngest age group (age 18-22 years) had abnormal ECGs compared with 36 of the 159 athletes (22.6%) in the oldest age group (age 27-39 years) (odds ratio, 2.9; 95% CI, 1.6-5.4; P < .001). Abnormal T-wave inversions (TWI) were present in 32 athletes (6.2%), and this was associated with smaller left ventricular cavity size and increased RWT. One of the 172 athletes (0.6%) in the lowest RWT group (range, 0.24-0.35) had TWIs compared with 24 of the 163 athletes (14.7%) in the highest RWT group (range, 0.41-0.57) (odds ratio, 29.5; 95% CI, 3.9-221.0; P < .001). Despite the improved specificity of the international recommendations over previous athlete-specific ECG criteria, abnormal ECG classification rates remain high in NBA athletes. The development of left ventricular concentric remodeling appears to have a significant influence on the prevalence of abnormal ECG classification and repolarization abnormalities in this athlete group.
Use of the Surface Electrocardiogram to Define the Nature of Challenging Arrhythmias.
Singh, David K; Peter, C Thomas
2016-03-01
Despite unprecedented advances in technology, the electrocardiogram (ECG) remains essential to the practice of modern electrophysiology. Since its emergence at the turn of the nineteenth century, the form of the ECG has changed little. What has changed is our ability to understand the complex mechanisms that underlie various arrhythmias. In this article, the authors review several important principles of ECG interpretation by providing illustrative tracings. The authors also highlight several important concepts that be can used in ECG analysis. There are several fundamental principles that should be considered in ECG interpretation. Copyright © 2016 Elsevier Inc. All rights reserved.
Fetal QRS detection and heart rate estimation: a wavelet-based approach.
Almeida, Rute; Gonçalves, Hernâni; Bernardes, João; Rocha, Ana Paula
2014-08-01
Fetal heart rate monitoring is used for pregnancy surveillance in obstetric units all over the world but in spite of recent advances in analysis methods, there are still inherent technical limitations that bound its contribution to the improvement of perinatal indicators. In this work, a previously published wavelet transform based QRS detector, validated over standard electrocardiogram (ECG) databases, is adapted to fetal QRS detection over abdominal fetal ECG. Maternal ECG waves were first located using the original detector and afterwards a version with parameters adapted for fetal physiology was applied to detect fetal QRS, excluding signal singularities associated with maternal heartbeats. Single lead (SL) based marks were combined in a single annotator with post processing rules (SLR) from which fetal RR and fetal heart rate (FHR) measures can be computed. Data from PhysioNet with reference fetal QRS locations was considered for validation, with SLR outperforming SL including ICA based detections. The error in estimated FHR using SLR was lower than 20 bpm for more than 80% of the processed files. The median error in 1 min based FHR estimation was 0.13 bpm, with a correlation between reference and estimated FHR of 0.48, which increased to 0.73 when considering only records for which estimated FHR > 110 bpm. This allows us to conclude that the proposed methodology is able to provide a clinically useful estimation of the FHR.
Adaptive EMG noise reduction in ECG signals using noise level approximation
NASA Astrophysics Data System (ADS)
Marouf, Mohamed; Saranovac, Lazar
2017-12-01
In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.
Lewicke, Aaron; Sazonov, Edward; Corwin, Michael J; Neuman, Michael; Schuckers, Stephanie
2008-01-01
Reliability of classification performance is important for many biomedical applications. A classification model which considers reliability in the development of the model such that unreliable segments are rejected would be useful, particularly, in large biomedical data sets. This approach is demonstrated in the development of a technique to reliably determine sleep and wake using only the electrocardiogram (ECG) of infants. Typically, sleep state scoring is a time consuming task in which sleep states are manually derived from many physiological signals. The method was tested with simultaneous 8-h ECG and polysomnogram (PSG) determined sleep scores from 190 infants enrolled in the collaborative home infant monitoring evaluation (CHIME) study. Learning vector quantization (LVQ) neural network, multilayer perceptron (MLP) neural network, and support vector machines (SVMs) are tested as the classifiers. After systematic rejection of difficult to classify segments, the models can achieve 85%-87% correct classification while rejecting only 30% of the data. This corresponds to a Kappa statistic of 0.65-0.68. With rejection, accuracy improves by about 8% over a model without rejection. Additionally, the impact of the PSG scored indeterminate state epochs is analyzed. The advantages of a reliable sleep/wake classifier based only on ECG include high accuracy, simplicity of use, and low intrusiveness. Reliability of the classification can be built directly in the model, such that unreliable segments are rejected.
Electrocardiograms in Low-Risk Patients Undergoing an Annual Health Examination.
Bhatia, R Sacha; Bouck, Zachary; Ivers, Noah M; Mecredy, Graham; Singh, Jasjit; Pendrith, Ciara; Ko, Dennis T; Martin, Danielle; Wijeysundera, Harindra C; Tu, Jack V; Wilson, Lynn; Wintemute, Kimberly; Dorian, Paul; Tepper, Joshua; Austin, Peter C; Glazier, Richard H; Levinson, Wendy
2017-09-01
Clinical guidelines advise against routine electrocardiograms (ECG) in low-risk, asymptomatic patients, but the frequency and impact of such ECGs are unknown. To assess the frequency of ECGs following an annual health examination (AHE) with a primary care physician among patients with no known cardiac conditions or risk factors, to explore factors predictive of receiving an ECG in this clinical scenario, and to compare downstream cardiac testing and clinical outcomes in low-risk patients who did and did not receive an ECG after their AHE. A population-based retrospective cohort study using administrative health care databases from Ontario, Canada, between 2010/2011 and 2014/2015 to identify low-risk primary care patients and to assess the subsequent outcomes of interest in this time frame. All patients 18 years or older who had no prior cardiac medical history or risk factors who received an AHE. Receipt of an ECG within 30 days of an AHE. Primary outcome was receipt of downstream cardiac testing or consultation with a cardiologist. Secondary outcomes were death, hospitalization, and revascularization at 12 months. A total of 3 629 859 adult patients had at least 1 AHE between fiscal years 2010/2011 and 2014/2015. Of these patients, 21.5% had an ECG within 30 days after an AHE. The proportion of patients receiving an ECG after an AHE varied from 1.8% to 76.1% among 679 primary care practices (coefficient of quartile dispersion [CQD], 0.50) and from 1.1% to 94.9% among 8036 primary care physicians (CQD, 0.54). Patients who had an ECG were significantly more likely to receive additional cardiac tests, visits, or procedures than those who did not (odds ratio [OR], 5.14; 95% CI, 5.07-5.21; P < .001). The rates of death (0.19% vs 0.16%), cardiac-related hospitalizations (0.46% vs 0.12%), and coronary revascularizations (0.20% vs 0.04%) were low in both the ECG and non-ECG cohorts. Despite recommendations to the contrary, ECG testing after an AHE is relatively common, with significant variation among primary care physicians. Routine ECG testing seems to increase risk for a subsequent cardiology testing and consultation cascade, even though the overall cardiac event rate in both groups was very low.
Rodrigues, Jonathan C.L.; Amadu, Antonio Matteo; Ghosh Dastidar, Amardeep; McIntyre, Bethannie; Szantho, Gergley V.; Lyen, Stephen; Godsave, Cattleya; Ratcliffe, Laura E.K.; Burchell, Amy E.; Hart, Emma C.; Hamilton, Mark C.K.; Nightingale, Angus K.; Paton, Julian F.R.; Manghat, Nathan E.; Bucciarelli-Ducci, Chiara
2017-01-01
Aims In hypertension, the presence of left ventricular (LV) strain pattern on 12-lead electrocardiogram (ECG) carries adverse cardiovascular prognosis. The underlying mechanisms are poorly understood. We investigated whether hypertensive ECG strain is associated with myocardial interstitial fibrosis and impaired myocardial strain, assessed by multi-parametric cardiac magnetic resonance (CMR). Methods and results A total of 100 hypertensive patients [50 ± 14 years, male: 58%, office systolic blood pressure (SBP): 170 ± 30 mmHg, office diastolic blood pressure (DBP): 97 ± 14 mmHg) underwent ECG and 1.5T CMR and were compared with 25 normotensive controls (46 ± 14 years, 60% male, SBP: 124 ± 8 mmHg, DBP: 76 ± 7 mmHg). Native T1 and extracellular volume fraction (ECV) were calculated with the modified look-locker inversion-recovery sequence. Myocardial strain values were estimated with voxel-tracking software. ECG strain (n = 20) was associated with significantly higher indexed LV mass (LVM) (119 ± 32 vs. 80 ± 17 g/m2, P < 0.05) and ECV (30 ± 4 vs. 27 ± 3%, P < 0.05) compared with hypertensive subjects without ECG strain (n = 80). ECG strain subjects had significantly impaired circumferential strain compared with hypertensive subjects without ECG strain and controls (−15.2 ± 4.7 vs. −17.0 ± 3.3 vs. −17.3 ± 2.4%, P < 0.05, respectively). In subgroup analysis, comparing ECG strain subjects to hypertensive subjects with elevated LVM but no ECG strain, a significantly higher ECV (30 ± 4 vs. 28 ± 3%, P < 0.05) was still observed. Indexed LVM was the only variable independently associated with ECG strain in multivariate logistic regression analysis [odds ratio (95th confidence interval): 1.07 (1.02–1.12), P < 0.05). Conclusion In hypertension, ECG strain is a marker of advanced LVH associated with increased interstitial fibrosis and associated with significant myocardial circumferential strain impairment. PMID:27334442
Gottschalk, Byron H; Garcia-Niebla, Javier; Anselm, Daniel D; Jaidka, Atul; De Luna, Antoni Bayés; Baranchuk, Adrian
2016-01-01
Brugada phenocopies (BrP) are clinical entities characterized by ECG patterns that are identical to true Brugada syndrome (BrS), but are elicited by various clinical circumstances. A recent study demonstrated that the patterns of BrP and BrS are indistinguishable under the naked eye, thereby validating the concept that the patterns are identical. The aim of our study was to determine whether recently developed ECG criteria would allow for discrimination between type-2 BrS ECG pattern and type-2 BrP ECG pattern. Ten ECGs from confirmed BrS (aborted sudden death, transformation into type 1 upon sodium channel blocking test and/or ventricular arrhythmias, positive genetics) cases and 9 ECGs from confirmed BrP were included in the study. Surface 12-lead ECGs were scanned, saved in JPEG format for blind measurement of two values: (i) β-angle; and (ii) the base of the triangle. Cut-off values of ≥58° for the β-angle and ≥4mm for the base of the triangle were used to determine the BrS ECG pattern. Mean values for the β-angle in leads V1 and V2 were 66.7±25.5 and 55.4±28.1 for BrS and 54.1±26.5 and 43.1±16.1 for BrP respectively (p=NS). Mean values for the base of the triangle in V1 and V2 were 7.5±3.9 and 5.7±3.9 for BrS and 5.6±3.2 and 4.7±2.7 for BrP respectively (p=NS). The β-angle had a sensitivity of 60%, specificity of 78% (LR+ 2.7, LR- 0.5). The base of the triangle had a sensitivity of 80%, specificity of 40% (LR+ 1.4, LR- 0.5). New ECG criteria presented relatively low sensitivity and specificity, positive and negative predictive values to discriminate between BrS and BrP ECG patterns, providing further evidence that the two patterns are identical. Copyright © 2016 Elsevier Inc. All rights reserved.
Rodrigues, Jonathan C L; Amadu, Antonio Matteo; Ghosh Dastidar, Amardeep; McIntyre, Bethannie; Szantho, Gergley V; Lyen, Stephen; Godsave, Cattleya; Ratcliffe, Laura E K; Burchell, Amy E; Hart, Emma C; Hamilton, Mark C K; Nightingale, Angus K; Paton, Julian F R; Manghat, Nathan E; Bucciarelli-Ducci, Chiara
2017-04-01
In hypertension, the presence of left ventricular (LV) strain pattern on 12-lead electrocardiogram (ECG) carries adverse cardiovascular prognosis. The underlying mechanisms are poorly understood. We investigated whether hypertensive ECG strain is associated with myocardial interstitial fibrosis and impaired myocardial strain, assessed by multi-parametric cardiac magnetic resonance (CMR). A total of 100 hypertensive patients [50 ± 14 years, male: 58%, office systolic blood pressure (SBP): 170 ± 30 mmHg, office diastolic blood pressure (DBP): 97 ± 14 mmHg) underwent ECG and 1.5T CMR and were compared with 25 normotensive controls (46 ± 14 years, 60% male, SBP: 124 ± 8 mmHg, DBP: 76 ± 7 mmHg). Native T1 and extracellular volume fraction (ECV) were calculated with the modified look-locker inversion-recovery sequence. Myocardial strain values were estimated with voxel-tracking software. ECG strain (n = 20) was associated with significantly higher indexed LV mass (LVM) (119 ± 32 vs. 80 ± 17 g/m2, P < 0.05) and ECV (30 ± 4 vs. 27 ± 3%, P < 0.05) compared with hypertensive subjects without ECG strain (n = 80). ECG strain subjects had significantly impaired circumferential strain compared with hypertensive subjects without ECG strain and controls (-15.2 ± 4.7 vs. -17.0 ± 3.3 vs. -17.3 ± 2.4%, P < 0.05, respectively). In subgroup analysis, comparing ECG strain subjects to hypertensive subjects with elevated LVM but no ECG strain, a significantly higher ECV (30 ± 4 vs. 28 ± 3%, P < 0.05) was still observed. Indexed LVM was the only variable independently associated with ECG strain in multivariate logistic regression analysis [odds ratio (95th confidence interval): 1.07 (1.02-1.12), P < 0.05). In hypertension, ECG strain is a marker of advanced LVH associated with increased interstitial fibrosis and associated with significant myocardial circumferential strain impairment. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Cardiology.
Left ventricular hypertrophy by ECG versus cardiac MRI as a predictor for heart failure.
Oseni, Abdullahi O; Qureshi, Waqas T; Almahmoud, Mohamed F; Bertoni, Alain G; Bluemke, David A; Hundley, William G; Lima, Joao A C; Herrington, David M; Soliman, Elsayed Z
2017-01-01
To determine if there is a significant difference in the predictive abilities of left ventricular hypertrophy (LVH) detected by ECG-LVH versus LVH ascertained by cardiac MRI-LVH in a model similar to the Framingham Heart Failure Risk Score (FHFRS). This study included 4745 (mean age 61±10 years, 53.5% women, 61.7% non-whites) participants in the Multi-Ethnic Study of Atherosclerosis. ECG-LVH was defined using Cornell voltage product while MRI-LVH was derived from left ventricular mass. Cox proportional hazard regression was used to examine the association between ECG-LVH and MRI-LVH with incident heart failure (HF). Harrell's concordance C-index was used to estimate the predictive ability of the model when either ECG-LVH or MRI-LVH was included as one of its components. ECG-LVH was present in 291 (6.1%), while MRI-LVH was present in 499 (10.5%) of the participants. Both ECG-LVH (HR 2.25, 95% CI 1.38 to 3.69) and MRI-LVH (HR 3.80, 95% CI 1.56 to 5.63) were predictive of HF. The absolute risk of developing HF was 8.81% for MRI-LVH versus 2.26% for absence of MRI-LVH with a relative risk of 3.9. With ECG-LVH, the absolute risk of developing HF 6.87% compared with 2.69% for absence of ECG-LVH with a relative risk of 2.55. The ability of the model to predict HF was better with MRI-LVH (C-index 0.871, 95% CI 0.842 to 0.899) than with ECG-LVH (C-index 0.860, 95% CI 0.833 to 0.888) (p<0.0001). ECG-LVH and MRI-LVH are predictive of HF. Substituting MRI-LVH for ECG-LVH improves the predictive ability of a model similar to the FHFRS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Barbagelata, Alejandro; Di Carli, Marcelo F; Califf, Robert M; Garg, Jyotsna; Birnbaum, Yochai; Grinfeld, Liliana; Gibbons, Raymond J; Granger, Christopher B; Goodman, Shaun G; Wagner, Galen S; Mahaffey, Kenneth W
2005-10-01
Noninvasive methods are needed to evaluate reperfusion success in patients with acute myocardial infarction (MI). The AMISTAD trial was analyzed to compare MI size and myocardial salvage determined by electrocardiogram (ECG) with technetium Tc 99m sestamibi single-photon emission computerized tomography (SPECT) imaging. Of 236 patients enrolled in AMISTAD, 166 (70 %) with no ECG confounding factors and no prior MI were included in this analysis. Of these, group 1 (126 patients, 53%) had final infarct size (FIS) available by both ECG and SPECT. Group 2 (56 patients, 24%) had myocardium at risk, FIS, and salvage index (SI) assessed by both SPECT and ECG techniques. Aldrich/Clemmensen scores for myocardium at risk and the Selvester QRS score for final MI size were used. Salvage index was calculated as follows: SI = (myocardium at risk-FIS)/(myocardium at risk). In group 1, FIS was 15% (6, 24) as measured by ECG and 11% (2, 27) as measured by SPECT. In the adenosine group, FIS was 12% (6, 21) and 11% (2, 22). In the placebo group, FIS was 16.5% (7.5, 24) and 11.5% (3.0, 38.5) by ECG and SPECT, respectively. The overall correlation between SPECT and ECG for FIS was 0.58 (P = .0001): 0.60 in the placebo group (P = .0001) and 0.54 (P = .0001) in the adenosine group. In group 2, myocardium at risk was 23% (17, 30) and 26% (10, 50) with ECG and SPECT, respectively (P = .0066). Final infarct size was 17% (6, 21) and 12% (1, 24) (P < .0001). The SI was 29% (-7, 57) and 46% (15, 79) with ECG and SPECT, respectively (P = .0510). The ECG measurement of infarct size has a moderate relationship with SPECT infarct size measurements in the population with available assessments. This ECG algorithm must further be validated on clinical outcomes.
Knol, Remco J J; Kan, Huub; Wondergem, Maurits; Cornel, Jan H; Umans, Victor A W M; van der Ploeg, Tjeerd; van der Zant, Friso M
2018-04-01
The value of exercise electrocardiogram (ExECG) in symptomatic female patients with low to intermediate risk for significant coronary artery disease (CAD) has been under debate for many years, and nondiagnostic or even erroneous test results are frequently encountered. Cardiac-CT may be more appropriate to exclude CAD in women. This study compares the results of ExECGs with those of cardiac-CTs, performed within a time frame of 1 month in an all-comers female chest pain population. Five hundred fifty-one consecutive female patients from a patient registry were included. ExECGs were negative in 324 (59%), positive in 14 (3%), and nondiagnostic in 213 (39%) patients. CAD was revealed by cardiac-CT in 57% of the women with negative ExECG. No signs of CAD were present on cardiac-CT in 64% of the women with a positive ExECG. Cardiac-CT showed presence of CAD in 268/551 (49%) patients, of whom 56/268 (21%) was diagnosed with ≥50% stenosis. The ExECG of the latter group was negative in 26 (46%), inconclusive in 29 (52%), and positive in 1 (2%). Considering ≥50% stenosis at cardiac-CT as the reference, sensitivity, specificity, PPV, and NPV of ExECG for the present population were 3.7%, 95.7%, 7.1%, and 91.7%, respectively. Similar diagnostic performance was calculated when considering ≥70% stenosis at cardiac-CT as the reference. ExECG failed to detect CAD in more than half of this cohort and in almost half of women with >50% stenosis at cardiac-CT. Importantly, no CAD was detected by cardiac-CT in 64% of women with a positive ExECG. ExECG is therefore questionable as a diagnostic strategy in women with low-to-intermediate risk of CAD, although prospective studies are warranted to determine whether replacing ExECG by cardiac-CT provides better prognoses.
Nitzken, Matthew; Bajaj, Nihit; Aslan, Sevda; Gimel’farb, Georgy; Ovechkin, Alexander
2013-01-01
Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorders associated with motor control deficits. However, EMG potentials recorded from these muscles are often contaminated with heart-induced electrocardiographic (ECG) signals. Elimination of these artifacts plays a critical role in the precise measure of the respiratory muscle electrical activity. This study was undertaken to find an optimal approach to eliminate the ECG artifacts from EMG recordings. Conventional global filtering can be used to decrease the ECG-induced artifact. However, this method can alter the EMG signal and changes physiologically relevant information. We hypothesize that, unlike global filtering, localized removal of ECG artifacts will not change the original EMG signals. We develop an approach to remove the ECG artifacts without altering the amplitude and frequency components of the EMG signal by using an externally recorded ECG signal as a mask to locate areas of the ECG spikes within EMG data. These segments containing ECG spikes were decomposed into 128 sub-wavelets by a custom-scaled Morlet Wavelet Transform. The ECG-related sub-wavelets at the ECG spike location were removed and a de-noised EMG signal was reconstructed. Validity of the proposed method was proven using mathematical simulated synthetic signals and EMG obtained from SCI patients. We compare the Root-mean Square Error and the Relative Change in Variance between this method, global, notch and adaptive filters. The results show that the localized wavelet-based filtering has the benefit of not introducing error in the native EMG signal and accurately removing ECG artifacts from EMG signals. PMID:24307920
Lowres, Nicole; Neubeck, Lis; Salkeld, Glenn; Krass, Ines; McLachlan, Andrew J; Redfern, Julie; Bennett, Alexandra A; Briffa, Tom; Bauman, Adrian; Martinez, Carlos; Wallenhorst, Christopher; Lau, Jerrett K; Brieger, David B; Sy, Raymond W; Freedman, S Ben
2014-06-01
Atrial fibrillation (AF) causes a third of all strokes, but often goes undetected before stroke. Identification of unknown AF in the community and subsequent anti-thrombotic treatment could reduce stroke burden. We investigated community screening for unknown AF using an iPhone electrocardiogram (iECG) in pharmacies, and determined the cost-effectiveness of this strategy.Pharmacists performedpulse palpation and iECG recordings, with cardiologist iECG over-reading. General practitioner review/12-lead ECG was facilitated for suspected new AF. An automated AF algorithm was retrospectively applied to collected iECGs. Cost-effectiveness analysis incorporated costs of iECG screening, and treatment/outcome data from a United Kingdom cohort of 5,555 patients with incidentally detected asymptomatic AF. A total of 1,000 pharmacy customers aged ≥65 years (mean 76 ± 7 years; 44% male) were screened. Newly identified AF was found in 1.5% (95% CI, 0.8-2.5%); mean age 79 ± 6 years; all had CHA2DS2-VASc score ≥2. AF prevalence was 6.7% (67/1,000). The automated iECG algorithm showed 98.5% (CI, 92-100%) sensitivity for AF detection and 91.4% (CI, 89-93%) specificity. The incremental cost-effectiveness ratio of extending iECG screening into the community, based on 55% warfarin prescription adherence, would be $AUD5,988 (€3,142; $USD4,066) per Quality Adjusted Life Year gained and $AUD30,481 (€15,993; $USD20,695) for preventing one stroke. Sensitivity analysis indicated cost-effectiveness improved with increased treatment adherence.Screening with iECG in pharmacies with an automated algorithm is both feasible and cost-effective. The high and largely preventable stroke/thromboembolism risk of those with newly identified AF highlights the likely benefits of community AF screening. Guideline recommendation of community iECG AF screening should be considered.
Green, Cynthia L.; Kligfield, Paul; George, Samuel; Gussak, Ihor; Vajdic, Branislav; Sager, Philip; Krucoff, Mitchell W.
2013-01-01
Background The Cardiac Safety Research Consortium (CSRC) provides both “learning” and blinded “testing” digital ECG datasets from thorough QT (TQT) studies annotated for submission to the US Food and Drug Administration (FDA) to developers of ECG analysis technologies. This manuscript reports the first results from a blinded “testing” dataset that examines Developer re-analysis of original Sponsor-reported core laboratory data. Methods 11,925 anonymized ECGs including both moxifloxacin and placebo arms of a parallel-group TQT in 191 subjects were blindly analyzed using a novel ECG analysis algorithm applying intelligent automation. Developer measured ECG intervals were submitted to CSRC for unblinding, temporal reconstruction of the TQT exposures, and statistical comparison to core laboratory findings previously submitted to FDA by the pharmaceutical sponsor. Primary comparisons included baseline-adjusted interval measurements, baseline- and placebo-adjusted moxifloxacin QTcF changes (ddQTcF), and associated variability measures. Results Developer and Sponsor-reported baseline-adjusted data were similar with average differences less than 1 millisecond (ms) for all intervals. Both Developer and Sponsor-reported data demonstrated assay sensitivity with similar ddQTcF changes. Average within-subject standard deviation for triplicate QTcF measurements was significantly lower for Developer than Sponsor-reported data (5.4 ms and 7.2 ms, respectively; p<0.001). Conclusion The virtually automated ECG algorithm used for this analysis produced similar yet less variable TQT results compared to the Sponsor-reported study, without the use of a manual core laboratory. These findings indicate CSRC ECG datasets can be useful for evaluating novel methods and algorithms for determining QT/QTc prolongation by drugs. While the results should not constitute endorsement of specific algorithms by either CSRC or FDA, the value of a public domain digital ECG warehouse to provide prospective, blinded comparisons of ECG technologies applied for QT/QTc measurement is illustrated. PMID:22424006
Dores, Hélder; Malhotra, Aneil; Sheikh, Nabeel; Millar, Lynne; Dhutia, Harshil; Narain, Rajay; Merghani, Ahmed; Papadakis, Michael; Sharma, Sanjay
2016-11-01
Athletes can exhibit abnormal electrocardiogram (ECG) phenotypes that require further evaluation prior to competition. These are apparently more prevalent in high-intensity endurance sports. The purpose of this study was to assess the association between ECG findings in athletes and intensity of sport and level of competition. A cohort of 3423 competitive athletes had their ECGs assessed according to the Seattle criteria (SC). The presence of abnormal ECGs was correlated with: (1) intensity of sport (low/moderate vs. at least one high static or dynamic component); (2) competitive level (regional vs. national/international); (3) training volume (≤20 vs. >20 hours/week); (4) type of sport (high dynamic vs. high static component). The same endpoints were studied according to the 'Refined Criteria' (RC). Abnormal ECGs according to the SC were present in 225 (6.6%) athletes, more frequently in those involved in high-intensity sports (8.0% vs. 5.4%; p=0.002), particularly in dynamic sports, and competing at national/international level (7.1% vs. 4.9%; p=0.028). Training volume was not significantly associated with abnormal ECGs. By multivariate analysis, high-intensity sport (OR 1.55, 1.18-2.03; p=0.002) and national/international level (OR 1.50, 95% CI 1.04-2.14; p=0.027) were independent predictors of abnormal ECGs, and these variables, when combined, doubled the prevalence of this finding. According to the RC, abnormal ECGs decreased to 103 (3.0%), but were also more frequent in high-intensity sports (4.2% vs. 2.0%; p<0.001). There is a positive correlation between higher intensity of sports and increased prevalence of ECG abnormalities. This relationship persists with the use of more restrictive criteria for ECG interpretation, although the number of abnormal ECGs is lower. Copyright © 2016 Sociedade Portuguesa de Cardiologia. Publicado por Elsevier España, S.L.U. All rights reserved.
Hood, Michael L
2018-05-01
The 12-lead electrocardiogram (ECG) is an integral part of the diagnostic tools available for recognising a patient who is experiencing an ST-segment elevated myocardial infarction (STEMI). Consequently, a great emphasis is placed on the rapid acquisition and expert interpretation of the 12-lead ECG so that the appropriate reperfusion management might be commenced to optimise patient outcomes by preventing further damage to the myocardium. With the advancement of telemetric and diagnostic abilities of the modern ECG machine, the role of frontline rural emergency clinicians is as important as ever. This clinical case report describes the presentation and management of a person experiencing a STEMI in a rural Australian hospital emergency department setting. The emanating point of interest from this case report is the early clinician recognition of significant ST-segment elevation in multiple leads of the initial ECG trace, indicating a STEMI. Despite the presence of significant acute ST-segment changes throughout the trace, the ECG's diagnostic analysis of the 12-lead ECG did not identify it as meeting STEMI criteria. Subsequently, the ECG was not recommended by the ECG machine for telemetric transmission to the remote on-call cardiologist for immediate STEMI management guidance. This article focuses on the telemetric technology utilised in the management of STEMIs in the rural emergency department, the diagnostic ability of the modern ECG and the role of the frontline rural emergency clinician in the utilisation of such technology. Competent utilisation of key technologies applied to the ECG machine require the clinician to be well trained in the technical use of the equipment, have a thorough understanding of how the technology interacts within the established clinical pathway and be ready to apply its use in a timely manner in order to prevent delays in treatment. Furthermore, an over-reliance on the diagnostic ability of the modern ECG machine in the rural or remote context may potentially lead to poor patient outcomes.
Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Lin, Wen-Yen; Chang, Po-Cheng; Lee, Ming-Yih
2018-01-28
Cardiovascular disease (CVD) is a major public concern and socioeconomic problem across the globe. The popular high-end cardiac health monitoring systems such as magnetic resonance imaging (MRI), computerized tomography scan (CT scan), and echocardiography (Echo) are highly expensive and do not support long-term continuous monitoring of patients without disrupting their activities of daily living (ADL). In this paper, the continuous and non-invasive cardiac health monitoring using unobtrusive sensors is explored aiming to provide a feasible and low-cost alternative to foresee possible cardiac anomalies in an early stage. It is learned that cardiac health monitoring based on sole usage of electrocardiogram (ECG) signals may not provide powerful insights as ECG provides shallow information on various cardiac activities in the form of electrical impulses only. Hence, a novel low-cost, non-invasive seismocardiogram (SCG) signal along with ECG signals are jointly investigated for the robust cardiac health monitoring. For this purpose, the in-laboratory data collection model is designed for simultaneous acquisition of ECG and SCG signals followed by mechanisms for the automatic delineation of relevant feature points in acquired ECG and SCG signals. In addition, separate feature points based novel approach is adopted to distinguish between normal and abnormal morphology in each ECG and SCG cardiac cycle. Finally, a combined analysis of ECG and SCG is carried out by designing a Naïve Bayes conditional probability model. Experiments on Institutional Review Board (IRB) approved licensed ECG/SCG signals acquired from real subjects containing 12,000 cardiac cycles show that the proposed feature point delineation mechanisms and abnormal morphology detection methods consistently perform well and give promising results. In addition, experimental results show that the combined analysis of ECG and SCG signals provide more reliable cardiac health monitoring compared to the standalone use of ECG and SCG.
Lin, Wen-Yen; Chang, Po-Cheng
2018-01-01
Cardiovascular disease (CVD) is a major public concern and socioeconomic problem across the globe. The popular high-end cardiac health monitoring systems such as magnetic resonance imaging (MRI), computerized tomography scan (CT scan), and echocardiography (Echo) are highly expensive and do not support long-term continuous monitoring of patients without disrupting their activities of daily living (ADL). In this paper, the continuous and non-invasive cardiac health monitoring using unobtrusive sensors is explored aiming to provide a feasible and low-cost alternative to foresee possible cardiac anomalies in an early stage. It is learned that cardiac health monitoring based on sole usage of electrocardiogram (ECG) signals may not provide powerful insights as ECG provides shallow information on various cardiac activities in the form of electrical impulses only. Hence, a novel low-cost, non-invasive seismocardiogram (SCG) signal along with ECG signals are jointly investigated for the robust cardiac health monitoring. For this purpose, the in-laboratory data collection model is designed for simultaneous acquisition of ECG and SCG signals followed by mechanisms for the automatic delineation of relevant feature points in acquired ECG and SCG signals. In addition, separate feature points based novel approach is adopted to distinguish between normal and abnormal morphology in each ECG and SCG cardiac cycle. Finally, a combined analysis of ECG and SCG is carried out by designing a Naïve Bayes conditional probability model. Experiments on Institutional Review Board (IRB) approved licensed ECG/SCG signals acquired from real subjects containing 12,000 cardiac cycles show that the proposed feature point delineation mechanisms and abnormal morphology detection methods consistently perform well and give promising results. In addition, experimental results show that the combined analysis of ECG and SCG signals provide more reliable cardiac health monitoring compared to the standalone use of ECG and SCG. PMID:29382098
Nitzken, Matthew; Bajaj, Nihit; Aslan, Sevda; Gimel'farb, Georgy; El-Baz, Ayman; Ovechkin, Alexander
2013-07-18
Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorders associated with motor control deficits. However, EMG potentials recorded from these muscles are often contaminated with heart-induced electrocardiographic (ECG) signals. Elimination of these artifacts plays a critical role in the precise measure of the respiratory muscle electrical activity. This study was undertaken to find an optimal approach to eliminate the ECG artifacts from EMG recordings. Conventional global filtering can be used to decrease the ECG-induced artifact. However, this method can alter the EMG signal and changes physiologically relevant information. We hypothesize that, unlike global filtering, localized removal of ECG artifacts will not change the original EMG signals. We develop an approach to remove the ECG artifacts without altering the amplitude and frequency components of the EMG signal by using an externally recorded ECG signal as a mask to locate areas of the ECG spikes within EMG data. These segments containing ECG spikes were decomposed into 128 sub-wavelets by a custom-scaled Morlet Wavelet Transform. The ECG-related sub-wavelets at the ECG spike location were removed and a de-noised EMG signal was reconstructed. Validity of the proposed method was proven using mathematical simulated synthetic signals and EMG obtained from SCI patients. We compare the Root-mean Square Error and the Relative Change in Variance between this method, global, notch and adaptive filters. The results show that the localized wavelet-based filtering has the benefit of not introducing error in the native EMG signal and accurately removing ECG artifacts from EMG signals.
Digital Signal Processing Based Biotelemetry Receivers
NASA Technical Reports Server (NTRS)
Singh, Avtar; Hines, John; Somps, Chris
1997-01-01
This is an attempt to develop a biotelemetry receiver using digital signal processing technology and techniques. The receiver developed in this work is based on recovering signals that have been encoded using either Pulse Position Modulation (PPM) or Pulse Code Modulation (PCM) technique. A prototype has been developed using state-of-the-art digital signal processing technology. A Printed Circuit Board (PCB) is being developed based on the technique and technology described here. This board is intended to be used in the UCSF Fetal Monitoring system developed at NASA. The board is capable of handling a variety of PPM and PCM signals encoding signals such as ECG, temperature, and pressure. A signal processing program has also been developed to analyze the received ECG signal to determine heart rate. This system provides a base for using digital signal processing in biotelemetry receivers and other similar applications.
The Electrocardiogram and Ischemic Heart Disease in Aircraft Pilots
Manning, G. W.
1965-01-01
A review of the Royal Canadian Air Force electrocardiographic (ECG) program for selection of aircrew and detection of coronary disease in trained aircrew is presented. Twenty reported cases of death due to coronary disease in pilots while at the controls of an aircraft are reviewed. The use of routine electrocardiography in the selection of aircrew has proved to be of considerable value, particularly in view of the high cost of training. The ECG continues to be our most sensitive means of detecting asymptomatic coronary disease in aircrew personnel. It is apparent that from both the military and commercial standpoint the incidence of aircraft accidents due to coronary disease is extremely small. This is due in large part to the careful medical supervision of flying personnel including the routine use of electrocardiography in the assessment of flying fitness of aircrew. PMID:14323657
Hysing, Per; Jonason, Tommy; Leppert, Jerzy; Hedberg, Pär
2017-11-24
Identifying cardiac disease in patients with extracardiac artery disease (ECAD) is essential for clinical decision-making. Electrocardiography (ECG) is an easily accessible tool to unmask subclinical cardiac disease and to risk stratify patient with or without manifest cardiovascular disease (CV). We aimed to examine the prevalence and prognostic impact of ECG changes in outpatients with ECAD. Outpatients with carotid or lower extremity artery disease (n = 435) and community-based controls (n = 397) underwent resting ECG. The patients were followed during a median of 4·8 years for CV events (hospitalization or death caused by ischaemic heart disease, cardiac arrest, heart failure, or stroke). ECG abnormalities were classified according to the Minnesota Code. Major (33% versus 15%, P<0·001) but not minor ECG abnormalities (23% versus 26%, P = 0·42) were significantly more common in patients versus controls. During the follow-up, 141 patients experienced CV events. Both major ECG abnormalities [hazard ratio (HR) 1·58, 95% confidence interval (CI) 1·11-2·25, P = 0·012] and any ECG abnormalities (HR 1·57, 95% CI 1·06-2·33, P = 0·024) were significantly associated with CV events after adjustment for potential risk factors. In conclusion, ECG abnormalities were common in these outpatients with ECAD. Major and any ECG abnormalities were independent predictors of CV events. Addition of easily accessible ECG information might be useful in risk stratification for such patients. © 2017 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.