Adaptive Fourier decomposition based ECG denoising.

PubMed

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.

High-frequency ECG

NASA Technical Reports Server (NTRS)

Tragardh, Elin; Schlegel, Todd T.

2006-01-01

The standard ECG is by convention limited to 0.05-150 Hz, but higher frequencies are also present in the ECG signal. With high-resolution technology, it is possible to record and analyze these higher frequencies. The highest amplitudes of the high-frequency components are found within the QRS complex. In past years, the term "high frequency", "high fidelity", and "wideband electrocardiography" have been used by several investigators to refer to the process of recording ECGs with an extended bandwidth of up to 1000 Hz. Several investigators have tried to analyze HF-QRS with the hope that additional features seen in the QRS complex would provide information enhancing the diagnostic value of the ECG. The development of computerized ECG-recording devices that made it possible to record ECG signals with high resolution in both time and amplitude, as well as better possibilities to store and process the signals digitally, offered new methods for analysis. Different techniques to extract the HF-QRS have been described. Several bandwidths and filter types have been applied for the extraction as well as different signal-averaging techniques for noise reduction. There is no standard method for acquiring and quantifying HF-QRS. The physiological mechanisms underlying HF-QRS are still not fully understood. One theory is that HF-QRS are related to the conduction velocity and the fragmentation of the depolarization wave in the myocardium. In a three-dimensional model of the ventricles with a fractal conduction system it was shown that high numbers of splitting branches are associated with HF-QRS. In this experiment, it was also shown that the changes seen in HF-QRS in patients with myocardial ischemia might be due to the slowing of the conduction velocity in the region of ischemia. This mechanism has been tested by Watanabe et al by infusing sodium channel blockers into the left anterior descending artery in dogs. In their study, 60 unipolar ECGs were recorded from the entire

Internet based ECG medical information system.

PubMed

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.

[Analysis of pacemaker ECGs].

PubMed

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.

A remote access ecg monitoring system - biomed 2009.

PubMed

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.

3-lead acquisition using single channel ECG device developed on AD8232 analog front end for wireless ECG application

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.

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.

ECG (image)

MedlinePlus

The electrocardiogram (ECG, EKG) is used extensively in the diagnosis of heart disease, ranging from congenital heart disease in ... and myocarditis in adults. Several different types of electrocardiogram exist.

Piezoelectric extraction of ECG signal

NASA Astrophysics Data System (ADS)

Ahmad, Mahmoud Al

2016-11-01

The monitoring and early detection of abnormalities or variations in the cardiac cycle functionality are very critical practices and have significant impact on the prevention of heart diseases and their associated complications. Currently, in the field of biomedical engineering, there is a growing need for devices capable of measuring and monitoring a wide range of cardiac cycle parameters continuously, effectively and on a real-time basis using easily accessible and reusable probes. In this paper, the revolutionary generation and extraction of the corresponding ECG signal using a piezoelectric transducer as alternative for the ECG will be discussed. The piezoelectric transducer pick up the vibrations from the heart beats and convert them into electrical output signals. To this end, piezoelectric and signal processing techniques were employed to extract the ECG corresponding signal from the piezoelectric output voltage signal. The measured electrode based and the extracted piezoelectric based ECG traces are well corroborated. Their peaks amplitudes and locations are well aligned with each other.

High Frequency QRS ECG Accurately Detects Cardiomyopathy

NASA Technical Reports Server (NTRS)

Schlegel, Todd T.; Arenare, Brian; Poulin, Gregory; Moser, Daniel R.; Delgado, Reynolds

2005-01-01

High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing

New methodologies for measuring Brugada ECG patterns cannot differentiate the ECG pattern of Brugada syndrome from Brugada phenocopy.

PubMed

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.

Variable threshold method for ECG R-peak detection.

PubMed

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.

Pilot study analyzing automated ECG screening of hypertrophic cardiomyopathy.

PubMed

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.

Diagnostic grade wireless ECG monitoring.

PubMed

Garudadri, Harinath; Chi, Yuejie; Baker, Steve; Majumdar, Somdeb; Baheti, Pawan K; Ballard, Dan

2011-01-01

In remote monitoring of Electrocardiogram (ECG), it is very important to ensure that the diagnostic integrity of signals is not compromised by sensing artifacts and channel errors. It is also important for the sensors to be extremely power efficient to enable wearable form factors and long battery life. We present an application of Compressive Sensing (CS) as an error mitigation scheme at the application layer for wearable, wireless sensors in diagnostic grade remote monitoring of ECG. In our previous work, we described an approach to mitigate errors due to packet losses by projecting ECG data to a random space and recovering a faithful representation using sparse reconstruction methods. Our contributions in this work are twofold. First, we present an efficient hardware implementation of random projection at the sensor. Second, we validate the diagnostic integrity of the reconstructed ECG after packet loss mitigation. We validate our approach on MIT and AHA databases comprising more than 250,000 normal and abnormal beats using EC57 protocols adopted by the Food and Drug Administration (FDA). We show that sensitivity and positive predictivity of a state-of-the-art ECG arrhythmia classifier is essentially invariant under CS based packet loss mitigation for both normal and abnormal beats even at high packet loss rates. In contrast, the performance degrades significantly in the absence of any error mitigation scheme, particularly for abnormal beats such as Ventricular Ectopic Beats (VEB).

Identifying UMLS concepts from ECG Impressions using KnowledgeMap

PubMed Central

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

Flexible Graphene Electrodes for Prolonged Dynamic ECG Monitoring

PubMed Central

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

Effect of ECG filter settings on J-waves.

PubMed

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.

ECG authentication in post-exercise situation.

PubMed

Dongsuk Sung; Jeehoon Kim; Myungjun Koh; Kwangsuk Park

2017-07-01

Human authentication based on electrocardiogram (ECG) has been a remarkable issue for recent ten years. This paper proposed an authentication technology with the ECG data recorded after the harsh exercise. 55 subjects voluntarily attended to this experiment. A stepper was used as an exercise equipment. The subjects are asked to do stepper for 5 minutes and their ECG signals are acquired before and after the exercise in rest, sitting posture. Linear discriminant analysis (LDA) was used for both feature extraction and classification. Even though, within the first 1 minute recording, the subject recognition accuracy was 59.64%, which is too low to utilize, after one minute the accuracy was higher than 90% and it increased up to 96.22% within 5 minutes, which is plausible to use in authentication circumstances. Therefore, we have concluded that ECG authentication techniques will be able to be used after 1 minute of catching breath.

Sparse Matrix for ECG Identification with Two-Lead Features.

PubMed

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.

ECG Sensor Card with Evolving RBP Algorithms for Human Verification.

PubMed

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.

A cloud computing based 12-lead ECG telemedicine service.

PubMed

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.

Noncontact ECG system for unobtrusive long-term monitoring.

PubMed

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.

A mobile phone-based ECG monitoring system.

PubMed

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.

Are ECG abnormalities in Noonan syndrome characteristic for the syndrome?

PubMed

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.

The Cardiac Safety Research Consortium ECG database.

PubMed

Kligfield, Paul; Green, Cynthia L

2012-01-01

The Cardiac Safety Research Consortium (CSRC) ECG database was initiated to foster research using anonymized, XML-formatted, digitized ECGs with corresponding descriptive variables from placebo- and positive-control arms of thorough QT studies submitted to the US Food and Drug Administration (FDA) by pharmaceutical sponsors. The database can be expanded to other data that are submitted directly to CSRC from other sources, and currently includes digitized ECGs from patients with genotyped varieties of congenital long-QT syndrome; this congenital long-QT database is also linked to ambulatory electrocardiograms stored in the Telemetric and Holter ECG Warehouse (THEW). Thorough QT data sets are available from CSRC for unblinded development of algorithms for analysis of repolarization and for blinded comparative testing of algorithms developed for the identification of moxifloxacin, as used as a positive control in thorough QT studies. Policies and procedures for access to these data sets are available from CSRC, which has developed tools for statistical analysis of blinded new algorithm performance. A recently approved CSRC project will create a data set for blinded analysis of automated ECG interval measurements, whose initial focus will include comparison of four of the major manufacturers of automated electrocardiographs in the United States. CSRC welcomes application for use of the ECG database for clinical investigation. Copyright © 2012 Elsevier Inc. All rights reserved.

Freeware eLearning Flash-ECG for learning electrocardiography.

PubMed

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.

A cloud computing based 12-lead ECG telemedicine service

PubMed Central

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

ECG telemetry in conscious guinea pigs.

PubMed

Ruppert, Sabine; Vormberge, Thomas; Igl, Bernd-Wolfgang; Hoffmann, Michael

2016-01-01

During preclinical drug development, monitoring of the electrocardiogram (ECG) is an important part of cardiac safety assessment. To detect potential pro-arrhythmic liabilities of a drug candidate and for internal decision-making during early stage drug development an in vivo model in small animals with translatability to human cardiac function is required. Over the last years, modifications/improvements regarding animal housing, ECG electrode placement, and data evaluation have been introduced into an established model for ECG recordings using telemetry in conscious, freely moving guinea pigs. Pharmacological validation using selected reference compounds affecting different mechanisms relevant for cardiac electrophysiology (quinidine, flecainide, atenolol, dl-sotalol, dofetilide, nifedipine, moxifloxacin) was conducted and findings were compared with results obtained in telemetered Beagle dogs. Under standardized conditions, reliable ECG data with low variability allowing largely automated evaluation were obtained from the telemetered guinea pig model. The model is sensitive to compounds blocking cardiac sodium channels, hERG K(+) channels and calcium channels, and appears to be even more sensitive to β-blockers as observed in dogs at rest. QT interval correction according to Bazett and Sarma appears to be appropriate methods in conscious guinea pigs. Overall, the telemetered guinea pig is a suitable model for the conduct of early stage preclinical ECG assessment. Copyright © 2016 Elsevier Inc. All rights reserved.

Methods for Improving the Diagnosis of a Brugada ECG Pattern.

PubMed

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.

[Lossless ECG compression algorithm with anti- electromagnetic interference].

PubMed

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.

[Practical experience about the compatibility of PDF converter in ECG information system].

PubMed

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.

Wearable ECG Based on Impulse-Radio-Type Human Body Communication.

PubMed

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.

Comparison of Digital 12-Lead ECG and Digital 12-Lead Holter ECG Recordings in Healthy Male Subjects: Results from a Randomized, Double-Blinded, Placebo-Controlled Clinical Trial.

PubMed

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.

Female False Positive Exercise Stress ECG Testing - Fact Verses Fiction.

PubMed

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.

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.

Biometric and Emotion Identification: An ECG Compression Based Method.

PubMed

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.

Image-guided optimization of the ECG trace in cardiac MRI.

PubMed

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.

Ability of a 5-minute electrocardiography (ECG) for predicting arrhythmias in Doberman Pinschers with cardiomyopathy in comparison with a 24-hour ambulatory ECG.

PubMed

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.

[ECG for non-competitive sports in childhood: strengths and disputes].

PubMed

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.

Unveiling the Biometric Potential of Finger-Based ECG Signals

PubMed Central

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

Unveiling the biometric potential of finger-based ECG signals.

PubMed

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.

A novel biometric authentication approach using ECG and EMG signals.

PubMed

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.

A Study on the Optimal Positions of ECG Electrodes in a Garment for the Design of ECG-Monitoring Clothing for Male.

PubMed

Cho, Hakyung; Lee, Joo Hyeon

2015-09-01

Smart clothing is a sort of wearable device used for ubiquitous health monitoring. It provides comfort and efficiency in vital sign measurements and has been studied and developed in various types of monitoring platforms such as T-shirt and sports bra. However, despite these previous approaches, smart clothing for electrocardiography (ECG) monitoring has encountered a serious shortcoming relevant to motion artifacts caused by wearer movement. In effect, motion artifacts are one of the major problems in practical implementation of most wearable health-monitoring devices. In the ECG measurements collected by a garment, motion artifacts are usually caused by improper location of the electrode, leading to lack of contact between the electrode and skin with body motion. The aim of this study was to suggest a design for ECG-monitoring clothing contributing to reduction of motion artifacts. Based on the clothing science theory, it was assumed in this study that the stability of the electrode in a dynamic state differed depending on the electrode location in an ECG-monitoring garment. Founded on this assumption, effects of 56 electrode positions were determined by sectioning the surface of the garment into grids with 6 cm intervals in the front and back of the bodice. In order to determine the optimal locations of the ECG electrodes from the 56 positions, ECG measurements were collected from 10 participants at every electrode position in the garment while the wearer was in motion. The electrode locations indicating both an ECG measurement rate higher than 80.0 % and a large amplitude during motion were selected as the optimal electrode locations. The results of this analysis show four electrode locations with consistently higher ECG measurement rates and larger amplitudes amongst the 56 locations. These four locations were abstracted to be least affected by wearer movement in this research. Based on this result, a design of the garment-formed ECG monitoring platform

PIC microcontroller-based RF wireless ECG monitoring system.

PubMed

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.

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.

Diagnostic value of prehospital ECG in acute stroke patients.

PubMed

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.

A wearable 12-lead ECG acquisition system with fabric electrodes.

PubMed

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.

Biometric and Emotion Identification: An ECG Compression Based Method

PubMed Central

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

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.

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).

Compressed domain ECG biometric with two-lead features

NASA Astrophysics Data System (ADS)

Lee, Wan-Jou; Chang, Wen-Whei

2016-07-01

This study presents a new method to combine ECG biometrics with data compression within a common JPEG2000 framework. We target the two-lead ECG configuration that is routinely used in long-term heart monitoring. Incorporation of compressed-domain biometric techniques enables faster person identification as it by-passes the full decompression. Experiments on public ECG databases demonstrate the validity of the proposed method for biometric identification with high accuracies on both healthy and diseased subjects.

From Pacemaker to Wearable: Techniques for ECG Detection Systems.

PubMed

Kumar, Ashish; Komaragiri, Rama; Kumar, Manjeet

2018-01-11

With the alarming rise in the deaths due to cardiovascular diseases (CVD), present medical research scenario places notable importance on techniques and methods to detect CVDs. As adduced by world health organization, technological proceeds in the field of cardiac function assessment have become the nucleus and heart of all leading research studies in CVDs in which electrocardiogram (ECG) analysis is the most functional and convenient tool used to test the range of heart-related irregularities. Most of the approaches present in the literature of ECG signal analysis consider noise removal, rhythm-based analysis, and heartbeat detection to improve the performance of a cardiac pacemaker. Advancements achieved in the field of ECG segments detection and beat classification have a limited evaluation and still require clinical approvals. In this paper, approaches on techniques to implement on-chip ECG detector for a cardiac pacemaker system are discussed. Moreover, different challenges regarding the ECG signal morphology analysis deriving from medical literature is extensively reviewed. It is found that robustness to noise, wavelet parameter choice, numerical efficiency, and detection performance are essential performance indicators required by a state-of-the-art ECG detector. Furthermore, many algorithms described in the existing literature are not verified using ECG data from the standard databases. Some ECG detection algorithms show very high detection performance with the total number of detected QRS complexes. However, the high detection performance of the algorithm is verified using only a few datasets. Finally, gaps in current advancements and testing are identified, and the primary challenge remains to be implementing bullseye test for morphology analysis evaluation.

Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

PubMed

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.

A method of ECG template extraction for biometrics applications.

PubMed

Zhou, Xiang; Lu, Yang; Chen, Meng; Bao, Shu-Di; Miao, Fen

2014-01-01

ECG has attracted widespread attention as one of the most important non-invasive physiological signals in healthcare-system related biometrics for its characteristics like ease-of-monitoring, individual uniqueness as well as important clinical value. This study proposes a method of dynamic threshold setting to extract the most stable ECG waveform as the template for the consequent ECG identification process. With the proposed method, the accuracy of ECG biometrics using the dynamic time wraping for difference measures has been significantly improved. Analysis results with the self-built electrocardiogram database show that the deployment of the proposed method was able to reduce the half total error rate of the ECG biometric system from 3.35% to 1.45%. Its average running time on the platform of android mobile terminal was around 0.06 seconds, and thus demonstrates acceptable real-time performance.

Variability in surface ECG morphology: signal or noise?

NASA Technical Reports Server (NTRS)

Smith, J. M.; Rosenbaum, D. S.; Cohen, R. J.

1988-01-01

Using data collected from canine models of acute myocardial ischemia, we investigated two issues of major relevance to electrocardiographic signal averaging: ECG epoch alignment, and the spectral characteristics of the beat-to-beat variability in ECG morphology. With initial digitization rates of 1 kHz, an iterative a posteriori matched filtering alignment scheme, and linear interpolation, we demonstrated that there is sufficient information in the body surface ECG to merit alignment to a precision of 0.1 msecs. Applying this technique to align QRS complexes and atrial pacing artifacts independently, we demonstrated that the conduction delay from atrial stimulus to ventricular activation may be so variable as to preclude using atrial pacing as an alignment mechanism, and that this variability in conduction time be modulated at the frequency of respiration and at a much lower frequency (0.02-0.03Hz). Using a multidimensional spectral technique, we investigated the beat-to-beat variability in ECG morphology, demonstrating that the frequency spectrum of ECG morphological variation reveals a readily discernable modulation at the frequency of respiration. In addition, this technique detects a subtle beat-to-beat alternation in surface ECG morphology which accompanies transient coronary artery occlusion. We conclude that physiologically important information may be stored in the variability in the surface electrocardiogram, and that this information is lost by conventional averaging techniques.

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).

Physician attitudes about prehospital 12-lead ECGs in chest pain patients.

PubMed

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.

FastICA peel-off for ECG interference removal from surface EMG.

PubMed

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.

[Study for portable dynamic ECG monitor and recorder].

PubMed

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.

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.

Near Field Communication-based telemonitoring with integrated ECG recordings.

PubMed

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.

Near Field Communication-based telemonitoring with integrated ECG recordings

PubMed Central

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

[Implementation of ECG Monitoring System Based on Internet of Things].

PubMed

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.

QRS detection based ECG quality assessment.

PubMed

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.

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.

ECG fiducial point extraction using switching Kalman filter.

PubMed

Akhbari, Mahsa; Ghahjaverestan, Nasim Montazeri; Shamsollahi, Mohammad B; Jutten, Christian

2018-04-01

In this paper, we propose a novel method for extracting fiducial points (FPs) of the beats in electrocardiogram (ECG) signals using switching Kalman filter (SKF). In this method, according to McSharry's model, ECG waveforms (P-wave, QRS complex and T-wave) are modeled with Gaussian functions and ECG baselines are modeled with first order auto regressive models. In the proposed method, a discrete state variable called "switch" is considered that affects only the observation equations. We denote a mode as a specific observation equation and switch changes between 7 modes and corresponds to different segments of an ECG beat. At each time instant, the probability of each mode is calculated and compared among two consecutive modes and a path is estimated, which shows the relation of each part of the ECG signal to the mode with the maximum probability. ECG FPs are found from the estimated path. For performance evaluation, the Physionet QT database is used and the proposed method is compared with methods based on wavelet transform, partially collapsed Gibbs sampler (PCGS) and extended Kalman filter. For our proposed method, the mean error and the root mean square error across all FPs are 2 ms (i.e. less than one sample) and 14 ms, respectively. These errors are significantly smaller than those obtained using other methods. The proposed method achieves lesser RMSE and smaller variability with respect to others. Copyright © 2018 Elsevier B.V. All rights reserved.

Detection of QT prolongation using a novel ECG analysis algorithm applying intelligent automation: Prospective blinded evaluation using the Cardiac Safety Research Consortium ECG database

PubMed Central

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

Designing ECG-based physical unclonable function for security of wearable devices.

PubMed

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.

PubMed

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.

A review on digital ECG formats and the relationships between them.

PubMed

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.

Advanced ECG in 2016: is there more than just a tracing?

PubMed

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

Extended Kalman smoother with differential evolution technique for denoising of ECG signal.

PubMed

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.

Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery

PubMed Central

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

Low-power analog integrated circuits for wireless ECG acquisition systems.

PubMed

Tsai, Tsung-Heng; Hong, Jia-Hua; Wang, Liang-Hung; Lee, Shuenn-Yuh

2012-09-01

This paper presents low-power analog ICs for wireless ECG acquisition systems. Considering the power-efficient communication in the body sensor network, the required low-power analog ICs are developed for a healthcare system through miniaturization and system integration. To acquire the ECG signal, a low-power analog front-end system, including an ECG signal acquisition board, an on-chip low-pass filter, and an on-chip successive-approximation analog-to-digital converter for portable ECG detection devices is presented. A quadrature CMOS voltage-controlled oscillator and a 2.4 GHz direct-conversion transmitter with a power amplifier and upconversion mixer are also developed to transmit the ECG signal through wireless communication. In the receiver, a 2.4 GHz fully integrated CMOS RF front end with a low-noise amplifier, differential power splitter, and quadrature mixer based on current-reused folded architecture is proposed. The circuits have been implemented to meet the specifications of the IEEE 802.15.4 2.4 GHz standard. The low-power ICs of the wireless ECG acquisition systems have been fabricated using a 0.18 μm Taiwan Semiconductor Manufacturing Company (TSMC) CMOS standard process. The measured results on the human body reveal that ECG signals can be acquired effectively by the proposed low-power analog front-end ICs.

Diagnostic Role of ECG Recording Simultaneously With EEG Testing.

PubMed

Kendirli, Mustafa Tansel; Aparci, Mustafa; Kendirli, Nurten; Tekeli, Hakan; Karaoglan, Mustafa; Senol, Mehmet Guney; Togrol, Erdem

2015-07-01

Arrhythmia is not uncommon in the etiology of syncope which mimics epilepsy. Data about the epilepsy induced vagal tonus abnormalities have being increasingly reported. So we aimed to evaluate what a neurologist may gain by a simultaneous electrocardiogram (ECG) and electroencephalogram (EEG) recording in the patients who underwent EEG testing due to prediagnosis of epilepsy. We retrospectively evaluated and detected ECG abnormalities in 68 (18%) of 376 patients who underwent EEG testing. A minimum of 20 of minutes artifact-free recording were required for each patient. Standard 1-channel ECG was simultaneously recorded in conjunction with the EEG. In all, 28% of females and 14% of males had ECG abnormalities. Females (mean age 49 years, range 18-88 years) were older compared with the male group (mean age 28 years, range 16-83 years). Atrial fibrillation was more frequent in female group whereas bradycardia and respiratory sinus arrhythmia was higher in male group. One case had been detected a critical asystole indicating sick sinus syndrome in the female group and treated with a pacemaker implantation in the following period. Simultaneous ECG recording in conjunction with EEG testing is a clinical prerequisite to detect and to clarify the coexisting ECG and EEG abnormalities and their clinical relevance. Potentially rare lethal causes of syncope that mimic seizure or those that could cause resistance to antiepileptic therapy could effectively be distinguished by detecting ECG abnormalities coinciding with the signs and abnormalities during EEG recording. © EEG and Clinical Neuroscience Society (ECNS) 2014.

ECG findings in comparison to cardiovascular MR imaging in viral myocarditis.

PubMed

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.

A novel low-complexity digital filter design for wearable ECG devices

PubMed Central

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

Feasibility of in utero telemetric fetal ECG monitoring in a lamb model.

PubMed

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.

21 CFR 892.1970 - Radiographic ECG/respirator synchronizer.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Radiographic ECG/respirator synchronizer. 892.1970 Section 892.1970 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1970 Radiographic ECG/respirator...

Live ECG readings using Google Glass in emergency situations.

PubMed

Schaer, Roger; Salamin, Fanny; Jimenez Del Toro, Oscar Alfonso; Atzori, Manfredo; Muller, Henning; Widmer, Antoine

2015-01-01

Most sudden cardiac problems require rapid treatment to preserve life. In this regard, electrocardiograms (ECG) shown on vital parameter monitoring systems help medical staff to detect problems. In some situations, such monitoring systems may display information in a less than convenient way for medical staff. For example, vital parameters are displayed on large screens outside the field of view of a surgeon during cardiac surgery. This may lead to losing time and to mistakes when problems occur during cardiac operations. In this paper we present a novel approach to display vital parameters such as the second derivative of the ECG rhythm and heart rate close to the field of view of a surgeon using Google Glass. As a preliminary assessment, we run an experimental study to verify the possibility for medical staff to identify abnormal ECG rhythms from Google Glass. This study compares 6 ECG rhythms readings from a 13.3 inch laptop screen and from the prism of Google Glass. Seven medical residents in internal medicine participated in the study. The preliminary results show that there is no difference between identifying these 6 ECG rhythms from the laptop screen versus Google Glass. Both allow close to perfect identification of the 6 common ECG rhythms. This shows the potential of connected glasses such as Google Glass to be useful in selected medical applications.

ECG Electrocardiogram (For Parents)

MedlinePlus

... 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 ...

ECG interpretation skills of South African Emergency Medicine residents

PubMed Central

Wallis, Lee; Maritz, David

2010-01-01

Background The use and interpretation of electrocardiograms (ECGs) are widely accepted as an essential core skill in Emergency Medicine. It is imperative that emergency physicians are expert in ECG interpretation when they exit their training programme. Aim It is unknown whether South African Emergency Medicine trainees are getting the necessary skills in ECG interpretation during the training programme. Currently there are no clear criteria to assess emergency physicians’ competency in ECG interpretation in South Africa. Methods A prospective cross-sectional study of Emergency Medicine residents and recently qualified emergency physicians was conducted between August 2008 and February 2009 using a focused questionnaire. Results At the time of the study, there were 55 eligible trainees in South Africa. A total of 55 assessments were distributed; 50 were returned (91%) and 49 were fully completed (89%). In this study, we found the overall average score of ECG interpretation was 46.4% [95% confidence interval (CI) 41.5–51.2%]. The junior group had an overall average of 42.2% (95% CI 36.9–47.5%), whereas the senior group managed 52.5% (95% CI 43.4–61.5%). Conclusion In this prospective cross-sectional study of Emergency Medicine residents and recently qualified emergency physicians, we found that there was improvement in the interpretation of ECGs with increased seniority. There exists, however, a low level of accuracy for many of the critical ECG diagnoses. The average score of 46.4% obtained in this study is lower than the scores obtained by other international studies from countries where Emergency Medicine is a well-established speciality. PMID:21373298

Threshold-based system for noise detection in multilead ECG recordings.

PubMed

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.

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.

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System.

PubMed

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.

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System

PubMed Central

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

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…

Brugada like pattern in ECG with drug overdose.

PubMed

Kiran, H S; Ravikumar, Y S; Jayasheelan, M R; Prashanth

2010-02-01

Tricyclic antidepressants (TCAs) may have dangerous cardiac effects in overdose. ECG is useful as both a screening tool for tricyclic antidepressant exposure and as a prognostic indicator. TCA overdose may produce various ECG changes. We report a case of Dothiepin overdose resulting in Brugada like pattern including RBBB which resolved spontaneously.

Low-cost compact ECG with graphic LCD and phonocardiogram system design.

PubMed

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.

Helical prospective ECG-gating in cardiac computed tomography: radiation dose and image quality.

PubMed

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.

Weekly Checks Improve Real-Time Prehospital ECG Transmission in Suspected STEMI.

PubMed

D'Arcy, Nicole T; Bosson, Nichole; Kaji, Amy H; Bui, Quang T; French, William J; Thomas, Joseph L; Elizarraraz, Yvonne; Gonzalez, Natalia; Garcia, Jose; Niemann, James T

2018-06-01

IntroductionField identification of ST-elevation myocardial infarction (STEMI) and advanced hospital notification decreases first-medical-contact-to-balloon (FMC2B) time. A recent study in this system found that electrocardiogram (ECG) transmission following a STEMI alert was frequently unsuccessful.HypothesisInstituting weekly test ECG transmissions from paramedic units to the hospital would increase successful transmission of ECGs and decrease FMC2B and door-to-balloon (D2B) times. This was a natural experiment of consecutive patients with field-identified STEMI transported to a single percutaneous coronary intervention (PCI)-capable hospital in a regional STEMI system before and after implementation of scheduled test ECG transmissions. In November 2014, paramedic units began weekly test transmissions. The mobile intensive care nurse (MICN) confirmed the transmission, or if not received, contacted the paramedic unit and the department's nurse educator to identify and resolve the problem. Per system-wide protocol, paramedics transmit all ECGs with interpretation of STEMI. Receiving hospitals submit patient data to a single registry as part of ongoing system quality improvement. The frequency of successful ECG transmission and time to intervention (FMC2B and D2B times) in the 18 months following implementation was compared to the 10 months prior. Post-implementation, the time the ECG transmission was received was also collected to determine the transmission gap time (time from ECG acquisition to ECG transmission received) and the advanced notification time (time from ECG transmission received to patient arrival). There were 388 patients with field ECG interpretations of STEMI, 131 pre-intervention and 257 post-intervention. The frequency of successful transmission post-intervention was 73% compared to 64% prior; risk difference (RD)=9%; 95% CI, 1-18%. In the post-intervention period, the median FMC2B time was 79 minutes (inter-quartile range [IQR]=68-102) versus 86

Textile Concentric Ring Electrodes for ECG Recording Based on Screen-Printing Technology

PubMed Central

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

Textile Concentric Ring Electrodes for ECG Recording Based on Screen-Printing Technology.

PubMed

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

A system for intelligent home care ECG upload and priorisation.

PubMed

D'Angelo, Lorenzo T; Tarita, Eugeniu; Zywietz, Tosja K; Lueth, Tim C

2010-01-01

In this contribution, a system for internet based, automated home care ECG upload and priorisation is presented for the first time. It unifies the advantages of existing telemonitoring ECG systems adding functionalities such as automated priorisation and usability for home care. Chronic cardiac diseases are a big group in the geriatric field. Most of them can be easily diagnosed with help of an electrocardiogram. A frequent or long-term ECG analysis allows early diagnosis of e.g. a cardiac infarction. Nevertheless, patients often aren't willing to visit a doctor for prophylactic purposes. Possible solutions of this problem are home care devices, which are used to investigate patients at home without the presence of a doctor on site. As the diffusion of such systems leads to a huge amount of data which has to be managed and evaluated, the presented approach focuses on an easy to use software for ECG upload from home, a web based management application and an algorithm for ECG preanalysis and priorisation.

Bedside identification of patients at risk for PVC-induced cardiomyopathy: Is ECG useful?

PubMed

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.

Matched Filtering for Heart Rate Estimation on Compressive Sensing ECG Measurements.

PubMed

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.

Implementation of a portable device for real-time ECG signal analysis.

PubMed

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

Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation.

PubMed

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.

MS-QI: A Modulation Spectrum-Based ECG Quality Index for Telehealth Applications.

PubMed

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.

Automated detection of ventricular pre-excitation in pediatric 12-lead ECG.

PubMed

Gregg, Richard E; Zhou, Sophia H; Dubin, Anne M

2016-01-01

With increased interest in screening of young people for potential causes of sudden death, accurate automated detection of ventricular pre-excitation (VPE) or Wolff-Parkinson-White syndrome (WPW) in the pediatric resting ECG is important. Several recent studies have shown interobserver variability when reading screening ECGs and thus an accurate automated reading for this potential cause of sudden death is critical. We designed and tested an automated algorithm to detect pediatric VPE optimized for low prevalence. Digital ECGs with 12 leads or 15 leads (12-lead plus V3R, V4R and V7) were selected from multiple hospitals and separated into a testing and training database. Inclusion criterion was age less than 16 years. The reference for algorithm detection of VPE was cardiologist annotation of VPE for each ECG. The training database (n=772) consisted of VPE ECGs (n=37), normal ECGs (n=492) and a high concentration of conduction defects, RBBB (n=232) and LBBB (n=11). The testing database was a random sample (n=763). All ECGs were analyzed with the Philips DXL ECG Analysis algorithm for basic waveform measurements. Additional ECG features specific to VPE, mainly delta wave scoring, were calculated from the basic measurements and the average beat. A classifier based on decision tree bootstrap aggregation (tree bagger) was trained in multiple steps to select the number of decision trees and the 10 best features. The classifier accuracy was measured on the test database. The new algorithm detected pediatric VPE with a sensitivity of 78%, a specificity of 99.9%, a positive predictive value of 88% and negative predictive value of 99.7%. This new algorithm for detection of pediatric VPE performs well with a reasonable positive and negative predictive value despite the low prevalence in the general population. Copyright © 2016 Elsevier Inc. All rights reserved.

Hybrid ECG signal conditioner

NASA Technical Reports Server (NTRS)

Rinard, G. A.; Steffen, D. A.; Sturm, R. E.

1979-01-01

Circuit with high common-mode rejection has ability to filter and amplify accepted analog electrocardiogram (ECG) signals of varying amplitude, shape, and polarity. In addition, low power circuit develops standardized pulses that can be counted and averaged by heart/breath rate processor.

Coronary CT angiography with single-source and dual-source CT: comparison of image quality and radiation dose between prospective ECG-triggered and retrospective ECG-gated protocols.

PubMed

Sabarudin, Akmal; Sun, Zhonghua; Yusof, Ahmad Khairuddin Md

2013-09-30

This study is conducted to investigate and compare image quality and radiation dose between prospective ECG-triggered and retrospective ECG-gated coronary CT angiography (CCTA) with the use of single-source CT (SSCT) and dual-source CT (DSCT). A total of 209 patients who underwent CCTA with suspected coronary artery disease scanned with SSCT (n=95) and DSCT (n=114) scanners using prospective ECG-triggered and retrospective ECG-gated protocols were recruited from two institutions. The image was assessed by two experienced observers, while quantitative assessment was performed by measuring the image noise, the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR). Effective dose was calculated using the latest published conversion coefficient factor. A total of 2087 out of 2880 coronary artery segments were assessable, with 98.0% classified as of sufficient and 2.0% as of insufficient image quality for clinical diagnosis. There was no significant difference in overall image quality between prospective ECG-triggered and retrospective gated protocols, whether it was performed with DSCT or SSCT scanners. Prospective ECG-triggered protocol was compared in terms of radiation dose calculation between DSCT (6.5 ± 2.9 mSv) and SSCT (6.2 ± 1.0 mSv) scanners and no significant difference was noted (p=0.99). However, the effective dose was significantly lower with DSCT (18.2 ± 8.3 mSv) than with SSCT (28.3 ± 7.0 mSv) in the retrospective gated protocol. Prospective ECG-triggered CCTA reduces radiation dose significantly compared to retrospective ECG-gated CCTA, while maintaining good image quality. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Alexander fractional differential window filter for ECG denoising.

PubMed

Verma, Atul Kumar; Saini, Indu; Saini, Barjinder Singh

2018-06-01

The electrocardiogram (ECG) non-invasively monitors the electrical activities of the heart. During the process of recording and transmission, ECG signals are often corrupted by various types of noises. Minimizations of these noises facilitate accurate detection of various anomalies. In the present paper, Alexander fractional differential window (AFDW) filter is proposed for ECG signal denoising. The designed filter is based on the concept of generalized Alexander polynomial and the R-L differential equation of fractional calculus. This concept is utilized to formulate a window that acts as a forward filter. Thereafter, the backward filter is constructed by reversing the coefficients of the forward filter. The proposed AFDW filter is then obtained by averaging of the forward and backward filter coefficients. The performance of the designed AFDW filter is validated by adding the various type of noise to the original ECG signal obtained from MIT-BIH arrhythmia database. The two non-diagnostic measure, i.e., SNR, MSE, and one diagnostic measure, i.e., wavelet energy based diagnostic distortion (WEDD) have been employed for the quantitative evaluation of the designed filter. Extensive experimentations on all the 48-records of MIT-BIH arrhythmia database resulted in average SNR of 22.014 ± 3.806365, 14.703 ± 3.790275, 13.3183 ± 3.748230; average MSE of 0.001458 ± 0.00028, 0.0078 ± 0.000319, 0.01061 ± 0.000472; and average WEDD value of 0.020169 ± 0.01306, 0.1207 ± 0.061272, 0.1432 ± 0.073588, for ECG signal contaminated by the power line, random, and the white Gaussian noise respectively. A new metric named as morphological power preservation measure (MPPM) is also proposed that account for the power preservance (as indicated by PSD plots) and the QRS morphology. The proposed AFDW filter retained much of the original (clean) signal power without any significant morphological distortion as validated by MPPM measure that were 0

A protocol for a prospective observational study using chest and thumb ECG: transient ECG assessment in stroke evaluation (TEASE) in Sweden.

PubMed

Magnusson, Peter; Koyi, Hirsh; Mattsson, Gustav

2018-04-03

Atrial fibrillation (AF) causes ischaemic stroke and based on risk factor evaluation warrants anticoagulation therapy. In stroke survivors, AF is typically detected with short-term ECG monitoring in the stroke unit. Prolonged continuous ECG monitoring requires substantial resources while insertable cardiac monitors are invasive and costly. Chest and thumb ECG could provide an alternative for AF detection poststroke.The primary objective of our study is to assess the incidence of newly diagnosed AF during 28 days of chest and thumb ECG monitoring in cryptogenic stroke. Secondary objectives are to assess health-related quality of life (HRQoL) using short-form health survey (SF-36) and the feasibility of the Coala Heart Monitor in patients who had a stroke. Stroke survivors in Region Gävleborg, Sweden, will be eligible for the study from October 2017. Patients with a history of ischaemic stroke without documented AF before or during ECG evaluation in the stroke unit will be evaluated by the chest and thumb ECG system Coala Heart Monitor. The monitoring system is connected to a smartphone application which allows for remote monitoring and prompt advice on clinical management. Over a period of 28 days, patients will be monitored two times a day and may activate the ECG recording at symptoms. On completion, the system is returned by mail. This system offers a possibility to evaluate the presence of AF poststroke, but the feasibility of this system in patients who recently suffered from a stroke is unknown. In addition, HRQoL using SF-36 in comparison to Swedish population norms will be assessed. The feasibility of the Coala Heart Monitor will be assessed by a self-developed questionnaire. The study was approved by The Regional Ethical Committee in Uppsala (2017/321). The database will be closed after the last follow-up, followed by statistical analyses, interpretation of results and dissemination to a scientific journal. NCT03301662; Pre-results. © Article author

Left Ventricular Hypertrophy: An allometric comparative analysis of different ECG markers

NASA Astrophysics Data System (ADS)

Bonomini, M. P.; Ingallina, F.; Barone, V.; Valentinuzzi, M. E.; Arini, P. D.

2011-12-01

Allometry, in general biology, measures the relative growth of a part in relation to the whole living organism. Left ventricular hypertrophy (LVH) is the heart adaptation to excessive load (systolic or diastolic). The increase in left ventricular mass leads to an increase in the electrocardiographic voltages. Based on clinical data, we compared the allometric behavior of three different ECG markers of LVH. To do this, the allometric fit AECG = δ + β (VM) relating left ventricular mass (estimated from ecocardiographic data) and ECG amplitudes (expressed as the Cornell-Voltage, Sokolow and the ECG overall voltage indexes) were compared. Besides, sensitivity and specifity for each index were analyzed. The more sensitive the ECG criteria, the better the allometric fit. In conclusion: The allometric paradigm should be regarded as the way to design new and more sensitive ECG-based LVH markers.

Detection of Cardiac Abnormalities from Multilead ECG using Multiscale Phase Alternation Features.

PubMed

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.

A new mobile phone-based ECG monitoring system.

PubMed

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.

[An Algorithm to Eliminate Power Frequency Interference in ECG Using Template].

PubMed

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.

ECG biometric identification: A compression based approach.

PubMed

Bras, Susana; Pinho, Armando J

2015-08-01

Using the electrocardiogram signal (ECG) to identify and/or authenticate persons are problems still lacking satisfactory solutions. Yet, ECG possesses characteristics that are unique or difficult to get from other signals used in biometrics: (1) it requires contact and liveliness for acquisition (2) it changes under stress, rendering it potentially useless if acquired under threatening. Our main objective is to present an innovative and robust solution to the above-mentioned problem. To successfully conduct this goal, we rely on information-theoretic data models for data compression and on similarity metrics related to the approximation of the Kolmogorov complexity. The proposed measure allows the comparison of two (or more) ECG segments, without having to follow traditional approaches that require heartbeat segmentation (described as highly influenced by external or internal interferences). As a first approach, the method was able to cluster the data in three groups: identical record, same participant, different participant, by the stratification of the proposed measure with values near 0 for the same participant and closer to 1 for different participants. A leave-one-out strategy was implemented in order to identify the participant in the database based on his/her ECG. A 1NN classifier was implemented, using as distance measure the method proposed in this work. The classifier was able to identify correctly almost all participants, with an accuracy of 99% in the database used.

A robust approach for ECG-based analysis of cardiopulmonary coupling.

PubMed

Zheng, Jiewen; Wang, Weidong; Zhang, Zhengbo; Wu, Dalei; Wu, Hao; Peng, Chung-Kang

2016-07-01

Deriving respiratory signal from a surface electrocardiogram (ECG) measurement has advantage of simultaneously monitoring of cardiac and respiratory activities. ECG-based cardiopulmonary coupling (CPC) analysis estimated by heart period variability and ECG-derived respiration (EDR) shows promising applications in medical field. The aim of this paper is to provide a quantitative analysis of the ECG-based CPC, and further improve its performance. Two conventional strategies were tested to obtain EDR signal: R-S wave amplitude and area of the QRS complex. An adaptive filter was utilized to extract the common component of inter-beat interval (RRI) and EDR, generating enhanced versions of EDR signal. CPC is assessed through probing the nonlinear phase interactions between RRI series and respiratory signal. Respiratory oscillations presented in both RRI series and respiratory signals were extracted by ensemble empirical mode decomposition for coupling analysis via phase synchronization index. The results demonstrated that CPC estimated from conventional EDR series exhibits constant and proportional biases, while that estimated from enhanced EDR series is more reliable. Adaptive filtering can improve the accuracy of the ECG-based CPC estimation significantly and achieve robust CPC analysis. The improved ECG-based CPC estimation may provide additional prognostic information for both sleep medicine and autonomic function analysis. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Assurance of energy efficiency and data security for ECG transmission in BASNs.

PubMed

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.

Using Intracardiac Vectorcardiographic Loop for Surface ECG Synthesis

NASA Astrophysics Data System (ADS)

Kachenoura, A.; Porée, F.; Hernández, A. I.; Carrault, G.

2008-12-01

Current cardiac implantable devices offer improved processing power and recording capabilities. Some of these devices already provide basic telemonitoring features that may help to reduce health care expenditure. A challenge is posed in particular for the telemonitoring of the patient's cardiac electrical activity. Indeed, only intracardiac electrograms (EGMs) are acquired by the implanted device and these signals are difficult to analyze directly by clinicians. In this paper, we propose a patient-specific method to synthesize the surface electrocardiogram (ECG) from a set of EGM signals, based on a 3D representation of the cardiac electrical activity and principal component analysis (PCA). The results, in the case of sinus rhythm, show a correlation coefficient between the real ECG and the synthesized ECG of about 0.85. Moreover, the application of the proposed method to the patients who present an abnormal heart rhythm exhibits promising results, especially for characterizing the bundle branch blocs. Finally, in order to evaluate the behavior of our procedure in some practical situations, the quality of the ECG reconstruction is studied as a function of the number of EGM electrodes provided by the CIDs.

ECG-cryptography and authentication in body area networks.

PubMed

Zhang, Zhaoyang; Wang, Honggang; Vasilakos, Athanasios V; Fang, Hua

2012-11-01

Wireless body area networks (BANs) have drawn much attention from research community and industry in recent years. Multimedia healthcare services provided by BANs can be available to anyone, anywhere, and anytime seamlessly. A critical issue in BANs is how to preserve the integrity and privacy of a person's medical data over wireless environments in a resource efficient manner. This paper presents a novel key agreement scheme that allows neighboring nodes in BANs to share a common key generated by electrocardiogram (ECG) signals. The improved Jules Sudan (IJS) algorithm is proposed to set up the key agreement for the message authentication. The proposed ECG-IJS key agreement can secure data communications over BANs in a plug-n-play manner without any key distribution overheads. Both the simulation and experimental results are presented, which demonstrate that the proposed ECG-IJS scheme can achieve better security performance in terms of serval performance metrics such as false acceptance rate (FAR) and false rejection rate (FRR) than other existing approaches. In addition, the power consumption analysis also shows that the proposed ECG-IJS scheme can achieve energy efficiency for BANs.

Development of a portable Linux-based ECG measurement and monitoring system.

PubMed

Tan, Tan-Hsu; Chang, Ching-Su; Huang, Yung-Fa; Chen, Yung-Fu; Lee, Cheng

2011-08-01

This work presents a portable Linux-based electrocardiogram (ECG) signals measurement and monitoring system. The proposed system consists of an ECG front end and an embedded Linux platform (ELP). The ECG front end digitizes 12-lead ECG signals acquired from electrodes and then delivers them to the ELP via a universal serial bus (USB) interface for storage, signal processing, and graphic display. The proposed system can be installed anywhere (e.g., offices, homes, healthcare centers and ambulances) to allow people to self-monitor their health conditions at any time. The proposed system also enables remote diagnosis via Internet. Additionally, the system has a 7-in. interactive TFT-LCD touch screen that enables users to execute various functions, such as scaling a single-lead or multiple-lead ECG waveforms. The effectiveness of the proposed system was verified by using a commercial 12-lead ECG signal simulator and in vivo experiments. In addition to its portability, the proposed system is license-free as Linux, an open-source code, is utilized during software development. The cost-effectiveness of the system significantly enhances its practical application for personal healthcare.

Smartphone ECG for evaluation of STEMI: results of the ST LEUIS Pilot Study.

PubMed

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.

ECG denoising with adaptive bionic wavelet transform.

PubMed

Sayadi, Omid; Shamsollahi, Mohammad Bagher

2006-01-01

In this paper a new ECG denoising scheme is proposed using a novel adaptive wavelet transform, named bionic wavelet transform (BWT), which had been first developed based on a model of the active auditory system. There has been some outstanding features with the BWT such as nonlinearity, high sensitivity and frequency selectivity, concentrated energy distribution and its ability to reconstruct signal via inverse transform but the most distinguishing characteristic of BWT is that its resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential. Besides by optimizing the BWT parameters parallel to modifying a new threshold value, one can handle ECG denoising with results comparing to those of wavelet transform (WT). Preliminary tests of BWT application to ECG denoising were constructed on the signals of MIT-BIH database which showed high performance of noise reduction.

A Pilot Study Assessing ECG versus ECHO Ventriculoventricular Optimization in Pediatric Resynchronization Patients.

PubMed

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.

Screening entire healthcare system ECG database: Association of deep terminal negativity of P wave in lead V1 and ECG referral with mortality.

PubMed

Junell, Allison; Thomas, Jason; Hawkins, Lauren; Sklenar, Jiri; Feldman, Trevor; Henrikson, Charles A; Tereshchenko, Larisa G

2017-02-01

Each encounter of asymptomatic individuals with the healthcare system presents an opportunity for improvement of cardiovascular disease (CVD) awareness and sudden cardiac death (SCD) risk assessment. ECG sign deep terminal negativity of the P wave in V1 (DTNP V1 ) was shown to be associated with an increased risk of SCD in the general population. To evaluate association of DTNP V1 with all-cause mortality and newly diagnosed atrial fibrillation (AFib) in the large tertiary healthcare system patient population. Retrospective double cohort study compared two levels of exposure (automatically measured amplitude of P-prime (Pp) in V1): DTNP V1 (Pp from -100μV to -200μV) and ZeroPpV1 (Pp=0). An entire healthcare system (2010-2014) ECG database was screened. Medical records of children and patients with previously diagnosed AFib/atrial flutter (AFl), implanted pacemaker or cardioverter-defibrillator were excluded. DTNP V1 (n=3,413) and ZeroPpV1 (n=3,405) cohorts were matched by age and sex. Primary outcome was all-cause mortality. Secondary outcomes were newly diagnosed AFib/AFl. Median follow-up was 2.5 y. DTNP V1 was associated with all-cause mortality (HR 1.95(1.64-2.31); P<0.0001) and newly diagnosed AFib (HR 1.29(1.04-1.59); P=0.021) after adjustment for CVD, comorbidities, other ECG parameters, medications, and index ECG referral. Index ECG referral by a cardiologist was independently associated with 34% relative risk reduction of mortality (HR 0.66(0.52-0.84); P=0.001), as compared to ECG referral by a non-cardiologist. DTNP V1 is independently associated with twice higher risk of all-cause death, as compared to patients without P prime in V1. Life-saving effect of the index ECG referral by a cardiologist requires further study. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Correlation between ECG changes and early left ventricular remodeling in preadolescent footballers.

PubMed

Zdravkovic, M; Milovanovic, B; Hinic, S; Soldatovic, I; Durmic, T; Koracevic, G; Prijic, S; Markovic, O; Filipovic, B; Lovic, D

2017-03-01

The aim of this study was to assess the early electrocardiogram (ECG) changes induced by physical training in preadolescent elite footballers. This study included 94 preadolescent highly trained male footballers (FG) competing in Serbian Football League (minimum of 7 training hours/week) and 47 age-matched healthy male controls (less than 2 training hours/week) (CG). They were screened by ECG and echocardiography at a tertiary referral cardio center. Sokolow-Lyon index was used as a voltage electrocardiographic criterion for left ventricular hypertrophy diagnosis. Characteristic ECG intervals and voltage were compared and reference range was given for preadolescent footballers. Highly significant differences between FG and CG were registered in all ECG parameters: P-wave voltage (p < 0.001), S-wave (V1 or V2 lead) voltage (p < 0.001), R-wave (V5 and V6 lead) voltage (p < 0.001), ECG sum of S V 1-2  + R V 5-6 (p < 0.001), T-wave voltage (p < 0.001), QRS complex duration (p < 0.001), T-wave duration (p < 0.001), QTc interval duration (p < 0.001), and R/T ratio (p < 0.001). No differences were found in PQ interval duration between these two groups (p > 0.05). During 6-year follow-up period, there was no adverse cardiac event in these footballers. None of them expressed pathological ECG changes. Benign ECG changes are presented in the early stage of athlete's heart remodeling, but they are not related to pathological ECG changes and they should be regarded as ECG pattern of LV remodeling.

Computational Electrocardiography: Revisiting Holter ECG Monitoring.

PubMed

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.

Statistical performance evaluation of ECG transmission using wireless networks.

PubMed

Shakhatreh, Walid; Gharaibeh, Khaled; Al-Zaben, Awad

2013-07-01

This paper presents simulation of the transmission of biomedical signals (using ECG signal as an example) over wireless networks. Investigation of the effect of channel impairments including SNR, pathloss exponent, path delay and network impairments such as packet loss probability; on the diagnosability of the received ECG signal are presented. The ECG signal is transmitted through a wireless network system composed of two communication protocols; an 802.15.4- ZigBee protocol and an 802.11b protocol. The performance of the transmission is evaluated using higher order statistics parameters such as kurtosis and Negative Entropy in addition to the common techniques such as the PRD, RMS and Cross Correlation.

Decomposition of ECG by linear filtering.

PubMed

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.

An effective and efficient compression algorithm for ECG signals with irregular periods.

PubMed

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.

[Experience in the use of equipment for ECG system analysis in municipal polyclinics].

PubMed

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.

An IoT-cloud Based Wearable ECG Monitoring System for Smart Healthcare.

PubMed

Yang, Zhe; Zhou, Qihao; Lei, Lei; Zheng, Kan; Xiang, Wei

2016-12-01

Public healthcare has been paid an increasing attention given the exponential growth human population and medical expenses. It is well known that an effective health monitoring system can detect abnormalities of health conditions in time and make diagnoses according to the gleaned data. As a vital approach to diagnose heart diseases, ECG monitoring is widely studied and applied. However, nearly all existing portable ECG monitoring systems cannot work without a mobile application, which is responsible for data collection and display. In this paper, we propose a new method for ECG monitoring based on Internet-of-Things (IoT) techniques. ECG data are gathered using a wearable monitoring node and are transmitted directly to the IoT cloud using Wi-Fi. Both the HTTP and MQTT protocols are employed in the IoT cloud in order to provide visual and timely ECG data to users. Nearly all smart terminals with a web browser can acquire ECG data conveniently, which has greatly alleviated the cross-platform issue. Experiments are carried out on healthy volunteers in order to verify the reliability of the entire system. Experimental results reveal that the proposed system is reliable in collecting and displaying real-time ECG data, which can aid in the primary diagnosis of certain heart diseases.

A Hygroscopic Sensor Electrode for Fast Stabilized Non-Contact ECG Signal Acquisition

PubMed Central

Fong, Ee-May; Chung, Wan-Young

2015-01-01

A capacitive electrocardiography (cECG) technique using a non-invasive ECG measuring technology that does not require direct contact between the sensor and the skin has attracted much interest. The system encounters several challenges when the sensor electrode and subject’s skin are weakly coupled. Because there is no direct physical contact between the subject and any grounding point, there is no discharge path for the built-up electrostatic charge. Subsequently, the electrostatic charge build-up can temporarily contaminate the ECG signal from being clearly visible; a stabilization period (3–15 min) is required for the measurement of a clean, stable ECG signal at low humidity levels (below 55% relative humidity). Therefore, to obtain a clear ECG signal without noise and to reduce the ECG signal stabilization time to within 2 min in a dry ambient environment, we have developed a fabric electrode with embedded polymer (FEEP). The designed hygroscopic FEEP has an embedded superabsorbent polymer layer. The principle of FEEP as a conductive electrode is to provide humidity to the capacitive coupling to ensure strong coupling and to allow for the measurement of a stable, clear biomedical signal. The evaluation results show that hygroscopic FEEP is capable of rapidly measuring high-accuracy ECG signals with a higher SNR ratio. PMID:26251913

A Hygroscopic Sensor Electrode for Fast Stabilized Non-Contact ECG Signal Acquisition.

PubMed

Fong, Ee-May; Chung, Wan-Young

2015-08-05

A capacitive electrocardiography (cECG) technique using a non-invasive ECG measuring technology that does not require direct contact between the sensor and the skin has attracted much interest. The system encounters several challenges when the sensor electrode and subject's skin are weakly coupled. Because there is no direct physical contact between the subject and any grounding point, there is no discharge path for the built-up electrostatic charge. Subsequently, the electrostatic charge build-up can temporarily contaminate the ECG signal from being clearly visible; a stabilization period (3-15 min) is required for the measurement of a clean, stable ECG signal at low humidity levels (below 55% relative humidity). Therefore, to obtain a clear ECG signal without noise and to reduce the ECG signal stabilization time to within 2 min in a dry ambient environment, we have developed a fabric electrode with embedded polymer (FEEP). The designed hygroscopic FEEP has an embedded superabsorbent polymer layer. The principle of FEEP as a conductive electrode is to provide humidity to the capacitive coupling to ensure strong coupling and to allow for the measurement of a stable, clear biomedical signal. The evaluation results show that hygroscopic FEEP is capable of rapidly measuring high-accuracy ECG signals with a higher SNR ratio.

The availability of prior ECGs improves paramedic accuracy in recognizing ST-segment elevation myocardial infarction.

PubMed

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.

An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm.

PubMed

Qin, Qin; Li, Jianqing; Yue, Yinggao; Liu, Chengyu

2017-01-01

R-peak detection is crucial in electrocardiogram (ECG) signal analysis. This study proposed an adaptive and time-efficient R-peak detection algorithm for ECG processing. First, wavelet multiresolution analysis was applied to enhance the ECG signal representation. Then, ECG was mirrored to convert large negative R-peaks to positive ones. After that, local maximums were calculated by the first-order forward differential approach and were truncated by the amplitude and time interval thresholds to locate the R-peaks. The algorithm performances, including detection accuracy and time consumption, were tested on the MIT-BIH arrhythmia database and the QT database. Experimental results showed that the proposed algorithm achieved mean sensitivity of 99.39%, positive predictivity of 99.49%, and accuracy of 98.89% on the MIT-BIH arrhythmia database and 99.83%, 99.90%, and 99.73%, respectively, on the QT database. By processing one ECG record, the mean time consumptions were 0.872 s and 0.763 s for the MIT-BIH arrhythmia database and QT database, respectively, yielding 30.6% and 32.9% of time reduction compared to the traditional Pan-Tompkins method.

An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm

PubMed Central

Qin, Qin

2017-01-01

R-peak detection is crucial in electrocardiogram (ECG) signal analysis. This study proposed an adaptive and time-efficient R-peak detection algorithm for ECG processing. First, wavelet multiresolution analysis was applied to enhance the ECG signal representation. Then, ECG was mirrored to convert large negative R-peaks to positive ones. After that, local maximums were calculated by the first-order forward differential approach and were truncated by the amplitude and time interval thresholds to locate the R-peaks. The algorithm performances, including detection accuracy and time consumption, were tested on the MIT-BIH arrhythmia database and the QT database. Experimental results showed that the proposed algorithm achieved mean sensitivity of 99.39%, positive predictivity of 99.49%, and accuracy of 98.89% on the MIT-BIH arrhythmia database and 99.83%, 99.90%, and 99.73%, respectively, on the QT database. By processing one ECG record, the mean time consumptions were 0.872 s and 0.763 s for the MIT-BIH arrhythmia database and QT database, respectively, yielding 30.6% and 32.9% of time reduction compared to the traditional Pan-Tompkins method. PMID:29104745

Improving Remote Health Monitoring: A Low-Complexity ECG Compression Approach

PubMed Central

Al-Ali, Abdulla; Mohamed, Amr; Ward, Rabab

2018-01-01

Recent advances in mobile technology have created a shift towards using battery-driven devices in remote monitoring settings and smart homes. Clinicians are carrying out diagnostic and screening procedures based on the electrocardiogram (ECG) signals collected remotely for outpatients who need continuous monitoring. High-speed transmission and analysis of large recorded ECG signals are essential, especially with the increased use of battery-powered devices. Exploring low-power alternative compression methodologies that have high efficiency and that enable ECG signal collection, transmission, and analysis in a smart home or remote location is required. Compression algorithms based on adaptive linear predictors and decimation by a factor B/K are evaluated based on compression ratio (CR), percentage root-mean-square difference (PRD), and heartbeat detection accuracy of the reconstructed ECG signal. With two databases (153 subjects), the new algorithm demonstrates the highest compression performance (CR=6 and PRD=1.88) and overall detection accuracy (99.90% sensitivity, 99.56% positive predictivity) over both databases. The proposed algorithm presents an advantage for the real-time transmission of ECG signals using a faster and more efficient method, which meets the growing demand for more efficient remote health monitoring. PMID:29337892

Improving Remote Health Monitoring: A Low-Complexity ECG Compression Approach.

PubMed

Elgendi, Mohamed; Al-Ali, Abdulla; Mohamed, Amr; Ward, Rabab

2018-01-16

Recent advances in mobile technology have created a shift towards using battery-driven devices in remote monitoring settings and smart homes. Clinicians are carrying out diagnostic and screening procedures based on the electrocardiogram (ECG) signals collected remotely for outpatients who need continuous monitoring. High-speed transmission and analysis of large recorded ECG signals are essential, especially with the increased use of battery-powered devices. Exploring low-power alternative compression methodologies that have high efficiency and that enable ECG signal collection, transmission, and analysis in a smart home or remote location is required. Compression algorithms based on adaptive linear predictors and decimation by a factor B / K are evaluated based on compression ratio (CR), percentage root-mean-square difference (PRD), and heartbeat detection accuracy of the reconstructed ECG signal. With two databases (153 subjects), the new algorithm demonstrates the highest compression performance ( CR = 6 and PRD = 1.88 ) and overall detection accuracy (99.90% sensitivity, 99.56% positive predictivity) over both databases. The proposed algorithm presents an advantage for the real-time transmission of ECG signals using a faster and more efficient method, which meets the growing demand for more efficient remote health monitoring.

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…

Mobile GPU-based implementation of automatic analysis method for long-term ECG.

PubMed

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

A harmonic linear dynamical system for prominent ECG feature extraction.

PubMed

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.

[Development of a portable ambulatory ECG monitor based on embedded microprocessor unit].

PubMed

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.

Performance of human body communication-based wearable ECG with capacitive coupling electrodes

PubMed Central

Sakuma, Jun; Anzai, Daisuke

2016-01-01

Wearable electrocardiogram (ECG) is attracting much attention in daily healthcare applications, and human body communication (HBC) technology provides an evident advantage in making the sensing electrodes of ECG also working for transmission through the human body. In view of actual usage in daily life, however, non-contact electrodes to the human body are desirable. In this Letter, the authors discussed the ECG circuit structure in the HBC-based wearable ECG for removing the common mode noise when employing non-contact capacitive coupling electrodes. Through the comparison of experimental results, they have shown that the authors’ proposed circuit structure with the third electrode directly connected to signal ground can provide an effect on common mode noise reduction similar to the usual drive-right-leg circuit, and a sufficiently good acquisition performance of ECG signals. PMID:27733931

Performance of human body communication-based wearable ECG with capacitive coupling electrodes.

PubMed

Sakuma, Jun; Anzai, Daisuke; Wang, Jianqing

2016-09-01

Wearable electrocardiogram (ECG) is attracting much attention in daily healthcare applications, and human body communication (HBC) technology provides an evident advantage in making the sensing electrodes of ECG also working for transmission through the human body. In view of actual usage in daily life, however, non-contact electrodes to the human body are desirable. In this Letter, the authors discussed the ECG circuit structure in the HBC-based wearable ECG for removing the common mode noise when employing non-contact capacitive coupling electrodes. Through the comparison of experimental results, they have shown that the authors' proposed circuit structure with the third electrode directly connected to signal ground can provide an effect on common mode noise reduction similar to the usual drive-right-leg circuit, and a sufficiently good acquisition performance of ECG signals.

Evaluation of a web-based ECG-interpretation programme for undergraduate medical students.

PubMed

Nilsson, Mikael; Bolinder, Gunilla; Held, Claes; Johansson, Bo-Lennart; Fors, Uno; Ostergren, Jan

2008-04-23

Most clinicians and teachers agree that knowledge about ECG is of importance in the medical curriculum. Students at Karolinska Institute have asked for more training in ECG-interpretation during their undergraduate studies. Clinical tutors, however, have difficulties in meeting these demands due to shortage of time. Thus, alternative ways to learn and practice ECG-interpretation are needed. Education offered via the Internet is readily available, geographically independent and flexible. Furthermore, the quality of education may increase and become more effective through a superior educational approach, improved visualization and interactivity. A Web-based comprehensive ECG-interpretation programme has been evaluated. Medical students from the sixth semester were given an optional opportunity to access the programme from the start of their course. Usage logs and an initial evaluation survey were obtained from each student. A diagnostic test was performed in order to assess the effect on skills in ECG interpretation. Students from the corresponding course, at another teaching hospital and without access to the ECG-programme but with conventional teaching of ECG served as a control group. 20 of the 32 students in the intervention group had tested the programme after 2 months. On a five-graded scale (1- bad to 5 - very good) they ranked the utility of a web-based programme for this purpose as 4.1 and the quality of the programme software as 3.9. At the diagnostic test (maximal points 16) by the end of the 5-month course at the 6th semester the mean result for the students in the intervention group was 9.7 compared with 8.1 for the control group (p = 0.03). Students ranked the Web-based ECG-interpretation programme as a useful instrument to learn ECG. Furthermore, Internet-delivered education may be more effective than traditional teaching methods due to greater immediacy, improved visualisation and interactivity.

Cancelable ECG biometrics using GLRT and performance improvement using guided filter with irreversible guide signal.

PubMed

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.

The short-term effect of smoking on fetal ECG.

PubMed

Péterfi, István; Kellényi, Lóránd; Péterfi, Lehel; Szilágyi, András

2017-10-26

The number of women who smoke during pregnancy is significant even today. The harmful effects of smoking during pregnancy are well known but there are no data on the effects of smoking on fetal electrocardiography (ECG). The lack of data is in connection with the difficulties of recording fetal ECG through the maternal abdomen. Third trimester pregnant women who were not able to give up the harmful passion of smoking despite repeated attempts of persuasion were recruited in the study on voluntary basis. The fetal ECG was recorded non-invasively through the maternal abdomen before, during and after smoking, then the data were processed offline. The electrophysiological measurements were performed by a self developed ECG device, which allowed the examination of the morphological differences in "true-to-form" fetal ECG in addition to studying the variability of fetal heart rate. The study involved nine pregnant women. The observed changes are presented through case studies of those pregnant women who showed the most significant anomalies. Compared with the resting state fetal heart rate was increased during smoking. The short-term variability of fetal heart rate was narrowed, while the mother's heart rate did not change significantly - which was an indication of direct fetal stress. No explicit ischemic signs were detected in fetal ECG during smoking, however, in the increasing period of the fetal heart rate, the T wave morphology changed slightly, then it returned to normal. Demonstrable by the electrophysiological methods, smoking has a direct effect on fetal cardiac function. The fetal heart rate variability shows a pattern during smoking which is a typical sign of stress conditions among adults. The results may have educational consequences as well. Understanding those, hopefully will help pregnant women give up this harmful addiction.

Wireless Sensor-Based Smart-Clothing Platform for ECG Monitoring

PubMed Central

Lin, Chung-Chih; Yu, Yan-Shuo

2015-01-01

The goal of this study is to use wireless sensor technologies to develop a smart clothes service platform for health monitoring. Our platform consists of smart clothes, a sensor node, a gateway server, and a health cloud. The smart clothes have fabric electrodes to detect electrocardiography (ECG) signals. The sensor node improves the accuracy of QRS complexes detection by morphology analysis and reduces power consumption by the power-saving transmission functionality. The gateway server provides a reconfigurable finite state machine (RFSM) software architecture for abnormal ECG detection to support online updating. Most normal ECG can be filtered out, and the abnormal ECG is further analyzed in the health cloud. Three experiments are conducted to evaluate the platform's performance. The results demonstrate that the signal-to-noise ratio (SNR) of the smart clothes exceeds 37 dB, which is within the “very good signal” interval. The average of the QRS sensitivity and positive prediction is above 99.5%. Power-saving transmission is reduced by nearly 1980 times the power consumption in the best-case analysis. PMID:26640512

Wireless Sensor-Based Smart-Clothing Platform for ECG Monitoring.

PubMed

Wang, Jie; Lin, Chung-Chih; Yu, Yan-Shuo; Yu, Tsang-Chu

2015-01-01

The goal of this study is to use wireless sensor technologies to develop a smart clothes service platform for health monitoring. Our platform consists of smart clothes, a sensor node, a gateway server, and a health cloud. The smart clothes have fabric electrodes to detect electrocardiography (ECG) signals. The sensor node improves the accuracy of QRS complexes detection by morphology analysis and reduces power consumption by the power-saving transmission functionality. The gateway server provides a reconfigurable finite state machine (RFSM) software architecture for abnormal ECG detection to support online updating. Most normal ECG can be filtered out, and the abnormal ECG is further analyzed in the health cloud. Three experiments are conducted to evaluate the platform's performance. The results demonstrate that the signal-to-noise ratio (SNR) of the smart clothes exceeds 37 dB, which is within the "very good signal" interval. The average of the QRS sensitivity and positive prediction is above 99.5%. Power-saving transmission is reduced by nearly 1980 times the power consumption in the best-case analysis.

Identifying QT prolongation from ECG impressions using a general-purpose Natural Language Processor

PubMed Central

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

A new feature detection mechanism and its application in secured ECG transmission with noise masking.

PubMed

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.

Non-invasive Foetal ECG – a Comparable Alternative to the Doppler CTG?

PubMed Central

Reinhard, J.; Louwen, F.

2012-01-01

This review discusses the alternative of using the non-invasive foetal ECG compared with the conventionally used Doppler CTG. Non-invasive abdominal electrocardiograms (ECG) have been approved for clinical routine since 2008; subsequently they were also approved for antepartum and subpartum procedures. The first study results have been published. Non-invasive foetal ECG is especially indicated during early pregnancy, while the Doppler CTG is recommended for the vernix period. Beyond the vernix period no difference has been recorded in the success rate of either approach. The foetal ECG signal quality is independent of the BMI, whereas the success rate of the Doppler CTG is diminished with an increased BMI. During the first stage of labour, non-invasive foetal ECG demonstrates better signal quality; however during the second stage of labour no difference has been identified between the methods. PMID:25308981

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 computer-aided ECG diagnostic tool.

PubMed

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.

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.

CNT/PDMS composite flexible dry electrodes for long-term ECG monitoring.

PubMed

Jung, Ha-Chul; Moon, Jin-Hee; Baek, Dong-Hyun; Lee, Jae-Hee; Choi, Yoon-Young; Hong, Joung-Sook; Lee, Sang-Hoon

2012-05-01

We fabricated a carbon nanotube (CNT)/ polydimethylsiloxane (PDMS) composite-based dry ECG electrode that can be readily connected to conventional ECG devices, and showed its long-term wearable monitoring capability and robustness to motion and sweat. While the dispersion of CNTs in PDMS is challenging, we optimized the process to disperse untreated CNTs within PDMS by mechanical force only. The electrical and mechanical characteristics of the CNT/PDMS electrode were tested according to the concentration of CNTs and its thickness. The performances of ECG electrodes were evaluated by using 36 types of electrodes which were fabricated with different concentrations of CNTs, and with a differing diameter and thickness. The ECG signals were obtained by using electrodes of diverse sizes to observe the effects of motion and sweat, and the proposed electrode was shown to be robust to both factors. The CNT concentration and diameter of the electrodes were critical parameters in obtaining high-quality ECG signals. The electrode was shown to be biocompatible from the cytotoxicity test. A seven-day continuous wearability test showed that the quality of the ECG signal did not degrade over time, and skin reactions such as itching or erythema were not observed. This electrode could be used for the long-term measurement of other electrical biosignals for ubiquitous health monitoring including EMG, EEG, and ERG.

[The relationship of ECG and pregnancy outcome of older pregnant woman in late pregnancy].

PubMed

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.

Microprocessor Based Real-Time Monitoring of Multiple ECG Signals

PubMed Central

Nasipuri, M.; Basu, D.K.; Dattagupta, R.; Kundu, M.; Banerjee, S.

1987-01-01

A microprocessor based system capable of realtime monitoring of multiple ECG signals has been described. The system consists of a number of microprocessors connected in a hierarchical fashion and capable of working concurrently on ECG data collected from different channels. The system can monitor different arrhythmic abnormalities for at least 36 patients even for a heart rate of 500 beats/min.

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.

A novel ECG data compression method based on adaptive Fourier decomposition

NASA Astrophysics Data System (ADS)

Tan, Chunyu; Zhang, Liming

2017-12-01

This paper presents a novel electrocardiogram (ECG) compression method based on adaptive Fourier decomposition (AFD). AFD is a newly developed signal decomposition approach, which can decompose a signal with fast convergence, and hence reconstruct ECG signals with high fidelity. Unlike most of the high performance algorithms, our method does not make use of any preprocessing operation before compression. Huffman coding is employed for further compression. Validated with 48 ECG recordings of MIT-BIH arrhythmia database, the proposed method achieves the compression ratio (CR) of 35.53 and the percentage root mean square difference (PRD) of 1.47% on average with N = 8 decomposition times and a robust PRD-CR relationship. The results demonstrate that the proposed method has a good performance compared with the state-of-the-art ECG compressors.

ECG-derived respiration based on iterated Hilbert transform and Hilbert vibration decomposition.

PubMed

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

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.

A Novel Approach to ECG Classification Based upon Two-Layered HMMs in Body Sensor Networks

PubMed Central

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

MYBPC3 hypertrophic cardiomyopathy can be detected by using advanced ECG in children and young adults.

PubMed

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

Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography

PubMed Central

Penzel, Thomas; Kantelhardt, Jan W.; Bartsch, Ronny P.; Riedl, Maik; Kraemer, Jan F.; Wessel, Niels; Garcia, Carmen; Glos, Martin; Fietze, Ingo; Schöbel, Christoph

2016-01-01

The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However, their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG, and cardio-respiratory couplings in a chronological (historical) sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability (HRV) analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave). PMID:27826247

Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography.

PubMed

Penzel, Thomas; Kantelhardt, Jan W; Bartsch, Ronny P; Riedl, Maik; Kraemer, Jan F; Wessel, Niels; Garcia, Carmen; Glos, Martin; Fietze, Ingo; Schöbel, Christoph

2016-01-01

The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However, their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG, and cardio-respiratory couplings in a chronological (historical) sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability (HRV) analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave).

Utility of Electrocardiography (ECG)-Gated Computed Tomography (CT) for Preoperative Evaluations of Thymic Epithelial Tumors.

PubMed

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.

Utility of Electrocardiography (ECG)-Gated Computed Tomography (CT) for Preoperative Evaluations of Thymic Epithelial Tumors

PubMed Central

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

A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm

PubMed Central

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

Left ventricular hypertrophy by ECG versus cardiac MRI as a predictor for heart failure.

PubMed

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/.

Ambulatory ECG monitoring in atrial fibrillation management.

PubMed

Rosero, Spencer Z; Kutyifa, Valentina; Olshansky, Brian; Zareba, Wojciech

2013-01-01

Ambulatory ECG monitoring technology has rapidly evolved over the last few decades and has been shown to identify life-threatening and non-life threatening arrhythmias and provide actionable data to guide clinical decision making. Atrial fibrillation episodes can often be asymptomatic, even after catheter ablation for atrial fibrillation, creating a disconnect between symptoms and actual arrhythmia burden which may alter clinical management. In this review, we aim to provide a comprehensive overview of invasive and non-invasive ECG monitoring strategies in patients with atrial fibrillation, with a special focus on the diagnosis of atrial fibrillation, and on follow-up of patients after catheter ablation for atrial fibrillation ablation. © 2013.

Chaos control applied to cardiac rhythms represented by ECG signals

NASA Astrophysics Data System (ADS)

Borem Ferreira, Bianca; Amorim Savi, Marcelo; Souza de Paula, Aline

2014-10-01

The control of irregular or chaotic heartbeats is a key issue in cardiology. In this regard, chaos control techniques represent a good alternative since they suggest treatments different from those traditionally used. This paper deals with the application of the extended time-delayed feedback control method to stabilize pathological chaotic heart rhythms. Electrocardiogram (ECG) signals are employed to represent the cardiovascular behavior. A mathematical model is employed to generate ECG signals using three modified Van der Pol oscillators connected with time delay couplings. This model provides results that qualitatively capture the general behavior of the heart. Controlled ECG signals show the ability of the strategy either to control or to suppress the chaotic heart dynamics generating less-critical behaviors.

Design intelligent wheelchair with ECG measurement and wireless transmission function.

PubMed

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.

Asymptomatic Wolff-Parkinson-White Pattern ECG in USAF Aviators.

PubMed

Davenport, Eddie D; Rupp, Karen A N; Palileo, Edwin; Haynes, Jared

2017-01-01

Wolff-Parkinson-White (WPW) pattern is occasionally found in asymptomatic aviators during routine ECGs. Aeromedical concerns regarding WPW pattern include risk of dysrhythmia or sudden cardiac death (SCD), thus affecting the safety of flight. The purpose of this study was to determine the prevalence and outcomes of aviators with asymptomatic WPW pattern and assess for risk factors that contribute to progression to dysrhythmia or symptoms. The U.S. Air Force (USAF) ECG library database containing over 1.2 million ECGs collected over the past 68 yr was used to identify 638 individual aviators with WPW pattern. Demographic, medical history, and outcome data were obtained by medical record review. Aviators who developed high risk features defined as symptoms, arrhythmia, or ablation of a high risk pathway, were compared to those who remained asymptomatic. Prevalence of WPW pattern was 0.30% among all USAF aviators. Of the 638 individuals, 64 (10%) progressed to the combined endpoint of SCD, arrhythmia, and/or ablation of a high risk pathway over 6868 patient years, with average follow-up of 10.5 yr. There were two sudden cardiac deaths (0.3%). Annual risk of possible sudden incapacitation was 0.95% and of SCD 0.03%. Those that progressed to high risk were significantly younger, had lower diastolic blood pressure, lower total cholesterol, and better physical fitness testing scores. WPW pattern on ECG found in asymptomatic aviators confers < 1% annual risk of arrhythmia or incapacitating events with the highest risk in the younger, healthier, and most fit populations.Davenport ED, Rupp KAN, Palileo E, Haynes J. Asymptomatic Wolff-Parkinson-White pattern ECG in USAF aviators. Aerosp Med Hum Perform. 2017; 88(1):56-60.

Making Sense of the ECG - Cases for Self-Assessment Houghton Andrew R Gray David Making Sense of the ECG - Cases for Self-Assessment 290pp Hodder Education 9780340946893 034094689X [Formula: see text].

PubMed

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.

Cohort Study of ECG Left Ventricular Hypertrophy Trajectories: Ethnic Disparities, Associations With Cardiovascular Outcomes, and Clinical Utility.

PubMed

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.

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

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

A compact ECG R-R interval, respiration and activity recording system.

PubMed

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.

Reconstruction of an 8-lead surface ECG from two subcutaneous ICD vectors.

PubMed

Wilson, David G; Cronbach, Peter L; Panfilo, D; Greenhut, Saul E; Stegemann, Berthold P; Morgan, John M

2017-06-01

Techniques exist which allow surface ECGs to be reconstructed from reduced lead sets. We aimed to reconstruct an 8-lead ECG from two independent S-ICD sensing electrodes vectors as proof of this principle. Participants with ICDs (N=61) underwent 3minute ECGs using a TMSi Porti7 multi-channel signal recorder (TMS international, The Netherlands) with electrodes in the standard S-ICD and 12-lead positions. Participants were randomised to either a training (N=31) or validation (N=30) group. The transformation used was a linear combination of the 2 independent S-ICD vectors to each of the 8 independent leads of the 12-lead ECG, with coefficients selected that minimized the root mean square error (RMSE) between recorded and derived ECGs when applied to the training group. The transformation was then applied to the validation group and agreement between the recorded and derived lead pairs was measured by Pearson correlation coefficient (r) and normalised RMSE (NRMSE). In total, 27 patients with complete data sets were included in the validation set consisting of 57,888 data points from 216 full lead sets. The distribution of the r and NRMSE were skewed. Mean r=0.770 (SE 0.024), median r=0.925. NRMSE mean=0.233 (SE 0.015) median=0.171. We have demonstrated that the reconstruction of an 8-lead ECG from two S-ICD vectors is possible. If perfected, the ability to generate accurate multi-lead surface ECG data from an S-ICD would potentially allow recording and review of clinical arrhythmias at follow-up. Copyright © 2017 Elsevier B.V. All rights reserved.

Interoperability in digital electrocardiography: harmonization of ISO/IEEE x73-PHD and SCP-ECG.

PubMed

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.

Real-time ECG monitoring and arrhythmia detection using Android-based mobile devices.

PubMed

Gradl, Stefan; Kugler, Patrick; Lohmuller, Clemens; Eskofier, Bjoern

2012-01-01

We developed an application for Android™-based mobile devices that allows real-time electrocardiogram (ECG) monitoring and automated arrhythmia detection by analyzing ECG parameters. ECG data provided by pre-recorded files or acquired live by accessing a Shimmer™ sensor node via Bluetooth™ can be processed and evaluated. The application is based on the Pan-Tompkins algorithm for QRS-detection and contains further algorithm blocks to detect abnormal heartbeats. The algorithm was validated using the MIT-BIH Arrhythmia and MIT-BIH Supraventricular Arrhythmia databases. More than 99% of all QRS complexes were detected correctly by the algorithm. Overall sensitivity for abnormal beat detection was 89.5% with a specificity of 80.6%. The application is available for download and may be used for real-time ECG-monitoring on mobile devices.

Design and implementation of a 3-lead ECG wireless remote monitoring system

NASA Astrophysics Data System (ADS)

Zhang, Shi; Jia, Xiaonan; Shang, Shuai

2006-11-01

Cardiovascular disease is one of the main diseases that menaces human health. It is necessary to monitor the patient's real-time electrocardiograph (ECG) for a long time to realize diagnosis and salvage. Remote ECG monitoring system is the solution. This paper introduces the design and implement of a 3-lead ECG wireless remote monitoring system. It collects, stores and transmits user's ECG which can be received by hospital and diagnosed by doctors. The development of the whole system contains three parts, the hardware and embedded software implementation of MONITOR, software of the MONITORING CENTER, and the routing software of NETWORK CENTER. According to the clinic experimentation, this system has high reliability and utility. There will be great social and economic benefit if this system is put into use.

Subcutaneous ICD screening with the Boston Scientific ZOOM programmer versus a 12-lead ECG machine.

PubMed

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.

ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

NASA Astrophysics Data System (ADS)

Kora, Padmavathi; Sri Rama Krishna, K.

2016-12-01

Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

Effects of electrocardiography contamination and comparison of ECG removal methods on upper trapezius electromyography recordings.

PubMed

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.

Classification of a Driver's cognitive workload levels using artificial neural network on ECG signals.

PubMed

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.

Evaluating ECG and carboxyhemoglobin changes due to smoking narghile.

PubMed

Yıldırım, Fazıl; Çevik, Yunsur; Emektar, Emine; Çorbacıoğlu, Şeref Kerem; Katırcı, Yavuz

2016-10-01

This study aimed to investigate whether increased carboxyhemoglobin (COHB) levels and ECG changes, which associated with fatal ventricular dysrhythmias, including increased QT, P-wave and T peak (Tp)-Tend (Te) dispersion, can be detected after smoking narghile, which is a traditional method of smoking tobacco that is smoked from hookah device. After local ethics committee approval, this prospective study was conducted using healthy volunteer subjects at a "narghile café," which is used by people smoking narghile in an open area. Before beginning to smoke narghile, all subjects' 12-lead electrocardiographs (ECG), measurements of COHB levels, and vital signs were recorded. After smoking narghile for 30 min, the recording of the 12-lead ECGs and the measurements of COHB level and all vital signs were repeated. The mean age of subjects was 26.8 ± 6.2 years (min-max: 18-40), and 28 subjects (84.8%) were male. Before smoking narghile, the median value of subjects' COHB levels was 1.3% (min-max: 0-6), whereas after smoking, the median value of COHB was 23.7% (min-max: 6-44), a statistically significant increase (p < 0.001). Analysis of the subjects' ECG changes after smoking narghile showed that dispersions of QT, QTc, P-wave and Tp-Te were increased, and all changes were statistically significant (p < 0.001 for all parameters). Although, especially among young people, it is commonly thought that smoking narghile has less harmful or toxic effects than other tobacco products. The results of this study and past studies clearly demonstrated that smoking narghile can cause several ECG changes - including increased QT, P-wave and Tp-Te dispersion - which can be associated with ventricular dysrhythmias.

Association between obesity and ECG variables in children and adolescents: A cross-sectional study.

PubMed

Sun, Guo-Zhe; Li, Yang; Zhou, Xing-Hu; Guo, Xiao-Fan; Zhang, Xin-Gang; Zheng, Li-Qiang; Li, Yuan; Jiao, Yun-DI; Sun, Ying-Xian

2013-12-01

Obesity exhibits a wide variety of electrocardiogram (ECG) abnormalities in adults, which often lead to cardiovascular events. However, there is currently no evidence of an association between obesity and ECG variables in children and adolescents. The present study aimed to explore the associations between obesity and ECG intervals and axes in children and adolescents. A cross-sectional observational study of 5,556 students aged 5-18 years was performed. Anthropometric data, blood pressure and standard 12-lead ECGs were collected for each participant. ECG variables were measured manually based on the temporal alignment of simultaneous 12 leads using a CV200 ECG Work Station. Overweight and obese groups demonstrated significantly longer PR intervals, wider QRS durations and leftward shifts of frontal P-wave, QRS and T-wave axes, while the obese group also demonstrated significantly higher heart rates, compared with normal weight groups within normotensive or hypertensive subjects (P<0.05). Abdominal obesity was also associated with longer PR intervals, wider QRS duration and a leftward shift of frontal ECG axes compared with normal waist circumference (WC) within normotensive or hypertensive subjects (P<0.05). Gender was a possible factor affecting the ECG variables. Furthermore, the ECG variables, including PR interval, QRS duration and frontal P-wave, QRS and T-wave axes, were significantly linearly correlated with body mass index, WC and waist-to-height ratio adjusted for age, gender, ethnicity and blood pressure. However, there was no significant association between obesity and the corrected QT interval (P>0.05). The results of the current study indicate that in children and adolescents, general and abdominal obesity is associated with longer PR intervals, wider QRS duration and a leftward shift of frontal P-wave, QRS and T-wave axes, independent of age, gender, ethnicity and blood pressure.

Coronary CT Angiography Incorporating Doppler-Guided Prospective ECG Gating in Patients with High Heart Rate: Comparison with Results of Traditional Prospective ECG Gating

PubMed Central

Li, Min; Yu, Bing-bing; Wu, Jian-hua; Xu, Lin; Sun, Gang

2013-01-01

Purpose As Doppler ultrasound has been proven to be an effective tool to predict and compress the optimal pulsing windows, we evaluated the effective dose and diagnostic accuracy of coronary CT angiography (CTA) incorporating Doppler-guided prospective electrocardiograph (ECG) gating, which presets pulsing windows according to Doppler analysis, in patients with a heart rate >65 bpm. Materials and Methods 119 patients with a heart rate >65 bpm who were scheduled for invasive coronary angiography were prospectively studied, and patients were randomly divided into traditional prospective (n = 61) and Doppler-guided prospective (n = 58) ECG gating groups. The exposure window of traditional prospective ECG gating was set at 30%–80% of the cardiac cycle. For the Doppler group, the length of diastasis was analyzed by Doppler. For lengths greater than 90 ms, the pulsing window was preset during diastole (during 60%–80%); otherwise, the optimal pulsing intervals were moved from diastole to systole (during 30%–50%). Results The mean heart rates of the traditional ECG and the Doppler-guided group during CT scanning were 75.0±7.7 bpm (range, 66–96 bpm) and 76.5±5.4 bpm (range: 66–105 bpm), respectively. The results indicated that whereas the image quality showed no significant difference between the traditional and Doppler groups (P = 0.42), the radiation dose of the Doppler group was significantly lower than that of the traditional group (5.2±3.4mSv vs. 9.3±4.5mSv, P<0.001). The sensitivities of CTA applying traditional and Doppler-guided prospective ECG gating to diagnose stenosis on a segment level were 95.5% and 94.3%, respectively; specificities 98.0% and 97.1%, respectively; positive predictive values 90.7% and 88.2%, respectively; negative predictive values 99.0% and 98.7%, respectively. There was no statistical difference in concordance between the traditional and Doppler groups (P = 0.22). Conclusion Doppler-guided prospective ECG gating

The Telemetric and Holter ECG Warehouse Initiative (THEW): a Data Repository for the Design, Implementation and Validation of ECG-related Technologies

PubMed Central

Couderc, Jean-Philippe

2011-01-01

We present an initiative supported by the National Heart Lung, and Blood Institute and the Food and Drug Administration for the development of a repository containing continuous electrocardiographic information to be shared with the worldwide scientific community. We believe that sharing data reinforces open scientific inquiry. It encourages diversity of analysis and opinion while promoting new research and facilitating the education of new researchers. In this paper, we present the resources available in this initiative for the scientific community. We describe the set of ECG signals currently hosted and we briefly discuss the associated clinical information (medical history. Disease and study-specific endpoints) and software tools we propose. Currently, the repository contains more than 250GB of data from eight clinical studies including healthy individuals and cardiac patients. This data is available for the development, implementation and validation of technologies related to body-surface ECGs. To conclude, the Telemetric and Holter ECG Warehouse (THEW) is an initiative developed to benefit the scientific community and to advance the field of quantitative electrocardiography and cardiac safety. PMID:21097349

Saturation of the right-leg drive amplifier in low-voltage ECG monitors.

PubMed

Freeman, Daniel K; Gatzke, Ronald D; Mallas, Georgios; Chen, Yu; Brouse, Chris J

2015-01-01

Electrocardiogram (ECG) monitoring is a critical tool in patient care, but its utility is often balanced with frustration from clinicians who are constantly distracted by false alarms. This has motivated the need to readdress the major factors that contribute to ECG noise with the goal of reducing false alarms. In this study, we describe a previously unreported phenomenon in which ECG noise can result from an unintended interaction between two systems: 1) the dc lead-off circuitry that is used to detect whether electrodes fall off the patient; and 2) the right-leg drive (RLD) system that is responsible for reducing ac common-mode noise that couples into the body. Using a circuit model to study this interaction, we found that in the presence of a dc lead-off system, even moderate increases in the right-leg skin-electrode resistance can cause the RLD amplifier to saturate. Such saturation can produce ECG noise because the RLD amplifier will no longer be capable of attenuating ac common-mode noise on the body. RLD saturation is particularly a problem for modern ECG monitors that use low-voltage supply levels. For example, for a 12-lead ECG and a 2 V power supply, saturation will occur when the right-leg electrode resistance reaches only 2 MΩ. We discuss several design solutions that can be used in low-voltage monitors to avoid RLD saturation.

Application of exercise ECG stress test in the current high cost modern-era healthcare system.

PubMed

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.

Design of a smart ECG garment based on conductive textile electrode and flexible printed circuit board.

PubMed

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.

Motion artifact removal algorithm by ICA for e-bra: a women ECG measurement system

NASA Astrophysics Data System (ADS)

Kwon, Hyeokjun; Oh, Sechang; Varadan, Vijay K.

2013-04-01

Wearable ECG(ElectroCardioGram) measurement systems have increasingly been developing for people who suffer from CVD(CardioVascular Disease) and have very active lifestyles. Especially, in the case of female CVD patients, several abnormal CVD symptoms are accompanied with CVDs. Therefore, monitoring women's ECG signal is a significant diagnostic method to prevent from sudden heart attack. The E-bra ECG measurement system from our previous work provides more convenient option for women than Holter monitor system. The e-bra system was developed with a motion artifact removal algorithm by using an adaptive filter with LMS(least mean square) and a wandering noise baseline detection algorithm. In this paper, ICA(independent component analysis) algorithms are suggested to remove motion artifact factor for the e-bra system. Firstly, the ICA algorithms are developed with two kinds of statistical theories: Kurtosis, Endropy and evaluated by performing simulations with a ECG signal created by sgolayfilt function of MATLAB, a noise signal including 0.4Hz, 1.1Hz and 1.9Hz, and a weighed vector W estimated by kurtosis or entropy. A correlation value is shown as the degree of similarity between the created ECG signal and the estimated new ECG signal. In the real time E-Bra system, two pseudo signals are extracted by multiplying with a random weighted vector W, the measured ECG signal from E-bra system, and the noise component signal by noise extraction algorithm from our previous work. The suggested ICA algorithm basing on kurtosis or entropy is used to estimate the new ECG signal Y without noise component.

ECG signal performance de-noising assessment based on threshold tuning of dual-tree wavelet transform.

PubMed

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.

ECG interpretation in Emergency Department residents: an update and e-learning as a resource to improve skills.

PubMed

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.

A mixed signal ECG processing platform with an adaptive sampling ADC for portable monitoring applications.

PubMed

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.

Efficacy and safety of dextrose-insulin in unmasking non-diagnostic Brugada ECG patterns.

PubMed

Velázquez-Rodríguez, Enrique; Rodríguez-Piña, Horacio; Pacheco-Bouthillier, Alex; Jiménez-Cruz, Marcelo Paz

Typical diagnostic, coved-type 1, Brugada ECG patterns fluctuate spontaneously over time with a high proportion of non-diagnostic ECG patterns. Insulin modulates ion transport mechanisms and causes hyperpolarization of the resting potential. We report our experience with unmasking J-ST changes in response to a dextrose-insulin test. Nine patients, mean age 40.5±19.4years (range: 15-65years), presented initially with a non-diagnostic ECG pattern, which was suggestive of Brugada syndrome (group I). They were compared with 10 patients with normal ECG patterns (group II). Participants received an infusion of 50g of 50% dextrose, followed by 10IU of intravenous regular insulin. Positive changes were defined by conversion to a diagnostic ECG pattern. The dextrose-insulin test was positive in six of seven (85.7%) patients (kappa 0.79, p=0.02) that was confirmed with a pharmacologic test (kappa 1, p=0.003). One had an inconclusive test, and two with a negative test had an early repolarization ECG pattern. All subjects in group II had a negative test (p<0.01). The maximum changes of the J-ST segment were observed 41.3±31.4minutes (range 3-90minutes) after dextrose-insulin infusion. One patient had monomorphic ventricular bigeminy without spontaneous or induced ventricular fibrillation. Changes in J-ST segment in the Brugada syndrome are influenced by glucose-insulin, and this report reproduces and supports the efficacy and safety of this metabolic test in the differential diagnosis of patients with non-diagnostic ECG patterns. Copyright © 2016 Elsevier Inc. All rights reserved.

[Implantable ECG recorder revealed the diagnosis in a baby with apparent life-threatening events].

PubMed

Hoorntje, T M; Langerak, W; Blokland-Loggers, H E; Sreeram, N

1999-09-25

A 14-month-old boy went through episodes of cyanosis and brief loss of consciousness. Extensive investigations failed to lead to a diagnosis, until an implanted ECG recorder revealed ECG abnormalities suggestive of strangulation. Interviews with the father and mother showed that this was indeed the case. The diagnosis of 'Münchhausen by proxy' was made. Psychiatric assistance and home help were called in. The child recovered well. If there is a suspicion of arrhythmia as the cause of apparent life-threatening events, prolonged ECG recordings are necessary. In a clinical environment it is possible to make continuous ECG recordings during a limited period. An insertable recorder allows continuous ECG recordings during a syncopal event and can be used for prolonged monitoring. The patient presented is the youngest infant in the world in whom such a device has been implanted.

Novel technical solutions for wireless ECG transmission & analysis in the age of the internet cloud.

PubMed

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.

Wavelet-based Encoding Scheme for Controlling Size of Compressed ECG Segments in Telecardiology Systems.

PubMed

Al-Busaidi, Asiya M; Khriji, Lazhar; Touati, Farid; Rasid, Mohd Fadlee; Mnaouer, Adel Ben

2017-09-12

One of the major issues in time-critical medical applications using wireless technology is the size of the payload packet, which is generally designed to be very small to improve the transmission process. Using small packets to transmit continuous ECG data is still costly. Thus, data compression is commonly used to reduce the huge amount of ECG data transmitted through telecardiology devices. In this paper, a new ECG compression scheme is introduced to ensure that the compressed ECG segments fit into the available limited payload packets, while maintaining a fixed CR to preserve the diagnostic information. The scheme automatically divides the ECG block into segments, while maintaining other compression parameters fixed. This scheme adopts discrete wavelet transform (DWT) method to decompose the ECG data, bit-field preserving (BFP) method to preserve the quality of the DWT coefficients, and a modified running-length encoding (RLE) scheme to encode the coefficients. The proposed dynamic compression scheme showed promising results with a percentage packet reduction (PR) of about 85.39% at low percentage root-mean square difference (PRD) values, less than 1%. ECG records from MIT-BIH Arrhythmia Database were used to test the proposed method. The simulation results showed promising performance that satisfies the needs of portable telecardiology systems, like the limited payload size and low power consumption.

Compressed ECG biometric: a fast, secured and efficient method for identification of CVD patient.

PubMed

Sufi, Fahim; Khalil, Ibrahim; Mahmood, Abdun

2011-12-01

Adoption of compression technology is often required for wireless cardiovascular monitoring, due to the enormous size of Electrocardiography (ECG) signal and limited bandwidth of Internet. However, compressed ECG must be decompressed before performing human identification using present research on ECG based biometric techniques. This additional step of decompression creates a significant processing delay for identification task. This becomes an obvious burden on a system, if this needs to be done for a trillion of compressed ECG per hour by the hospital. Even though the hospital might be able to come up with an expensive infrastructure to tame the exuberant processing, for small intermediate nodes in a multihop network identification preceded by decompression is confronting. In this paper, we report a technique by which a person can be identified directly from his / her compressed ECG. This technique completely obviates the step of decompression and therefore upholds biometric identification less intimidating for the smaller nodes in a multihop network. The biometric template created by this new technique is lower in size compared to the existing ECG based biometrics as well as other forms of biometrics like face, finger, retina etc. (up to 8302 times lower than face template and 9 times lower than existing ECG based biometric template). Lower size of the template substantially reduces the one-to-many matching time for biometric recognition, resulting in a faster biometric authentication mechanism.

ECG Holter monitor with alert system and mobile application

NASA Astrophysics Data System (ADS)

Teron, Abigail C.; Rivera, Pedro A.; Goenaga, Miguel A.

2016-05-01

This paper proposes a new approach on the Holter monitor by creating a portable Electrocardiogram (ECG) Holter monitor that will alert the user by detecting abnormal heart beats using a digital signal processing software. The alarm will be triggered when the patient experiences arrhythmias such as bradycardia and tachycardia. The equipment is simple, comfortable and small in size that fit in the hand. It can be used at any time and any moment by placing three leads to the person's chest which is connected to an electronic circuit. The ECG data will be transmitted via Bluetooth to the memory of a selected mobile phone using an application that will store the collected data for up to 24 hrs. The arrhythmia is identified by comparing the reference signals with the user's signal. The diagnostic results demonstrate that the ECG Holter monitor alerts the user when an arrhythmia is detected thru the Holter monitor and mobile application.

An ECG ambulatory system with mobile embedded architecture for ST-segment analysis.

PubMed

Miranda-Cid, Alejandro; Alvarado-Serrano, Carlos

2010-01-01

A prototype of a ECG ambulatory system for long term monitoring of ST segment of 3 leads, low power, portability and data storage in solid state memory cards has been developed. The solution presented is based in a mobile embedded architecture of a portable entertainment device used as a tool for storage and processing of bioelectric signals, and a mid-range RISC microcontroller, PIC 16F877, which performs the digitalization and transmission of ECG. The ECG amplifier stage is a low power, unipolar voltage and presents minimal distortion of the phase response of high pass filter in the ST segment. We developed an algorithm that manages access to files through an implementation for FAT32, and the ECG display on the device screen. The records are stored in TXT format for further processing. After the acquisition, the system implemented works as a standard USB mass storage device.

ECG feature extraction and disease diagnosis.

PubMed

Bhyri, Channappa; Hamde, S T; Waghmare, L M

2011-01-01

An important factor to consider when using findings on electrocardiograms for clinical decision making is that the waveforms are influenced by normal physiological and technical factors as well as by pathophysiological factors. In this paper, we propose a method for the feature extraction and heart disease diagnosis using wavelet transform (WT) technique and LabVIEW (Laboratory Virtual Instrument Engineering workbench). LabVIEW signal processing tools are used to denoise the signal before applying the developed algorithm for feature extraction. First, we have developed an algorithm for R-peak detection using Haar wavelet. After 4th level decomposition of the ECG signal, the detailed coefficient is squared and the standard deviation of the squared detailed coefficient is used as the threshold for detection of R-peaks. Second, we have used daubechies (db6) wavelet for the low resolution signals. After cross checking the R-peak location in 4th level, low resolution signal of daubechies wavelet P waves and T waves are detected. Other features of diagnostic importance, mainly heart rate, R-wave width, Q-wave width, T-wave amplitude and duration, ST segment and frontal plane axis are also extracted and scoring pattern is applied for the purpose of heart disease diagnosis. In this study, detection of tachycardia, bradycardia, left ventricular hypertrophy, right ventricular hypertrophy and myocardial infarction have been considered. In this work, CSE ECG data base which contains 5000 samples recorded at a sampling frequency of 500 Hz and the ECG data base created by the S.G.G.S. Institute of Engineering and Technology, Nanded (Maharashtra) have been used.

A configurable and low-power mixed signal SoC for portable ECG monitoring applications.

PubMed

Kim, Hyejung; Kim, Sunyoung; Van Helleputte, Nick; Artes, Antonio; Konijnenburg, Mario; Huisken, Jos; Van Hoof, Chris; Yazicioglu, Refet Firat

2014-04-01

This paper describes a mixed-signal ECG System-on-Chip (SoC) that is capable of implementing configurable functionality with low-power consumption for portable ECG monitoring applications. A low-voltage and high performance analog front-end extracts 3-channel ECG signals and single channel electrode-tissue-impedance (ETI) measurement with high signal quality. This can be used to evaluate the quality of the ECG measurement and to filter motion artifacts. A custom digital signal processor consisting of 4-way SIMD processor provides the configurability and advanced functionality like motion artifact removal and R peak detection. A built-in 12-bit analog-to-digital converter (ADC) is capable of adaptive sampling achieving a compression ratio of up to 7, and loop buffer integration reduces the power consumption for on-chip memory access. The SoC is implemented in 0.18 μm CMOS process and consumes 32 μ W from a 1.2 V while heart beat detection application is running, and integrated in a wireless ECG monitoring system with Bluetooth protocol. Thanks to the ECG SoC, the overall system power consumption can be reduced significantly.

Is screening for abnormal ECG patterns justified in long-term follow-up of childhood cancer survivors treated with anthracyclines?

PubMed

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.

Making sense of the ECG: cases for self-assessment Making Sense of the ECG: Cases for Self-Assessment Houghton Andrew and Gray David Hodder Education £18.99 290pp 9780340946893 034094689X [Formula: see text].

PubMed

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.

A Wearable Context-Aware ECG Monitoring System Integrated with Built-in Kinematic Sensors of the Smartphone.

PubMed

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.

An Interoperable System toward Cardiac Risk Stratification from ECG Monitoring

PubMed Central

Mora-Jiménez, Inmaculada; Ramos-López, Javier; Quintanilla Fernández, Teresa; García-García, Antonio; Díez-Mazuela, Daniel; García-Alberola, Arcadi

2018-01-01

Many indices have been proposed for cardiovascular risk stratification from electrocardiogram signal processing, still with limited use in clinical practice. We created a system integrating the clinical definition of cardiac risk subdomains from ECGs and the use of diverse signal processing techniques. Three subdomains were defined from the joint analysis of the technical and clinical viewpoints. One subdomain was devoted to demographic and clinical data. The other two subdomains were intended to obtain widely defined risk indices from ECG monitoring: a simple-domain (heart rate turbulence (HRT)), and a complex-domain (heart rate variability (HRV)). Data provided by the three subdomains allowed for the generation of alerts with different intensity and nature, as well as for the grouping and scrutinization of patients according to the established processing and risk-thresholding criteria. The implemented system was tested by connecting data from real-world in-hospital electronic health records and ECG monitoring by considering standards for syntactic (HL7 messages) and semantic interoperability (archetypes based on CEN/ISO EN13606 and SNOMED-CT). The system was able to provide risk indices and to generate alerts in the health records to support decision-making. Overall, the system allows for the agile interaction of research and clinical practice in the Holter-ECG-based cardiac risk domain. PMID:29494497

Automatic detection of respiration rate from ambulatory single-lead ECG.

PubMed

Boyle, Justin; Bidargaddi, Niranjan; Sarela, Antti; Karunanithi, Mohan

2009-11-01

Ambulatory electrocardiography is increasingly being used in clinical practice to detect abnormal electrical behavior of the heart during ordinary daily activities. The utility of this monitoring can be improved by deriving respiration, which previously has been based on overnight apnea studies where patients are stationary, or the use of multilead ECG systems for stress testing. We compared six respiratory measures derived from a single-lead portable ECG monitor with simultaneously measured respiration air flow obtained from an ambulatory nasal cannula respiratory monitor. Ten controlled 1-h recordings were performed covering activities of daily living (lying, sitting, standing, walking, jogging, running, and stair climbing) and six overnight studies. The best method was an average of a 0.2-0.8 Hz bandpass filter and RR technique based on lengthening and shortening of the RR interval. Mean error rates with the reference gold standard were +/-4 breaths per minute (bpm) (all activities), +/-2 bpm (lying and sitting), and +/-1 breath per minute (overnight studies). Statistically similar results were obtained using heart rate information alone (RR technique) compared to the best technique derived from the full ECG waveform that simplifies data collection procedures. The study shows that respiration can be derived under dynamic activities from a single-lead ECG without significant differences from traditional methods.

Anatomic distribution of culprit lesions in patients with non-ST-segment elevation myocardial infarction and normal ECG.

PubMed

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

A Digital Compressed Sensing-Based Energy-Efficient Single-Spot Bluetooth ECG Node

PubMed Central

Cai, Zhipeng; Zou, Fumin; Zhang, Xiangyu

2018-01-01

Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing- (CS-) based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic sleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power analog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the node's specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of lay, sit, stand, walk, and run. Under using sparse binary matrix (SBM), block sparse Bayesian learning (BSBL) method, and discrete cosine transform (DCT) basis, all ECG signals were essentially undistorted recovered with root-mean-square differences (PRDs) which are less than 6%. The proposed sleep/wake-up scheme and data compression can reduce the airtime over energy-hungry wireless links, the energy consumption of proposed node is 6.53 mJ, and the energy consumption of radio decreases 77.37%. Moreover, the energy consumption increase caused by CS code execution is negligible, which is 1.3% of the total energy consumption. PMID:29599945

A Digital Compressed Sensing-Based Energy-Efficient Single-Spot Bluetooth ECG Node.

PubMed

Luo, Kan; Cai, Zhipeng; Du, Keqin; Zou, Fumin; Zhang, Xiangyu; Li, Jianqing

2018-01-01

Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing- (CS-) based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic sleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power analog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the node's specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of lay, sit, stand, walk, and run. Under using sparse binary matrix (SBM), block sparse Bayesian learning (BSBL) method, and discrete cosine transform (DCT) basis, all ECG signals were essentially undistorted recovered with root-mean-square differences (PRDs) which are less than 6%. The proposed sleep/wake-up scheme and data compression can reduce the airtime over energy-hungry wireless links, the energy consumption of proposed node is 6.53 mJ, and the energy consumption of radio decreases 77.37%. Moreover, the energy consumption increase caused by CS code execution is negligible, which is 1.3% of the total energy consumption.

Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals.

PubMed

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

Biosignal integrated circuit with simultaneous acquisition of ECG and PPG for wearable healthcare applications.

PubMed

Kim, Hyungseup; Park, Yunjong; Ko, Youngwoon; Mun, Yeongjin; Lee, Sangmin; Ko, Hyoungho

2018-01-01

Wearable healthcare systems require measurements from electrocardiograms (ECGs) and photoplethysmograms (PPGs), and the blood pressure of the user. The pulse transit time (PTT) can be calculated by measuring the ECG and PPG simultaneously. Continuous-time blood pressure without using an air cuff can be estimated by using the PTT. This paper presents a biosignal acquisition integrated circuit (IC) that can simultaneously measure the ECG and PPG for wearable healthcare applications. Included in this biosignal acquisition circuit are a voltage mode instrumentation amplifier (IA) for ECG acquisition and a current mode transimpedance amplifier for PPG acquisition. The analog outputs from the ECG and PPG channels are muxed and converted to digital signals using 12-bit successive approximation register (SAR) analog-to-digital converter (ADC). The proposed IC is fabricated by using a standard 0.18 μm CMOS process with an active area of 14.44 mm2. The total current consumption for the multichannel IC is 327 μA with a 3.3 V supply. The measured input referred noise of ECG readout channel is 1.3 μVRMS with a bandwidth of 0.5 Hz to 100 Hz. And the measured input referred current noise of the PPG readout channel is 0.122 nA/√Hz with a bandwidth of 0.5 Hz to 100 Hz. The proposed IC, which is implemented using various circuit techniques, can measure ECG and PPG signals simultaneously to calculate the PTT for wearable healthcare applications.

Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment

PubMed Central

De Cooman, Thomas; Gu, Ying; Cleeren, Evy; Claes, Kasper; Van Paesschen, Wim; Van Huffel, Sabine; Hunyadi, Borbála

2017-01-01

Electrocardiography has added value to automatically detect seizures in temporal lobe epilepsy (TLE) patients. The wired hospital system is not suited for a long-term seizure detection system at home. To address this need, the performance of two wearable devices, based on electrocardiography (ECG) and photoplethysmography (PPG), are compared with hospital ECG using an existing seizure detection algorithm. This algorithm classifies the seizures on the basis of heart rate features, extracted from the heart rate increase. The algorithm was applied to recordings of 11 patients in a hospital setting with 701 h capturing 47 (fronto-)temporal lobe seizures. The sensitivities of the hospital system, the wearable ECG device and the wearable PPG device were respectively 57%, 70% and 32%, with corresponding false alarms per hour of 1.92, 2.11 and 1.80. Whereas seizure detection performance using the wrist-worn PPG device was considerably lower, the performance using the wearable ECG is proven to be similar to that of the hospital ECG. PMID:29027928

Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment.

PubMed

Vandecasteele, Kaat; De Cooman, Thomas; Gu, Ying; Cleeren, Evy; Claes, Kasper; Paesschen, Wim Van; Huffel, Sabine Van; Hunyadi, Borbála

2017-10-13

Electrocardiography has added value to automatically detect seizures in temporal lobe epilepsy (TLE) patients. The wired hospital system is not suited for a long-term seizure detection system at home. To address this need, the performance of two wearable devices, based on electrocardiography (ECG) and photoplethysmography (PPG), are compared with hospital ECG using an existing seizure detection algorithm. This algorithm classifies the seizures on the basis of heart rate features, extracted from the heart rate increase. The algorithm was applied to recordings of 11 patients in a hospital setting with 701 h capturing 47 (fronto-)temporal lobe seizures. The sensitivities of the hospital system, the wearable ECG device and the wearable PPG device were respectively 57%, 70% and 32%, with corresponding false alarms per hour of 1.92, 2.11 and 1.80. Whereas seizure detection performance using the wrist-worn PPG device was considerably lower, the performance using the wearable ECG is proven to be similar to that of the hospital ECG.

Deployment of an Advanced Electrocardiographic Analysis (A-ECG) to Detect Cardiovascular Risk in Career Firefighters

NASA Technical Reports Server (NTRS)

Dolezal, B. A.; Storer, T. W.; Abrazado, M.; Watne, R.; Schlegel, T. T.; Batalin, M.; Kaiser, W.; Smith, D. L.; Cooper, C. B.

2011-01-01

INTRODUCTION: Sudden cardiac death is the leading cause of line of duty death among firefighters, accounting for approximately 45% of fatalities annually. Firefighters perform strenuous muscular work while wearing heavy, encapsulating personal protective equipment in high ambient temperatures, under chaotic and emotionally stressful conditions. These factors can precipitate sudden cardiac events like myocardial infarction, serious dysrhythmias, or cerebrovascular accidents in firefighters with underlying cardiovascular disease. PURPOSE: The purpose of this study was to deploy and then evaluate the contribution of resting advanced ECG (A-ECG) in addition to other screening tools (family history, lipid profiles, and cardiopulmonary exercise tests, XT) in assessment of an individual fs cardiac risk profile. METHODS: Forty-four career firefighters were recruited to perform comprehensive baseline assessments including tests of aerobic performance, fasting lipids and glucose. Five-min resting 12-lead A-ECGs were obtained in a subset of firefighters (n=21) and transmitted over a secure networked system to a NASA physician collaborator. Using myocardial perfusion and other imaging as the gold standard, A-ECG scoring has been proven useful in accurately identifying a number of cardiac pathologies including coronary artery disease (CAD), left ventricular hypertrophy, hypertrophic cardiomyopathy, and non-ischemic and ischemic cardiomyopathy. RESULTS: Subjects f mean (SD) age was 43 (8) years, weight 91 (13) kg, and BMI 28 (3) kg/m2. Fifty-one percent of subjects had .3 cardiovascular risk factors. One subject had ST depression on XT ECG, at least one positive A-ECG score for CAD, and documented CAD based on cardiology referral. While all other subjects, including those with fewer risk factors, higher aerobic fitness, and normal exercise ECGs, were classified as healthy by A-ECG, there was no trend for association between risk factors and any of 20 A-ECG parameters in the

Optimisation algorithms for ECG data compression.

PubMed

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.

QRS classification and spatial combination for robust heart rate detection in low-quality fetal ECG recordings.

PubMed

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.

Wireless remote monitoring of myocardial ischemia using reconstructed 12-lead ECGs.

PubMed

Vukcevic, Vladan; Panescu, Dorin; Bojovic, Bosko; George, Samuel; Gussak, Ihor; Giga, Vojislav; Stankovic, Ivana

2010-01-01

CardioBip (CB) is a hand-held patient-activated device for recording and wireless transmission of reconstructed 12-lead ECG (12CB) based on patient specific matrices. It has 5 contact points: 3 precordial and 2 on the device top serving as limb leads when touched by index fingers. To determine whether CB could be used to monitor coronary disease (CAD) patients, we compared 12CB to simultaneous 12-lead ECGs (12L) in patients with CAD, pre-and post-exercise treadmill testing (ETT). The study goals were to assess: (1) whether 12CB can accurately reconstruct and wirelessly transmit 12-lead ECGs in CAD patients during ETT recovery; (2) whether 12CB can be used to evaluate ST segment changes in patients with exercise-induced ischemia.

ECG Wave-Maven: An Internet-based Electrocardiography Self-Assessment Program for Students and Clinicians.

PubMed

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.

Non-ECG-gated unenhanced MRA of the carotids: optimization and clinical feasibility.

PubMed

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.

Genetic algorithm for the optimization of features and neural networks in ECG signals classification

NASA Astrophysics Data System (ADS)

Li, Hongqiang; Yuan, Danyang; Ma, Xiangdong; Cui, Dianyin; Cao, Lu

2017-01-01

Feature extraction and classification of electrocardiogram (ECG) signals are necessary for the automatic diagnosis of cardiac diseases. In this study, a novel method based on genetic algorithm-back propagation neural network (GA-BPNN) for classifying ECG signals with feature extraction using wavelet packet decomposition (WPD) is proposed. WPD combined with the statistical method is utilized to extract the effective features of ECG signals. The statistical features of the wavelet packet coefficients are calculated as the feature sets. GA is employed to decrease the dimensions of the feature sets and to optimize the weights and biases of the back propagation neural network (BPNN). Thereafter, the optimized BPNN classifier is applied to classify six types of ECG signals. In addition, an experimental platform is constructed for ECG signal acquisition to supply the ECG data for verifying the effectiveness of the proposed method. The GA-BPNN method with the MIT-BIH arrhythmia database achieved a dimension reduction of nearly 50% and produced good classification results with an accuracy of 97.78%. The experimental results based on the established acquisition platform indicated that the GA-BPNN method achieved a high classification accuracy of 99.33% and could be efficiently applied in the automatic identification of cardiac arrhythmias.

An integrated healthcare information system for end-to-end standardized exchange and homogeneous management of digital ECG formats.

PubMed

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.

Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems.

PubMed

Elgendi, Mohamed; Eskofier, Björn; Dokos, Socrates; Abbott, Derek

2014-01-01

Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices.

Revisiting QRS Detection Methodologies for Portable, Wearable, Battery-Operated, and Wireless ECG Systems

PubMed Central

Elgendi, Mohamed; Eskofier, Björn; Dokos, Socrates; Abbott, Derek

2014-01-01

Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices. PMID:24409290

Community-Based ECG Monitoring System for Patients with Cardiovascular Diseases.

PubMed

Lin, Bor-Shyh; Wong, Alice M; Tseng, Kevin C

2016-04-01

This study aims to develop a community-based electrocardiogram (ECG) monitoring system for cardiac outpatients to wirelessly detect heart rate, provide personalized healthcare, and enhance interactive social contact because of the prevalence of deaths from cardiovascular disease and the growing problem of aging in the world. The system not only strengthens the performance of the ECG monitoring system but also emphasizes the ergonomic design of wearable devices and user interfaces. In addition, it enables medical professionals to diagnose cardiac symptoms remotely and electronically manage medical reports and suggestions. The experimental result shows high performance of the dry electrode, even in dynamic conditions. The comparison result with different ECG healthcare systems shows the essential factors that the system should possess and the capability of the proposed system. Finally, a user survey was conducted based on the unified theory of acceptance and users of technology (UTAUT) model.

Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring.

PubMed

Everss-Villalba, Estrella; Melgarejo-Meseguer, Francisco Manuel; Blanco-Velasco, Manuel; Gimeno-Blanes, Francisco Javier; Sala-Pla, Salvador; Rojo-Álvarez, José Luis; García-Alberola, Arcadi

2017-10-25

Noise and artifacts are inherent contaminating components and are particularly present in Holter electrocardiogram (ECG) monitoring. The presence of noise is even more significant in long-term monitoring (LTM) recordings, as these are collected for several days in patients following their daily activities; hence, strong artifact components can temporarily impair the clinical measurements from the LTM recordings. Traditionally, the noise presence has been dealt with as a problem of non-desirable component removal by means of several quantitative signal metrics such as the signal-to-noise ratio (SNR), but current systems do not provide any information about the true impact of noise on the ECG clinical evaluation. As a first step towards an alternative to classical approaches, this work assesses the ECG quality under the assumption that an ECG has good quality when it is clinically interpretable. Therefore, our hypotheses are that it is possible (a) to create a clinical severity score for the effect of the noise on the ECG, (b) to characterize its consistency in terms of its temporal and statistical distribution, and (c) to use it for signal quality evaluation in LTM scenarios. For this purpose, a database of external event recorder (EER) signals is assembled and labeled from a clinical point of view for its use as the gold standard of noise severity categorization. These devices are assumed to capture those signal segments more prone to be corrupted with noise during long-term periods. Then, the ECG noise is characterized through the comparison of these clinical severity criteria with conventional quantitative metrics taken from traditional noise-removal approaches, and noise maps are proposed as a novel representation tool to achieve this comparison. Our results showed that neither of the benchmarked quantitative noise measurement criteria represent an accurate enough estimation of the clinical severity of the noise. A case study of long-term ECG is reported

Application of computerized exercise ECG digitization. Interpretation in large clinical trials.

PubMed

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.

Interactive Videoconference Supported Teaching in Undergraduate Nursing: A Case Study for ECG

ERIC Educational Resources Information Center

Celikkan, Ufuk; Senuzun, Fisun; Sari, Dilek; Sahin, Yasar Guneri

2013-01-01

This paper describes how interactive videoconference can benefit the Electrocardiography (ECG) skills of undergraduate nursing students. We have implemented a learning system that interactively transfers the visual and practical aspects of ECG from a nursing skills lab into a classroom where the theoretical part of the course is taught. The…

[Design and Implementation of Intelligent Mobile ECG].

PubMed

Cao, Shaoping; Liu, Jian

2016-05-01

This paper introduces the development of intelligent mobile ECG, and internet big data sharing resources to further improve the remote diagnosis of medical service platform , to enhance the level of mobile medical standard and control medical risks.

ECG signal quality during arrhythmia and its application to false alarm reduction.

PubMed

Behar, Joachim; Oster, Julien; Li, Qiao; Clifford, Gari D

2013-06-01

An automated algorithm to assess electrocardiogram (ECG) quality for both normal and abnormal rhythms is presented for false arrhythmia alarm suppression of intensive care unit (ICU) monitors. A particular focus is given to the quality assessment of a wide variety of arrhythmias. Data from three databases were used: the Physionet Challenge 2011 dataset, the MIT-BIH arrhythmia database, and the MIMIC II database. The quality of more than 33 000 single-lead 10 s ECG segments were manually assessed and another 12 000 bad-quality single-lead ECG segments were generated using the Physionet noise stress test database. Signal quality indices (SQIs) were derived from the ECGs segments and used as the inputs to a support vector machine classifier with a Gaussian kernel. This classifier was trained to estimate the quality of an ECG segment. Classification accuracies of up to 99% on the training and test set were obtained for normal sinus rhythm and up to 95% for arrhythmias, although performance varied greatly depending on the type of rhythm. Additionally, the association between 4050 ICU alarms from the MIMIC II database and the signal quality, as evaluated by the classifier, was studied. Results suggest that the SQIs should be rhythm specific and that the classifier should be trained for each rhythm call independently. This would require a substantially increased set of labeled data in order to train an accurate algorithm.

A novel application of deep learning for single-lead ECG classification.

PubMed

Mathews, Sherin M; Kambhamettu, Chandra; Barner, Kenneth E

2018-06-04

Detecting and classifying cardiac arrhythmias is critical to the diagnosis of patients with cardiac abnormalities. In this paper, a novel approach based on deep learning methodology is proposed for the classification of single-lead electrocardiogram (ECG) signals. We demonstrate the application of the Restricted Boltzmann Machine (RBM) and deep belief networks (DBN) for ECG classification following detection of ventricular and supraventricular heartbeats using single-lead ECG. The effectiveness of this proposed algorithm is illustrated using real ECG signals from the widely-used MIT-BIH database. Simulation results demonstrate that with a suitable choice of parameters, RBM and DBN can achieve high average recognition accuracies of ventricular ectopic beats (93.63%) and of supraventricular ectopic beats (95.57%) at a low sampling rate of 114 Hz. Experimental results indicate that classifiers built into this deep learning-based framework achieved state-of-the art performance models at lower sampling rates and simple features when compared to traditional methods. Further, employing features extracted at a sampling rate of 114 Hz when combined with deep learning provided enough discriminatory power for the classification task. This performance is comparable to that of traditional methods and uses a much lower sampling rate and simpler features. Thus, our proposed deep neural network algorithm demonstrates that deep learning-based methods offer accurate ECG classification and could potentially be extended to other physiological signal classifications, such as those in arterial blood pressure (ABP), nerve conduction (EMG), and heart rate variability (HRV) studies. Copyright © 2018. Published by Elsevier Ltd.

Deployment of an Advanced Electrocardiographic Analysis (A-ECG) to Detect Cardiovascular Risk in Career Firefighters

NASA Technical Reports Server (NTRS)

Dolezal, B. A.; Storer, T. W.; Abrazado, M.; Watne, R.; Schlegel, T. T.; Batalin, M.; Kaiser, W.; Smith, D. L.; Cooper, C. B.

2011-01-01

INTRODUCTION Sudden cardiac death is the leading cause of line of duty death among firefighters, accounting for approximately 45% of fatalities annually. Firefighters perform strenuous muscular work while wearing heavy, encapsulating personal protective equipment in high ambient temperatures, under chaotic and emotionally stressful conditions. These factors can precipitate sudden cardiac events like myocardial infarction, serious dysrhythmias, or cerebrovascular accidents in firefighters with underlying cardiovascular disease. Screening for cardiovascular risk factors is recommended but not always followed in this population. PHASER is a project charged with identifying and prioritizing risk factors in emergency responders. We have deployed an advanced ECG (A-ECG) system developed at NASA for improved sensitivity and specificity in the detection of cardiac risk. METHODS Forty-four professional firefighters were recruited to perform comprehensive baseline assessments including tests of aerobic performance and laboratory tests for fasting lipid profiles and glucose. Heart rate and conventional 12-lead ECG were obtained at rest and during incremental treadmill exercise testing (XT). In addition, a 5-min resting 12-lead A-ECG was obtained in a subset of firefighters (n=18) and transmitted over a secure networked system to a physician collaborator at NASA for advanced-ECG analysis. This A-ECG system has been proven, using myocardial perfusion and other imaging, to accurately identify a number of cardiac pathologies including coronary artery disease (CAD), left ventricular hypertrophy, hypertrophic cardiomyopathy, non-ischemic cardiomyopathy, and ischemic cardiomyopathy. RESULTS Subjects mean (SD) age was 43 (8) years, weight 91 (13) kg, and BMI of 28 (3) kg/square meter. Maximum oxygen uptake (VO2max) was 39 (9) ml/kg/min. This compares with the 45th %ile in healthy reference values and a recommended standard of 42 ml/kg/min for firefighters. The metabolic threshold (VO

Pre-participation examination of competitive athletes: role of the ECG.

PubMed

Hirzinger, Corinna; Froelicher, Victor F; Niebauer, Josef

2010-08-01

Sudden cardiac death in athletes is rare but has a wide social impact because it confronts the general population with the paradox that athletes perceived and admired as the fittest and healthiest suddenly drop dead during their sport. Mass media coverage is guaranteed in the case of sudden cardiac death of a top athlete, while other competitive and noncompetitive athletes of all ages, team members, sponsors, as well as huge parts of society remain puzzled and frightened. Therefore, debate is ongoing regarding how to minimize the number of fatalities, and the search continues for a cost-effective preparticipation screening for competitive athletes. Despite the fact that routine ECG screening would be widely available and rather inexpensive, debate continues regarding whether this should be part of initial screening for every athlete before starting to train at high intensity as well as during annual checkups. The role of ECGs in preparticipation examinations of competitive athletes is intensively discussed because there is a lack of strict criteria for which ECG findings should generate further workup. In this article, we analyze the main publications on sudden cardiac death, focusing on the benefit of ECG screening in preparticipation examination as it has been shown to be feasible and effective in identifying athletes at risk of sudden cardiac death. Copyright © 2010 Elsevier Inc. All rights reserved.

Patient-Specific Deep Architectural Model for ECG Classification

PubMed Central

Luo, Kan; Cuschieri, Alfred

2017-01-01

Heartbeat classification is a crucial step for arrhythmia diagnosis during electrocardiographic (ECG) analysis. The new scenario of wireless body sensor network- (WBSN-) enabled ECG monitoring puts forward a higher-level demand for this traditional ECG analysis task. Previously reported methods mainly addressed this requirement with the applications of a shallow structured classifier and expert-designed features. In this study, modified frequency slice wavelet transform (MFSWT) was firstly employed to produce the time-frequency image for heartbeat signal. Then the deep learning (DL) method was performed for the heartbeat classification. Here, we proposed a novel model incorporating automatic feature abstraction and a deep neural network (DNN) classifier. Features were automatically abstracted by the stacked denoising auto-encoder (SDA) from the transferred time-frequency image. DNN classifier was constructed by an encoder layer of SDA and a softmax layer. In addition, a deterministic patient-specific heartbeat classifier was achieved by fine-tuning on heartbeat samples, which included a small subset of individual samples. The performance of the proposed model was evaluated on the MIT-BIH arrhythmia database. Results showed that an overall accuracy of 97.5% was achieved using the proposed model, confirming that the proposed DNN model is a powerful tool for heartbeat pattern recognition. PMID:29065597

Systematic analysis of ECG predictors of sinus rhythm maintenance after electrical cardioversion for persistent atrial fibrillation.

PubMed

Lankveld, Theo; de Vos, Cees B; Limantoro, Ione; Zeemering, Stef; Dudink, Elton; Crijns, Harry J; Schotten, Ulrich

2016-05-01

Electrical cardioversion (ECV) is one of the rhythm control strategies in patients with persistent atrial fibrillation (AF). Unfortunately, recurrences of AF are common after ECV, which significantly limits the practical benefit of this treatment in patients with AF. The objectives of this study were to identify noninvasive complexity or frequency parameters obtained from the surface electrocardiogram (ECG) to predict sinus rhythm (SR) maintenance after ECV and to compare these ECG parameters with clinical predictors. We studied a wide variety of ECG-derived time- and frequency-domain AF complexity parameters in a prospective cohort of 502 patients with persistent AF referred for ECV. During 1-year follow-up, 161 patients (32%) maintained SR. The best clinical predictor of SR maintenance was antiarrhythmic drug (AAD) treatment. A model including clinical parameters predicted SR maintenance with a mean cross-validated area under the receiver operating characteristic curve (AUC) of 0.62 ± 0.05. The best single ECG parameter was the dominant frequency (DF) on lead V6. Combining several ECG parameters predicted SR maintenance with a mean AUC of 0.64 ± 0.06. Combining clinical and ECG parameters improved prediction to a mean AUC of 0.67 ± 0.05. Although the DF was affected by AAD treatment, excluding patients taking AADs did not significantly lower the predictive performance captured by the ECG. ECG-derived parameters predict SR maintenance during 1-year follow-up after ECV at least as good as known clinical predictors of rhythm outcome. The DF proved to be the most powerful ECG-derived predictor. Copyright © 2016 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

A sub-nJ CMOS ECG classifier for wireless smart sensor.

PubMed

Chollet, Paul; Pallas, Remi; Lahuec, Cyril; Arzel, Matthieu; Seguin, Fabrice

2017-07-01

Body area sensor networks hold the promise of more efficient and cheaper medical care services through the constant monitoring of physiological markers such as heart beats. Continuously transmitting the electrocardiogram (ECG) signal requires most of the wireless ECG sensor energy budget. This paper presents the analog implantation of a classifier for ECG signals that can be embedded onto a sensor. The classifier is a sparse neural associative memory. It is implemented using the ST 65 nm CMOS technology and requires only 234 pJ per classification while achieving a 93.6% classification accuracy. The energy requirement is 6 orders of magnitude lower than a digital accelerator that performs a similar task. The lifespan of the resulting sensor is 191 times as large as that of a sensor sending all the data.

Derivation of respiration rate from ambulatory ECG and PPG using Ensemble Empirical Mode Decomposition: Comparison and fusion.

PubMed

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.

Check your biosignals here: a new dataset for off-the-person ECG biometrics.

PubMed

da Silva, Hugo Plácido; Lourenço, André; Fred, Ana; Raposo, Nuno; Aires-de-Sousa, Marta

2014-02-01

The Check Your Biosignals Here initiative (CYBHi) was developed as a way of creating a dataset and consistently repeatable acquisition framework, to further extend research in electrocardiographic (ECG) biometrics. In particular, our work targets the novel trend towards off-the-person data acquisition, which opens a broad new set of challenges and opportunities both for research and industry. While datasets with ECG signals collected using medical grade equipment at the chest can be easily found, for off-the-person ECG data the solution is generally for each team to collect their own corpus at considerable expense of resources. In this paper we describe the context, experimental considerations, methods, and preliminary findings of two public datasets created by our team, one for short-term and another for long-term assessment, with ECG data collected at the hand palms and fingers. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Segmentation of ECG from Surface EMG Using DWT and EMD: A Comparison Study

NASA Astrophysics Data System (ADS)

Shahbakhti, Mohammad; Heydari, Elnaz; Luu, Gia Thien

2014-10-01

The electrocardiographic (ECG) signal is a major artifact during recording the surface electromyography (SEMG). Removal of this artifact is one of the important tasks before SEMG analysis for biomedical goals. In this paper, the application of discrete wavelet transform (DWT) and empirical mode decomposition (EMD) for elimination of ECG artifact from SEMG is investigated. The focus of this research is to reach the optimized number of decomposed levels using mean power frequency (MPF) by both techniques. In order to implement the proposed methods, ten simulated and three real ECG contaminated SEMG signals have been tested. Signal-to-noise ratio (SNR) and mean square error (MSE) between the filtered and the pure signals are applied as the performance indexes of this research. The obtained results suggest both techniques could remove ECG artifact from SEMG signals fair enough, however, DWT performs much better and faster in real data.

Multiadaptive Bionic Wavelet Transform: Application to ECG Denoising and Baseline Wandering Reduction

NASA Astrophysics Data System (ADS)

Sayadi, Omid; Shamsollahi, Mohammad B.

2007-12-01

We present a new modified wavelet transform, called the multiadaptive bionic wavelet transform (MABWT), that can be applied to ECG signals in order to remove noise from them under a wide range of variations for noise. By using the definition of bionic wavelet transform and adaptively determining both the center frequency of each scale together with the[InlineEquation not available: see fulltext.]-function, the problem of desired signal decomposition is solved. Applying a new proposed thresholding rule works successfully in denoising the ECG. Moreover by using the multiadaptation scheme, lowpass noisy interference effects on the baseline of ECG will be removed as a direct task. The method was extensively clinically tested with real and simulated ECG signals which showed high performance of noise reduction, comparable to those of wavelet transform (WT). Quantitative evaluation of the proposed algorithm shows that the average SNR improvement of MABWT is 1.82 dB more than the WT-based results, for the best case. Also the procedure has largely proved advantageous over wavelet-based methods for baseline wandering cancellation, including both DC components and baseline drifts.

Fusion of ECG and ABP signals based on wavelet transform for cardiac arrhythmias classification.

PubMed

Arvanaghi, Roghayyeh; Daneshvar, Sabalan; Seyedarabi, Hadi; Goshvarpour, Atefeh

2017-11-01

Each of Electrocardiogram (ECG) and Atrial Blood Pressure (ABP) signals contain information of cardiac status. This information can be used for diagnosis and monitoring of diseases. The majority of previously proposed methods rely only on ECG signal to classify heart rhythms. In this paper, ECG and ABP were used to classify five different types of heart rhythms. To this end, two mentioned signals (ECG and ABP) have been fused. These physiological signals have been used from MINIC physioNet database. ECG and ABP signals have been fused together on the basis of the proposed Discrete Wavelet Transformation fusion technique. Then, some frequency features were extracted from the fused signal. To classify the different types of cardiac arrhythmias, these features were given to a multi-layer perceptron neural network. In this study, the best results for the proposed fusion algorithm were obtained. In this case, the accuracy rates of 96.6%, 96.9%, 95.6% and 93.9% were achieved for two, three, four and five classes, respectively. However, the maximum classification rate of 89% was obtained for two classes on the basis of ECG features. It has been found that the higher accuracy rates were acquired by using the proposed fusion technique. The results confirmed the importance of fusing features from different physiological signals to gain more accurate assessments. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis Spectrum of ECG Signal and QRS Detection during Running on Treadmill

NASA Astrophysics Data System (ADS)

Agung Suhendra, M.; Ilham R., M.; Simbolon, Artha I.; Faizal A., M.; Munandar, A.

2018-03-01

The heart is an important organ in our metabolism in which it controls circulatory and oxygen. The heart exercise is needed one of them using the treadmill to prevent health. To analysis, it using electrocardiograph (ECG) to investigating and diagnosing anomalies of the heart. In this paper, we would like to analysis ECG signals during running on the treadmill with kinds of speeds. There are two analysis ECG signals i.e. QRS detection and power spectrum density (PSD). The result of PSD showed that subject 3 has highly for all subject and the result of QRS detection using pan Tomkins algorithm that a percentage of failed detection is an approaching to 0 % for all subject.

ECG Denoising Using Marginalized Particle Extended Kalman Filter With an Automatic Particle Weighting Strategy.

PubMed

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

A new statistical PCA-ICA algorithm for location of R-peaks in ECG.

PubMed

Chawla, M P S; Verma, H K; Kumar, Vinod

2008-09-16

The success of ICA to separate the independent components from the mixture depends on the properties of the electrocardiogram (ECG) recordings. This paper discusses some of the conditions of independent component analysis (ICA) that could affect the reliability of the separation and evaluation of issues related to the properties of the signals and number of sources. Principal component analysis (PCA) scatter plots are plotted to indicate the diagnostic features in the presence and absence of base-line wander in interpreting the ECG signals. In this analysis, a newly developed statistical algorithm by authors, based on the use of combined PCA-ICA for two correlated channels of 12-channel ECG data is proposed. ICA technique has been successfully implemented in identifying and removal of noise and artifacts from ECG signals. Cleaned ECG signals are obtained using statistical measures like kurtosis and variance of variance after ICA processing. This analysis also paper deals with the detection of QRS complexes in electrocardiograms using combined PCA-ICA algorithm. The efficacy of the combined PCA-ICA algorithm lies in the fact that the location of the R-peaks is bounded from above and below by the location of the cross-over points, hence none of the peaks are ignored or missed.

E-Bra system for women ECG measurement with GPRS communication, Nanosensor, and motion artifact remove algorithm

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

Skin-electrode impedance measurement during ECG acquisition: method’s validation

NASA Astrophysics Data System (ADS)

Casal, Leonardo; La Mura, Guillermo

2016-04-01

Skm-electrode impedance measurement can provide valuable information prior. dunng and post electrocardiographic (ECG) or electroencephalographs (EEG) acquisitions. In this work we validate a method for skm-electrode impedance measurement using test circuits with known resistance and capacitor values, at different frequencies for injected excitation current. Finally the method is successfully used for impedance measurement during ECG acquisition on a subject usmg 125 Hz and 6 nA square wave excitation signal at instrumentation amplifier mput. The method can be used for many electrodes configuration.

3D Finite Element Electrical Model of Larval Zebrafish ECG Signals

PubMed Central

Crowcombe, James; Dhillon, Sundeep Singh; Hurst, Rhiannon Mary; Egginton, Stuart; Müller, Ferenc; Sík, Attila; Tarte, Edward

2016-01-01

Assessment of heart function in zebrafish larvae using electrocardiography (ECG) is a potentially useful tool in developing cardiac treatments and the assessment of drug therapies. In order to better understand how a measured ECG waveform is related to the structure of the heart, its position within the larva and the position of the electrodes, a 3D model of a 3 days post fertilisation (dpf) larval zebrafish was developed to simulate cardiac electrical activity and investigate the voltage distribution throughout the body. The geometry consisted of two main components; the zebrafish body was modelled as a homogeneous volume, while the heart was split into five distinct regions (sinoatrial region, atrial wall, atrioventricular band, ventricular wall and heart chambers). Similarly, the electrical model consisted of two parts with the body described by Laplace’s equation and the heart using a bidomain ionic model based upon the Fitzhugh-Nagumo equations. Each region of the heart was differentiated by action potential (AP) parameters and activation wave conduction velocities, which were fitted and scaled based on previously published experimental results. ECG measurements in vivo at different electrode recording positions were then compared to the model results. The model was able to simulate action potentials, wave propagation and all the major features (P wave, R wave, T wave) of the ECG, as well as polarity of the peaks observed at each position. This model was based upon our current understanding of the structure of the normal zebrafish larval heart. Further development would enable us to incorporate features associated with the diseased heart and hence assist in the interpretation of larval zebrafish ECGs in these conditions. PMID:27824910

Wearable technology and ECG processing for fall risk assessment, prevention and detection.

PubMed

Melillo, Paolo; Castaldo, Rossana; Sannino, Giovanna; Orrico, Ada; de Pietro, Giuseppe; Pecchia, Leandro

2015-01-01

Falls represent one of the most common causes of injury-related morbidity and mortality in later life. Subjects with cardiovascular disorders (e.g., related to autonomic dysfunctions and postural hypotension) are at higher risk of falling. Autonomic dysfunctions increasing the risk of falling in the short and mid-term could be assessed by Heart Rate Variability (HRV) extracted by electrocardiograph (ECG). We developed three trials for assessing the usefulness of ECG monitoring using wearable devices for: risk assessment of falling in the next few weeks; prevention of imminent falls due to standing hypotension; and fall detection. Statistical and data-mining methods are adopted to develop classification and regression models, validated with the cross-validation approach. The first classifier based on HRV features enabled to identify future fallers among hypertensive patients with an accuracy of 72% (sensitivity: 51.1%, specificity: 80.2%). The regression model to predict falls due to orthostatic dropdown from HRV recorded before standing achieved an overall accuracy of 80% (sensitivity: 92%, specificity: 90%). Finally, the classifier to detect simulated falls using ECG achieved an accuracy of 77.3% (sensitivity: 81.8%, specificity: 72.7%). The evidence from these three studies showed that ECG monitoring and processing could achieve satisfactory performances compared to other system for risk assessment, fall prevention and detection. This is interesting as differently from other technologies actually employed to prevent falls, ECG is recommended for many other pathologies of later life and is more accepted by senior citizens.

A wavelet-based ECG delineation algorithm for 32-bit integer online processing.

PubMed

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.

A reconfigurable, wearable, wireless ECG system.

PubMed

Borromeo, S; Rodriguez-Sanchez, C; Machado, F; Hernandez-Tamames, J A; de la Prieta, R

2007-01-01

New emerging concepts as "wireless hospital", "mobile healthcare" or "wearable telemonitoring" require the development of bio-signal acquisition devices to be easily integrated into the clinical routine. In this work, we present a new system for Electrocardiogram (ECG) acquisition and its processing, with wireless transmission on demand (either the complete ECG or only one alarm message, just in case a pathological heart rate detected). Size and power consumption are optimized in order to provide mobility and comfort to the patient. We have designed a modular hardware system and an autonomous platform based on a Field-Programmable Gate Array (FPGA) for developing and debugging. The modular approach allows to redesign the system in an easy way. Its adaptation to a new biomedical signal would only need small changes on it. The hardware system is composed of three layers that can be plugged/unplugged: communication layer, processing layer and sensor layer. In addition, we also present a general purpose end-user application developed for mobile phones or Personal Digital Assistant devices (PDAs).

ECG and morphologic adaptations in Arabic athletes: are the European Society of Cardiology's recommendations for the interpretation of the 12-lead ECG appropriate for this ethnicity?

PubMed

Riding, Nathan R; Salah, Othman; Sharma, Sanjay; Carré, François; George, Keith P; Farooq, Abdulaziz; Hamilton, Bruce; Chalabi, Hakim; Whyte, Gregory P; Wilson, Mathew G

2014-08-01

To examine the cardiac structure and function of Arabic athletes and to establish if the European Society of Cardiology (ESC) guidelines for the interpretation of an athlete's ECG are applicable to this ethnicity. 600 high-level Arabic, 415 Black African, 160 Caucasian male athletes (exercising ≥6 h/week) and 201 Arabic controls presented for ECG and echocardiographic screening. 9 athletes (0.7%) were identified with a cardiac pathology associated with sudden cardiac death. Two Arabics (0.3%) and five Black Africans (1.2%) were diagnosed with hypertrophic cardiomyopathy; a prevalence four times greater in Black African compared to Arabic athletes. Arabic athletes had significantly greater (p<0.05) left ventricular (LV) end-diastolic diameters, maximal LV wall thicknesses and LV mass compared with controls; yet were significantly smaller than Black African and Caucasian athletes. The percentage of athletes demonstrating LV hypertrophy (≥12 mm) was comparable between Arabic, Black African and Caucasian populations (0.5%, 0.5% and 0.6%, respectively). There was no difference in the frequency of an uncommon and training-unrelated ECG between Arabic and Caucasian. However, Black Africans demonstrated a significantly greater prevalence than Arabic and Caucasian athletes (20% vs 8.4% and 6.9%, p<0.001); specifically more right/left atrial enlargement and T wave inversion. Arabic athletes present significantly smaller cardiac dimensions than Black African and Caucasian athletes. There was no significant difference between the frequency of an uncommon and training-unrelated ECG between Arabic and Caucasian athletes. Therefore, the use of ESC guidelines for the interpretation of an athlete's ECG is clinically relevant and acceptable for use within Arabic athletes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Single frequency RF powered ECG telemetry system

NASA Technical Reports Server (NTRS)

Ko, W. H.; Hynecek, J.; Homa, J.

1979-01-01

It has been demonstrated that a radio frequency magnetic field can be used to power implanted electronic circuitry for short range telemetry to replace batteries. A substantial reduction in implanted volume can be achieved by using only one RF tank circuit for receiving the RF power and transmitting the telemetered information. A single channel telemetry system of this type, using time sharing techniques, was developed and employed to transmit the ECG signal from Rhesus monkeys in primate chairs. The signal from the implant is received during the period when the RF powering radiation is interrupted. The ECG signal is carried by 20-microsec pulse position modulated pulses, referred to the trailing edge of the RF powering pulse. Satisfactory results have been obtained with this single frequency system. The concept and the design presented may be useful for short-range long-term implant telemetry systems.

Spatial enhancement of ECG using diagnostic similarity score based lead selective multi-scale linear model.

PubMed

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.

Prolonged corrected QT interval is predictive of future stroke events even in subjects without ECG-diagnosed left ventricular hypertrophy.

PubMed

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.

Adaptive spatio-temporal filtering of disturbed ECGs: a multi-channel approach to heartbeat detection in smart clothing.

PubMed

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.

An Investigation on the Effect of Extremely Low Frequency Pulsed Electromagnetic Fields on Human Electrocardiograms (ECGs).

PubMed

Fang, Qiang; Mahmoud, Seedahmed S; Yan, Jiayong; Li, Hui

2016-11-23

For this investigation, we studied the effects of extremely low frequency pulse electromagnetic fields (ELF-PEMF) on the human cardiac signal. Electrocardiograms (ECGs) of 22 healthy volunteers before and after a short duration of ELF-PEMF exposure were recorded. The experiment was conducted under single-blind conditions. The root mean square (RMS) value of the recorded data was considered as comparison criteria. We also measured and analysed four important ECG time intervals before and after ELF-PEMF exposure. Results revealed that the RMS value of the ECG recordings from 18 participants (81.8% of the total participants) increased with a mean value of 3.72%. The increase in ECG voltage levels was then verified by a second experimental protocol with a control exposure. In addition to this, we used hyperbolic T-distributions (HTD) in the analysis of ECG signals to verify the change in the RR interval. It was found that there were small shifts in the frequency-domain signal before and after EMF exposure. This shift has an influence on all frequency components of the ECG signals, as all spectrums were shifted. It is shown from this investigation that a short time exposure to ELF-PEMF can affect the properties of ECG signals. Further study is needed to consolidate this finding and discover more on the biological effects of ELF-PEMF on human physiological processes.

[Monitor of ECG signal and heart rate using a mobile phone with Bluetooth communication protocol].

PubMed

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.

A Differential ECG Amplifier with Single-Ended Output

NASA Technical Reports Server (NTRS)

Katchis, L.

1972-01-01

Three-stage amplifier is used for ECG measurements which require conversion of differential input to single-ended output. Circuit may be useful in biological telemetry for amplification of signals from specimen-implanted sensors.

An ultra-high input impedance ECG amplifier for long-term monitoring of athletes.

PubMed

Gargiulo, Gaetano; Bifulco, Paolo; Cesarelli, Mario; Ruffo, Mariano; Romano, Maria; Calvo, Rafael A; Jin, Craig; van Schaik, André

2010-01-01

We present a new, low-power electrocardiogram (ECG) recording system with an ultra-high input impedance that enables the use of long-lasting, dry electrodes. The system incorporates a low-power Bluetooth module for wireless connectivity and is designed to be suitable for long-term monitoring during daily activities. The new system using dry electrodes was compared with a clinically approved ECG reference system using gelled Ag/AgCl electrodes and performance was found to be equivalent. In addition, the system was used to monitor an athlete during several physical tasks, and a good quality ECG was obtained in all cases, including when the athlete was totally submerged in fresh water.

Is 50 Hz high enough ECG sampling frequency for accurate HRV analysis?

PubMed

Mahdiani, Shadi; Jeyhani, Vala; Peltokangas, Mikko; Vehkaoja, Antti

2015-01-01

With the worldwide growth of mobile wireless technologies, healthcare services can be provided at anytime and anywhere. Usage of wearable wireless physiological monitoring system has been extensively increasing during the last decade. These mobile devices can continuously measure e.g. the heart activity and wirelessly transfer the data to the mobile phone of the patient. One of the significant restrictions for these devices is usage of energy, which leads to requiring low sampling rate. This article is presented in order to investigate the lowest adequate sampling frequency of ECG signal, for achieving accurate enough time domain heart rate variability (HRV) parameters. For this purpose the ECG signals originally measured with high 5 kHz sampling rate were down-sampled to simulate the measurement with lower sampling rate. Down-sampling loses information, decreases temporal accuracy, which was then restored by interpolating the signals to their original sampling rates. The HRV parameters obtained from the ECG signals with lower sampling rates were compared. The results represent that even when the sampling rate of ECG signal is equal to 50 Hz, the HRV parameters are almost accurate with a reasonable error.

Wavelet-based watermarking and compression for ECG signals with verification evaluation.

PubMed

Tseng, Kuo-Kun; He, Xialong; Kung, Woon-Man; Chen, Shuo-Tsung; Liao, Minghong; Huang, Huang-Nan

2014-02-21

In the current open society and with the growth of human rights, people are more and more concerned about the privacy of their information and other important data. This study makes use of electrocardiography (ECG) data in order to protect individual information. An ECG signal can not only be used to analyze disease, but also to provide crucial biometric information for identification and authentication. In this study, we propose a new idea of integrating electrocardiogram watermarking and compression approach, which has never been researched before. ECG watermarking can ensure the confidentiality and reliability of a user's data while reducing the amount of data. In the evaluation, we apply the embedding capacity, bit error rate (BER), signal-to-noise ratio (SNR), compression ratio (CR), and compressed-signal to noise ratio (CNR) methods to assess the proposed algorithm. After comprehensive evaluation the final results show that our algorithm is robust and feasible.

Comparison of standard and Lewis ECG in detection of atrioventricular dissociation in patients with wide QRS tachycardia.

PubMed

Aksu, Uğur; Kalkan, Kamuran; Gülcü, Oktay; Topcu, Selim; Sevimli, Serdar; Aksakal, Enbiya; Ipek, Emrah; Açıkel, Mahmut; Tanboğa, Ibrahim Halil

2016-12-15

The atrioventricular (AV) dissociation, which is frequently used in differential diagnosis of wide QRS complex tachycardia (WQCT), is the most specific finding of ventricular tachycardia (VT) with lower sensitivity. Herein, we aimed to show the importance of Lewis lead ECG records to detect 'visible p waves' during WQCT. A total of 21 consecutive patients who underwent electrophysiologic study (EPS) were included in the study. During EPS, by using a quadripolar diagnostic catheter directed to the right ventricular apex, a fixed stimulus was given and the ventriculoatrial (VA) Wenkebach point was found, and a VT was simulated by a RV apical stimulus at 300ms. The standard and Lewis lead ECG records were taken during this procedure. We detected 'visible p waves' in 7 (33.3%) and 14 (66.7%) patients in the standard and Lewis lead ECG groups, respectively. In terms of the 'visible p waves', there was a statistically significant difference between groups (p=0.022). The sensitivity of standard and Lewis lead ECG in determination of the visible p waves was 33.3% and 66.7%, respectively. The Lewis lead ECG can be more informative about AV dissociation than the standard 12 lead ECG. As a result, we could suggest the assessment of the Lewis lead ECG recording in addition to the standard 12 lead ECG in differential diagnosis of VT in patients with WQCT. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A machine learning approach to multi-level ECG signal quality classification.

PubMed

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.

ECG contamination of EEG signals: effect on entropy.

PubMed

Chakrabarti, Dhritiman; Bansal, Sonia

2016-02-01

Entropy™ is a proprietary algorithm which uses spectral entropy analysis of electroencephalographic (EEG) signals to produce indices which are used as a measure of depth of hypnosis. We describe a report of electrocardiographic (ECG) contamination of EEG signals leading to fluctuating erroneous Entropy values. An explanation is provided for mechanism behind this observation by describing the spread of ECG signals in head and neck and its influence on EEG/Entropy by correlating the observation with the published Entropy algorithm. While the Entropy algorithm has been well conceived, there are still instances in which it can produce erroneous values. Such erroneous values and their cause may be identified by close scrutiny of the EEG waveform if Entropy values seem out of sync with that expected at given anaesthetic levels.

A wavelet-based ECG delineation algorithm for 32-bit integer online processing

PubMed Central

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

Home labour induction with retrievable prostaglandin pessary and continuous telemetric trans-abdominal fetal ECG monitoring.

PubMed

Rauf, Zubair; O'Brien, Ediri; Stampalija, Tamara; Ilioniu, Florin P; Lavender, Tina; Alfirevic, Zarko

2011-01-01

To evaluate the feasibility of continuous telemetric trans-abdominal fetal electrocardiogram (a-fECG) in women undergoing labour induction at home. Low risk women with singleton term pregnancy undergoing labour induction with retrievable, slow-release dinoprostone pessaries (n = 70) were allowed home for up to 24 hours, while a-fECG and uterine activity were monitored in hospital via wireless technology. Semi-structured diaries were analysed using a combined descriptive and interpretive approach. 62/70 women (89%) had successful home monitoring; 8 women (11%) were recalled because of signal loss. Home monitoring lasted between 2-22 hours (median 10 hours). Good quality signal was achieved most of the time (86%, SD 10%). 3 women were recalled back to hospital for suspicious a-fECG. In 2 cases suspicious a-fECG persisted, requiring Caesarean section after recall to hospital. 48/51 women who returned the diary coped well (94%); 46/51 were satisfied with home monitoring (90%). Continuous telemetric trans-abdominal fetal ECG monitoring of ambulatory women undergoing labour induction is feasible and acceptable to women.

ECG signal analysis through hidden Markov models.

PubMed

Andreão, Rodrigo V; Dorizzi, Bernadette; Boudy, Jérôme

2006-08-01

This paper presents an original hidden Markov model (HMM) approach for online beat segmentation and classification of electrocardiograms. The HMM framework has been visited because of its ability of beat detection, segmentation and classification, highly suitable to the electrocardiogram (ECG) problem. Our approach addresses a large panel of topics some of them never studied before in other HMM related works: waveforms modeling, multichannel beat segmentation and classification, and unsupervised adaptation to the patient's ECG. The performance was evaluated on the two-channel QT database in terms of waveform segmentation precision, beat detection and classification. Our waveform segmentation results compare favorably to other systems in the literature. We also obtained high beat detection performance with sensitivity of 99.79% and a positive predictivity of 99.96%, using a test set of 59 recordings. Moreover, premature ventricular contraction beats were detected using an original classification strategy. The results obtained validate our approach for real world application.

Bayesian Classification Models for Premature Ventricular Contraction Detection on ECG Traces.

PubMed

Casas, Manuel M; Avitia, Roberto L; Gonzalez-Navarro, Felix F; Cardenas-Haro, Jose A; Reyna, Marco A

2018-01-01

According to the American Heart Association, in its latest commission about Ventricular Arrhythmias and Sudden Death 2006, the epidemiology of the ventricular arrhythmias ranges from a series of risk descriptors and clinical markers that go from ventricular premature complexes and nonsustained ventricular tachycardia to sudden cardiac death due to ventricular tachycardia in patients with or without clinical history. The premature ventricular complexes (PVCs) are known to be associated with malignant ventricular arrhythmias and sudden cardiac death (SCD) cases. Detecting this kind of arrhythmia has been crucial in clinical applications. The electrocardiogram (ECG) is a clinical test used to measure the heart electrical activity for inferences and diagnosis. Analyzing large ECG traces from several thousands of beats has brought the necessity to develop mathematical models that can automatically make assumptions about the heart condition. In this work, 80 different features from 108,653 ECG classified beats of the gold-standard MIT-BIH database were extracted in order to classify the Normal, PVC, and other kind of ECG beats. Three well-known Bayesian classification algorithms were trained and tested using these extracted features. Experimental results show that the F1 scores for each class were above 0.95, giving almost the perfect value for the PVC class. This gave us a promising path in the development of automated mechanisms for the detection of PVC complexes.

High frequency QRS ECG predicts ischemic defects during myocardial perfusion imaging

NASA Technical Reports Server (NTRS)

2004-01-01

Changes in high frequency QRS components of the electrocardiogram (HF QRS ECG) (150-250 Hz) are more sensitive than changes in conventional ST segments for detecting myocardial ischemia. We investigated the accuracy of 12-lead HF QRS ECG in detecting ischemia during adenosine tetrofosmin myocardial perfusion imaging (MPI). 12-lead HF QRS ECG recordings were obtained from 45 patients before and during adenosine technetium-99 tetrofosmin MPI tests. Before the adenosine infusions, recordings of HF QRS were analyzed according to a morphological score that incorporated the number, type and location of reduced amplitude zones (RAZs) present in the 12 leads. During the adenosine infusions, recordings of HF QRS were analyzed according to the maximum percentage changes (in both the positive and negative directions) that occurred in root mean square (RMS) voltage amplitudes within the 12 leads. The best set of prospective HF QRS criteria had a sensitivity of 94% and a specificity of 83% for correctly identifying the MPI result. The sensitivity of simultaneous ST segment changes (18%) was significantly lower than that of any individual HF QRS criterion (P less than 0.00l). Analysis of 12-lead HF QRS ECG is highly sensitive and specific for detecting ischemic perfusion defects during adenosine MPI stress tests and significantly more sensitive than analysis of conventional ST segments.

High frequency QRS ECG predicts ischemic defects during myocardial perfusion imaging

NASA Technical Reports Server (NTRS)

Rahman, Atiar

2006-01-01

Background: Changes in high frequency QRS components of the electrocardiogram (HF QRS ECG) (150-250 Hz) are more sensitive than changes in conventional ST segments for detecting myocardial ischemia. We investigated the accuracy of 12-lead HF QRS ECG in detecting ischemia during adenosine tetrofosmin myocardial perfusion imaging (MPI). Methods and Results: 12-lead HF QRS ECG recordings were obtained from 45 patients before and during adenosine technetium-99 tetrofosmin MPI tests. Before the adenosine infusions, recordings of HF QRS were analyzed according to a morphological score that incorporated the number, type and location of reduced amplitude zones (RAZs) present in the 12 leads. During the adenosine infusions, recordings of HF QRS were analyzed according to the maximum percentage changes (in both the positive and negative directions) that occurred in root mean square (RMS) voltage amplitudes within the 12 leads. The best set of prospective HF QRS criteria had a sensitivity of 94% and a specificity of 83% for correctly identifying the MPI result. The sensitivity of simultaneous ST segment changes (18%) was significantly lower than that of any individual HF QRS criterion (P<0.001). Conclusions: Analysis of 12-lead HF QRS ECG is highly sensitive and specific for detecting ischemic perfusion defects during adenosine MPI stress tests and significantly more sensitive than analysis of conventional ST segments.

Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances

PubMed Central

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

On the Design of an Efficient Cardiac Health Monitoring System Through Combined Analysis of ECG and SCG Signals.

PubMed

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

On the Design of an Efficient Cardiac Health Monitoring System Through Combined Analysis of ECG and SCG Signals

PubMed Central

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

Extracting the respiration cycle lengths from ECG signal recorded with bed sheet electrodes

NASA Astrophysics Data System (ADS)

Vehkaoja, A.; Peltokangas, M.; Lekkala, J.

2013-09-01

A method for recognizing the respiration cycle lengths from the electrocardiographic (ECG) signal recorded with textile electrodes that are attached to a bed sheet is proposed. The method uses two features extracted from the ECG that are affected by the respiration: respiratory sinus arrhythmia and the amplitude of the R-peaks. The proposed method was tested in one hour long recordings with ten healthy young adults. A relative mean absolute error of 5.6 % was achieved when the algorithm was able to provide a result for approximately 40 % of the time. 90 % of the values were within 0.5 s and 97 % within 1 s from the reference respiration value. In addition to the instantaneous respiration cycle lengths, also the mean values during 1 and 5 minutes epochs are calculated. The effect of the ECG signal source is evaluated by calculating the result also from the simultaneously recorded reference ECG signal. The acquired respiration information can be used in the estimation of sleep quality and the detection of sleep disorders.

Washable and Reliable Textile Electrodes Embedded into Underwear Fabric for Electrocardiography (ECG) Monitoring

PubMed Central

Ankhili, Amale; Tao, Xuyuan; Cochrane, Cédric; Coulon, David; Koncar, Vladan

2018-01-01

A medical quality electrocardiogram (ECG) signal is necessary for permanent monitoring, and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The article focuses on textile electrode design and production guaranteeing optimal contact impedance. Therefore, different types of textile fabrics were coated with modified poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) in order to develop and manufacture reliable and washable textile electrodes assembled to female underwear (bras), by sewing using commercially available conductive yarns. Washability tests of connected underwear containing textile electrodes and conductive threads were carried out up to 50 washing cycles. The influence of standardized washing cycles on the quality of ECG signals and the electrical properties of the textile electrodes were investigated and characterized. PMID:29414849

Washable and Reliable Textile Electrodes Embedded into Underwear Fabric for Electrocardiography (ECG) Monitoring.

PubMed

Ankhili, Amale; Tao, Xuyuan; Cochrane, Cédric; Coulon, David; Koncar, Vladan

2018-02-07

A medical quality electrocardiogram (ECG) signal is necessary for permanent monitoring, and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The article focuses on textile electrode design and production guaranteeing optimal contact impedance. Therefore, different types of textile fabrics were coated with modified poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) in order to develop and manufacture reliable and washable textile electrodes assembled to female underwear (bras), by sewing using commercially available conductive yarns. Washability tests of connected underwear containing textile electrodes and conductive threads were carried out up to 50 washing cycles. The influence of standardized washing cycles on the quality of ECG signals and the electrical properties of the textile electrodes were investigated and characterized.

Issues in implementing a knowledge-based ECG analyzer for personal mobile health monitoring.

PubMed

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.

Implementation of a wireless ECG acquisition SoC for IEEE 802.15.4 (ZigBee) applications.

PubMed

Wang, Liang-Hung; Chen, Tsung-Yen; Lin, Kuang-Hao; Fang, Qiang; Lee, Shuenn-Yuh

2015-01-01

This paper presents a wireless biosignal acquisition system-on-a-chip (WBSA-SoC) specialized for electrocardiogram (ECG) monitoring. The proposed system consists of three subsystems, namely, 1) the ECG acquisition node, 2) the protocol for standard IEEE 802.15.4 ZigBee system, and 3) the RF transmitter circuits. The ZigBee protocol is adopted for wireless communication to achieve high integration, applicability, and portability. A fully integrated CMOS RF front end containing a quadrature voltage-controlled oscillator and a 2.4-GHz low-IF (i.e., zero-IF) transmitter is employed to transmit ECG signals through wireless communication. The low-power WBSA-SoC is implemented by the TSMC 0.18-μm standard CMOS process. An ARM-based displayer with FPGA demodulation and an RF receiver with analog-to-digital mixed-mode circuits are constructed as verification platform to demonstrate the wireless ECG acquisition system. Measurement results on the human body show that the proposed SoC can effectively acquire ECG signals.

Study on a Biometric Authentication Model based on ECG using a Fuzzy Neural Network

NASA Astrophysics Data System (ADS)

Kim, Ho J.; Lim, Joon S.

2018-03-01

Traditional authentication methods use numbers or graphic passwords and thus involve the risk of loss or theft. Various studies are underway regarding biometric authentication because it uses the unique biometric data of a human being. Biometric authentication technology using ECG from biometric data involves signals that record electrical stimuli from the heart. It is difficult to manipulate and is advantageous in that it enables unrestrained measurements from sensors that are attached to the skin. This study is on biometric authentication methods using the neural network with weighted fuzzy membership functions (NEWFM). In the biometric authentication process, normalization and the ensemble average is applied during preprocessing, characteristics are extracted using Haar-wavelets, and a registration process called “training” is performed in the fuzzy neural network. In the experiment, biometric authentication was performed on 73 subjects in the Physionet Database. 10-40 ECG waveforms were tested for use in the registration process, and 15 ECG waveforms were deemed the appropriate number for registering ECG waveforms. 1 ECG waveforms were used during the authentication stage to conduct the biometric authentication test. Upon testing the proposed biometric authentication method based on 73 subjects from the Physionet Database, the TAR was 98.32% and FAR was 5.84%.

Construction of a Resting High Fidelity ECG "SuperScore" for Management and Screening of Heart Disease

NASA Technical Reports Server (NTRS)

Schlegel, Todd T.; Delgado, Reynolds; Poulin, Greg; Starc, Vito; Arenare, Brian; Rahman, M. A.

2006-01-01

Resting conventional ECG is notoriously insensitive for detecting coronary artery disease (CAD) and only nominally useful in screening for cardiomyopathy (CM). Similarly, conventional exercise stress test ECG is both time- and labor-consuming and its accuracy in identifying CAD is suboptimal for use in population screening. We retrospectively investigated the accuracy of several advanced resting electrocardiographic (ECG) parameters, both alone and in combination, for detecting CAD and cardiomyopathy (CM).

Educational technology improves ECG interpretation of acute myocardial infarction among medical students and emergency medicine residents.

PubMed

Pourmand, Ali; Tanski, Mary; Davis, Steven; Shokoohi, Hamid; Lucas, Raymond; Zaver, Fareen

2015-01-01

Asynchronous online training has become an increasingly popular educational format in the new era of technology-based professional development. We sought to evaluate the impact of an online asynchronous training module on the ability of medical students and emergency medicine (EM) residents to detect electrocardiogram (ECG) abnormalities of an acute myocardial infarction (AMI). We developed an online ECG training and testing module on AMI, with emphasis on recognizing ST elevation myocardial infarction (MI) and early activation of cardiac catheterization resources. Study participants included senior medical students and EM residents at all post-graduate levels rotating in our emergency department (ED). Participants were given a baseline set of ECGs for interpretation. This was followed by a brief interactive online training module on normal ECGs as well as abnormal ECGs representing an acute MI. Participants then underwent a post-test with a set of ECGs in which they had to interpret and decide appropriate intervention including catheterization lab activation. 148 students and 35 EM residents participated in this training in the 2012-2013 academic year. Students and EM residents showed significant improvements in recognizing ECG abnormalities after taking the asynchronous online training module. The mean score on the testing module for students improved from 5.9 (95% CI [5.7-6.1]) to 7.3 (95% CI [7.1-7.5]), with a mean difference of 1.4 (95% CI [1.12-1.68]) (p<0.0001). The mean score for residents improved significantly from 6.5 (95% CI [6.2-6.9]) to 7.8 (95% CI [7.4-8.2]) (p<0.0001). An online interactive module of training improved the ability of medical students and EM residents to correctly recognize the ECG evidence of an acute MI.

Study design and rationale for biomedical shirt-based electrocardiography monitoring in relevant clinical situations: ECG-shirt study.

PubMed

Balsam, Paweł; Lodziński, Piotr; Tymińska, Agata; Ozierański, Krzysztof; Januszkiewicz, Łukasz; Główczyńska, Renata; Wesołowska, Katarzyna; Peller, Michał; Pietrzak, Radosław; Książczyk, Tomasz; Borodzicz, Sonia; Kołtowski, Łukasz; Borkowski, Mariusz; Werner, Bożena; Opolski, Grzegorz; Grabowski, Marcin

2018-01-01

Today, the main challenge for researchers is to develop new technologies which may help to improve the diagnoses of cardiovascular disease (CVD), thereby reducing healthcare costs and improving the quality of life for patients. This study aims to show the utility of biomedical shirt-based electrocardiography (ECG) monitoring of patients with CVD in different clinical situations using the Nuubo® ECG (nECG) system. An investigator-initiated, multicenter, prospective observational study was carried out in a cardiology (adult and pediatric) and cardiac rehabilitation wards. ECG monitoring was used with the biomedical shirt in the following four independent groups of patients: 1) 30 patients after pulmonary vein isolation (PVI), 2) 30 cardiac resynchronization therapy (CRT) recipients, 3) 120 patients during cardiac rehabilitation after myocardial infarction, and 4) 40 pediatric patients with supraventricular tachycardia (SVT) before electrophysiology study. Approval for all study groups was obtained from the institutional review board. The biomedical shirt captures the electrocardiographic signal via textile electrodes integrated into a garment. The software allows the visualization and analysis of data such as ECG, heart rate, arrhythmia detecting algorithm and relative position of the body is captured by an electronic device. The major advantages of the nECG system are continuous ECG monitoring during daily activities, high quality of ECG recordings, as well as assurance of a proper adherence due to adequate comfort while wearing the shirt. There are only a few studies that have examined wearable systems, especially in pediatric populations. This study is registered in ClinicalTrials.gov: Identifier NCT03068169. (Cardiol J 2018; 25, 1: 52-59).

Association between use of pre-hospital ECG and 30-day mortality: A large cohort study of patients experiencing chest pain.

PubMed

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.

ECG-derived Cheyne-Stokes respiration and periodic breathing in healthy and hospitalized populations.

PubMed

Tinoco, Adelita; Drew, Barbara J; Hu, Xiao; Mortara, David; Cooper, Bruce A; Pelter, Michele M

2017-11-01

Cheyne-Stokes respiration (CSR) has been investigated primarily in outpatients with heart failure. In this study we compare CSR and periodic breathing (PB) between healthy and cardiac groups. We compared CSR and PB, measured during 24 hr of continuous 12-lead electrocardiographic (ECG) Holter recording, in a group of 90 hospitalized patients presenting to the emergency department with symptoms suggestive of acute coronary syndrome (ACS) to a group of 100 healthy ambulatory participants. We also examined CSR and PB in the 90 patients presenting with ACS symptoms, divided into a group of 39 (43%) with confirmed ACS, and 51 (57%) with a cardiac diagnosis but non-ACS. SuperECG software was used to derive respiration and then calculate CSR and PB episodes from the ECG Holter data. Regression analyses were used to analyze the data. We hypothesized SuperECG software would differentiate between the groups by detecting less CSR and PB in the healthy group than the group of patients presenting to the emergency department with ACS symptoms. Hospitalized patients with suspected ACS had 7.3 times more CSR episodes and 1.6 times more PB episodes than healthy ambulatory participants. Patients with confirmed ACS had 6.0 times more CSR episodes and 1.3 times more PB episodes than cardiac non-ACS patients. Continuous 12-lead ECG derived CSR and PB appear to differentiate between healthy participants and hospitalized patients. © 2017 Wiley Periodicals, Inc.

Cost-effectiveness analysis of computerized ECG interpretation system in an ambulatory health care organization.

PubMed

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."

Prevalence of ECG changes during adenosine stress and its association with perfusion defect on myocardial perfusion scintigraphy.

PubMed

Taywade, Sameer K; Ramaiah, Vijayaraghavan L; Basavaraja, Harish; Venkatasubramaniam, Parameswaran R; Selvakumar, Job

2017-04-01

Myocardial perfusion scintigraphy (MPS) is a valuable, noninvasive imaging modality in the evaluation of patients with coronary artery disease. Adenosine stress may occasionally be associated with ECG changes. This study evaluated the strength of association between adenosine stress-related ECG changes and perfusion defects on Tc-MPS. 117 (mean age: 61.25±9.27 years; sex: men 87, women 30) patients with known/suspected coronary artery disease underwent adenosine stress MPS. ECG was monitored continuously during adenosine stress for ST-depression. On the basis of the summed difference score, reversible perfusion defects were categorized as follows: normal: less than 4, mild: 4-8, moderate: 9-13, and severe: more than 13. ST-depression was observed in 27/117 (23.1%) and reversible perfusion defects were observed in 18/27 (66.66%) patients. 2/27, 6/27, and 10/27 patients had mild, moderate, and severe ischemia, respectively. 9/27 patients had normal perfusion. ECG changes and perfusion defects showed a moderate strength of association (correlation coefficient r=0.35, P=0.006). The sensitivity, specificity, positive predictive value, and negative predictive value of ECG findings for prediction of ischemia were 35.29, 86.36, 67.67, and 63.33%, respectively. ECG changes during adenosine stress are not uncommon. It shows a moderate strength of association with reversible perfusion defects. ECG changes during adenosine merit critical evaluation of MPS findings.

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal

PubMed Central

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

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

PubMed

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.

Presetting ECG electrodes for earlier heart rate detection in the delivery room.

PubMed

Gulati, Rashmi; Zayek, Michael; Eyal, Fabien

2018-07-01

To determine whether heart rate (HR) could be detected earlier than by pulse oximeter (POX), using a novel method of application of electrocardiogram (ECG) electrodes during neonatal resuscitation in the delivery room. ECG electrodes were set before delivery to be applied to the back of infants' thorax. Time to detect HR was recorded as soon as a numerical HR along with a recognizable and persistent QRS complex was observed on ECG monitor (HRECG) and a plethysmographic waveform was seen on POX monitor (HRPOX). Out of 334 infants, 49 were <31 weeks of gestational age. Overall, the median (interquartile range, IQR) time to detect HRECG was significantly shorter [29 (5, 60) seconds] than time by POX [60 (45,120) seconds], (p < 0.001). Similarly, in <31-week infants, the median (IQR) time to detect HRECG was 10 (2, 40) seconds compared to 60 (30,120) seconds by POX, (p < 0.001). Failure to have HR detected by 1 minute occurred in 30%, 54% and 20% of infants by ECG, POX and either of the devices, respectively. In the delivery room, electrodes applied by the study method are more effective than pulse oximetry in providing the neonatal team with timely HR information that is necessary for proper resuscitative actions. Published by Elsevier B.V.

[A Smart Low-Power-Consumption ECG Monitor Based on MSP430F5529 and CC2540].

PubMed

Gong, Yuan; Cao, Jin; Luo, Zehui; Zhou, Guohui

2015-07-01

A design of ECG monitor was presented in this paper. It is based on the latest MCU and BLE4.0 technologies and can interact with multi-platform smart devices with extra low power consumption. Besides, a clinical expansion part can realize functions including displaying the real-time ECG and heart rate curve, reading abnormal ECG signals stored in the monitor, and setting alarm threshold. These functions are suitable for follow-up use.

An ultra low power ECG signal processor design for cardiovascular disease detection.

PubMed

Jain, Sanjeev Kumar; Bhaumik, Basabi

2015-08-01

This paper presents an ultra low power ASIC design based on a new cardiovascular disease diagnostic algorithm. This new algorithm based on forward search is designed for real time ECG signal processing. The algorithm is evaluated for Physionet PTB database from the point of view of cardiovascular disease diagnosis. The failed detection rate of QRS complex peak detection of our algorithm ranges from 0.07% to 0.26% for multi lead ECG signal. The ASIC is designed using 130-nm CMOS low leakage process technology. The area of ASIC is 1.21 mm(2). This ASIC consumes only 96 nW at an operating frequency of 1 kHz with a supply voltage of 0.9 V. Due to ultra low power consumption, our proposed ASIC design is most suitable for energy efficient wearable ECG monitoring devices.

A PC-based generator of surface ECG potentials for computer electrocardiograph testing.

PubMed

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.

Acute ECG changes and chest pain induced by neck motion in patients with cervical hernia--a case report.

PubMed

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.

What adult electrocardiogram (ECG) diagnoses and/or findings do residents in emergency medicine need to know?

PubMed

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.

Relationship between echocardiographic LV mass and ECG based left ventricular voltages in an adolescent population: related or random?

PubMed

Czosek, Richard J; Cnota, James F; Knilans, Timothy K; Pratt, Jesse; Guerrier, Karine; Anderson, Jeffrey B

2014-09-01

In attempts to detect diseases that may place adolescents at risk for sudden death, some have advocated for population-based screening. Controversy exists over electrocardiography (ECG) screening due to the lack of specificity, cost, and detrimental effects of false positive or extraneous outcomes. Analyze the relationship between precordial lead voltage on ECG and left ventricle (LV) mass by echocardiogram in adolescent athletes. Retrospective cohort analysis of a prospectively obtained population of self-identified adolescent athletes during sports screening with ECG and echocardiogram. Correlation between ECG LV voltages (R wave in V6 [RV6] and S wave in lead V1 [SV1]) was compared to echocardiogram-based measurements of left ventricular mass. Potential effects on ECG voltages by body anthropometrics, including weight, body mass index (BMI), and body surface area were analyzed, and ECG voltages indexed to BMI were compared to LV mass indices to analyze for improved correlation. A total of 659 adolescents enrolled in this study (64% male). The mean age was 15.4 years (14-18). The correlations between LV mass and RV6, SV1, and RV6 + SV1 were all less than 0.20. The false positive rate for abnormal voltages was relatively high (5.5%) but improved if abnormal voltages in both RV6 and SV1 were mandated simultaneously (0%). Indexing ECG voltages to BMI significantly improved correlation to LV mass, though false positive findings were increased (12.9%). There is poor correlation between ECG precordial voltages and echocardiographic LV mass. This relationship is modified by BMI. This finding may contribute to the poor ECG screening characteristics. ©2014 Wiley Periodicals, Inc.

Feasibility of Using Mobile ECG Recording Technology to Detect Atrial Fibrillation in Low-Resource Settings.

PubMed

Evans, Grahame F; Shirk, Arianna; Muturi, Peter; Soliman, Elsayed Z

2017-12-01

Screening for atrial fibrillation (AF), a major risk factor for stroke that is on the rise in Africa, is becoming increasingly critical. This study sought to examine the feasibility of using mobile electrocardiogram (ECG) recording technology to detect AF. In this prospective observational study, we used a mobile ECG recorder to screen 50 African adults (66% women; mean age 54.3 ± 20.5 years) attending Kijabe Hospital (Kijabe, Kenya). Five hospital health providers involved in this study's data collection process also completed a self-administered survey to obtain information on their access to the Internet and mobile devices, both factors necessary to implement ECG mobile technology. Outcome measures included feasibility (completion of the study and recruitment of the patients on the planned study time frame) and the yield of the screening by the mobile ECG technology (ability to detect previously undiagnosed AF). Patients were recruited in a 2-week period as planned; only 1 of the 51 patients approached refused to participate (98% acceptance rate). All of the 50 patients who agreed to participate completed the test and produced readable ECGs (100% study completion rate). ECG tracings of 4 of the 50 patients who completed the study showed AF (8% AF yield), and none had been previously diagnosed with AF. When asked about continuous access to Internet and personal mobile devices, almost all of the health care providers surveyed answered affirmatively. Using mobile ECG technology in screening for AF in low-resource settings is feasible, and can detect a significant proportion of AF cases that will otherwise go undiagnosed. Further study is needed to examine the cost-effectiveness of this approach for detection of AF and its effect on reducing the risk of stroke in developing countries. Copyright © 2016 World Heart Federation (Geneva). Published by Elsevier B.V. All rights reserved.

Study of ECG changes and its relation to mortality in cases of cerebrovascular accidents.

PubMed

Purushothaman, Suja; Salmani, Deepalaxmi; Prarthana, Kaleramma Gopalakrishna; Bandelkar, Srinidhi Muddanna Gundappa; Varghese, Sarah

2014-07-01

Its being long recognized about the highly debilitating and destructive nature of cerebrovascular accidents (CVAs). Around the world CVAs has posed as a major factor in medical morbidity and mortality. It has thrown up challenges with regards to their medical management and also towards posttreatment rehabilitation. It is well-known that neurologic disorder contributes variously towards varied electrocardiogram (ECG) changes and stroke is no exception. To study the ECG changes and its relation to mortality in cases of CVA. A total of 100 patients with acute stroke were enrolled in the study. All the 100 patients underwent ECG recording within first 24 h of admission. The patients were divided into ischemic and hemorrhagic group depending on the nature of lesion. Out of 100 cases, 58 were ischemic and 42 were hemorrhagic. The ECG changes were noted in 78 patients. Among the ischemic group, the changes noted in the ECG were: T wave inversion (34.48%), ST segment depression (32.75%), QTc prolongation (29.31%), and presence of U waves (27.58%). In cases of hemorrhagic stroke, it was: T wave inversion (33.33%), arrhythmias (33.33%), U waves (30.95%), and ST segment depression (23.80%). Mortality was higher in patients with ST-T changes in ischemic group (66.66%) and in patients with positive U waves (60%) in hemorrhagic group. In acute stroke patients, changes in ECG were commonly seen. The changes varied from T-wave inversion to ST segment depression in ischemic stroke. In hemorrhagic stroke it consisted of T wave inversion and arrhythmias. Overall mortality was high in cases of hemorrhagic compared to ischemic group.

Study of ECG changes and its relation to mortality in cases of cerebrovascular accidents

PubMed Central

Purushothaman, Suja; Salmani, Deepalaxmi; Prarthana, Kaleramma Gopalakrishna; Bandelkar, Srinidhi Muddanna Gundappa; Varghese, Sarah

2014-01-01

Background: Its being long recognized about the highly debilitating and destructive nature of cerebrovascular accidents (CVAs). Around the world CVAs has posed as a major factor in medical morbidity and mortality. It has thrown up challenges with regards to their medical management and also towards posttreatment rehabilitation. It is well-known that neurologic disorder contributes variously towards varied electrocardiogram (ECG) changes and stroke is no exception. Objective: To study the ECG changes and its relation to mortality in cases of CVA. Materials and Methods: A total of 100 patients with acute stroke were enrolled in the study. All the 100 patients underwent ECG recording within first 24 h of admission. The patients were divided into ischemic and hemorrhagic group depending on the nature of lesion. Results: Out of 100 cases, 58 were ischemic and 42 were hemorrhagic. The ECG changes were noted in 78 patients. Among the ischemic group, the changes noted in the ECG were: T wave inversion (34.48%), ST segment depression (32.75%), QTc prolongation (29.31%), and presence of U waves (27.58%). In cases of hemorrhagic stroke, it was: T wave inversion (33.33%), arrhythmias (33.33%), U waves (30.95%), and ST segment depression (23.80%). Mortality was higher in patients with ST-T changes in ischemic group (66.66%) and in patients with positive U waves (60%) in hemorrhagic group. Conclusion: In acute stroke patients, changes in ECG were commonly seen. The changes varied from T-wave inversion to ST segment depression in ischemic stroke. In hemorrhagic stroke it consisted of T wave inversion and arrhythmias. Overall mortality was high in cases of hemorrhagic compared to ischemic group. PMID:25097430

Fetal electrocardiogram (ECG) for fetal monitoring during labour.

PubMed

Neilson, James P

2015-12-21

Hypoxaemia during labour can alter the shape of the fetal electrocardiogram (ECG) waveform, notably the relation of the PR to RR intervals, and elevation or depression of the ST segment. Technical systems have therefore been developed to monitor the fetal ECG during labour as an adjunct to continuous electronic fetal heart rate monitoring with the aim of improving fetal outcome and minimising unnecessary obstetric interference. To compare the effects of analysis of fetal ECG waveforms during labour with alternative methods of fetal monitoring. The Cochrane Pregnancy and Childbirth Group's Trials Register (latest search 23 September 2015) and reference lists of retrieved studies. Randomised trials comparing fetal ECG waveform analysis with alternative methods of fetal monitoring during labour. One review author independently assessed trials for inclusion and risk of bias, extracted data and checked them for accuracy. One review author assessed the quality of the evidence using the GRADE approach. Seven trials (27,403 women) were included: six trials of ST waveform analysis (26,446 women) and one trial of PR interval analysis (957 women). The trials were generally at low risk of bias for most domains and the quality of evidence for ST waveform analysis trials was graded moderate to high. In comparison to continuous electronic fetal heart rate monitoring alone, the use of adjunctive ST waveform analysis made no obvious difference to primary outcomes: births by caesarean section (risk ratio (RR) 1.02, 95% confidence interval (CI) 0.96 to 1.08; six trials, 26,446 women; high quality evidence); the number of babies with severe metabolic acidosis at birth (cord arterial pH less than 7.05 and base deficit greater than 12 mmol/L) (average RR 0.72, 95% CI 0.43 to 1.20; six trials, 25,682 babies; moderate quality evidence); or babies with neonatal encephalopathy (RR 0.61, 95% CI 0.30 to 1.22; six trials, 26,410 babies; high quality evidence). There were, however, on average

Epileptic seizure onset detection based on EEG and ECG data fusion.

PubMed

Qaraqe, Marwa; Ismail, Muhammad; Serpedin, Erchin; Zulfi, Haneef

2016-05-01

This paper presents a novel method for seizure onset detection using fused information extracted from multichannel electroencephalogram (EEG) and single-channel electrocardiogram (ECG). In existing seizure detectors, the analysis of the nonlinear and nonstationary ECG signal is limited to the time-domain or frequency-domain. In this work, heart rate variability (HRV) extracted from ECG is analyzed using a Matching-Pursuit (MP) and Wigner-Ville Distribution (WVD) algorithm in order to effectively extract meaningful HRV features representative of seizure and nonseizure states. The EEG analysis relies on a common spatial pattern (CSP) based feature enhancement stage that enables better discrimination between seizure and nonseizure features. The EEG-based detector uses logical operators to pool SVM seizure onset detections made independently across different EEG spectral bands. Two fusion systems are adopted. In the first system, EEG-based and ECG-based decisions are directly fused to obtain a final decision. The second fusion system adopts an override option that allows for the EEG-based decision to override the fusion-based decision in the event that the detector observes a string of EEG-based seizure decisions. The proposed detectors exhibit an improved performance, with respect to sensitivity and detection latency, compared with the state-of-the-art detectors. Experimental results demonstrate that the second detector achieves a sensitivity of 100%, detection latency of 2.6s, and a specificity of 99.91% for the MAJ fusion case. Copyright © 2016 Elsevier Inc. All rights reserved.

Radiotherapy-induced Early ECG Changes and Their Comparison with Echocardiography in Patients with Early-stage Breast Cancer.

PubMed

Tuohinen, Suvi Sirkku; Keski-Pukkila, Konsta; Skyttä, Tanja; Huhtala, Heini; Virtanen, Vesa; Kellokumpu-Lehtinen, Pirkko-Liisa; Raatikainen, Pekka; Nikus, Kjell

2018-04-01

Early electrocardiogram (ECG) changes after breast cancer radiotherapy (RT) have been reported, but their characteristics and associated factors are largely unknown. This study aimed to explore early RT-induced ECG changes and to compare them with echocardiography changes. Sixty eligible patients with chemotherapy-naïve left-sided and 20 with right-sided breast cancer were evaluated with echocardiography, blood samples and ECG before and after RT. RT-induced ECG changes in the anterior leads. T-Wave changes were most frequent. T-Wave decline was associated independently with patient age (β=-0.245, p=0.005), mean heart radiation dose (β=1.252, p=0.001) and global systolic strain rate change (β=7.943, p=0.002). T-Wave inversion was associated independently with mean heart radiation dose (β=0.143, p<0.001), global longitudinal strain change (β=0.053, p=0.017) and posterior calibrated integrated backscatter (β=-0.022, p=0.049). RT-induced ECG changes were prevalent and associated with functional and structural changes in echocardiography. ECG could be used for post-RT cardiac screening. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Future cardiac events in patients with ischemic ECG changes during adenosine infusion as a myocardial stress agent and normal cardiac scan.

PubMed

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.

Unsupervised feature relevance analysis applied to improve ECG heartbeat clustering.

PubMed

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.

Compressed sensing system considerations for ECG and EMG wireless biosensors.

PubMed

Dixon, Anna M R; Allstot, Emily G; Gangopadhyay, Daibashish; Allstot, David J

2012-04-01

Compressed sensing (CS) is an emerging signal processing paradigm that enables sub-Nyquist processing of sparse signals such as electrocardiogram (ECG) and electromyogram (EMG) biosignals. Consequently, it can be applied to biosignal acquisition systems to reduce the data rate to realize ultra-low-power performance. CS is compared to conventional and adaptive sampling techniques and several system-level design considerations are presented for CS acquisition systems including sparsity and compression limits, thresholding techniques, encoder bit-precision requirements, and signal recovery algorithms. Simulation studies show that compression factors greater than 16X are achievable for ECG and EMG signals with signal-to-quantization noise ratios greater than 60 dB.

Estimating actigraphy from motion artifacts in ECG and respiratory effort signals.

PubMed

Fonseca, Pedro; Aarts, Ronald M; Long, Xi; Rolink, Jérôme; Leonhardt, Steffen

2016-01-01

Recent work in unobtrusive sleep/wake classification has shown that cardiac and respiratory features can help improve classification performance. Nevertheless, actigraphy remains the single most discriminative modality for this task. Unfortunately, it requires the use of dedicated devices in addition to the sensors used to measure electrocardiogram (ECG) or respiratory effort. This paper proposes a method to estimate actigraphy from the body movement artifacts present in the ECG and respiratory inductance plethysmography (RIP) based on the time-frequency analysis of those signals. Using a continuous wavelet transform to analyze RIP, and ECG and RIP combined, it provides a surrogate measure of actigraphy with moderate correlation (for ECG+RIP, ρ = 0.74, p  <  0.001) and agreement (mean bias ratio of 0.94 and 95% agreement ratios of 0.11 and 8.45) with reference actigraphy. More important, it can be used as a replacement of actigraphy in sleep/wake classification: after cross-validation with a data set comprising polysomnographic (PSG) recordings of 15 healthy subjects and 25 insomniacs annotated by an external sleep technician, it achieves a statistically non-inferior classification performance when used together with respiratory features (average κ of 0.64 for 15 healthy subjects, and 0.50 for a dataset with 40 healthy and insomniac subjects), and when used together with respiratory and cardiac features (average κ of 0.66 for 15 healthy subjects, and 0.56 for 40 healthy and insomniac subjects). Since this method eliminates the need for a dedicated actigraphy device, it reduces the number of sensors needed for sleep/wake classification to a single sensor when using respiratory features, and to two sensors when using respiratory and cardiac features without any loss in performance. It offers a major benefit in terms of comfort for long-term home monitoring and is immediately applicable for legacy ECG and RIP monitoring devices already used in clinical

Autoadaptivity and optimization in distributed ECG interpretation.

PubMed

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.

A Primary Study of Indirect ECG Monitor Embedded in a Bed for Home Health Care

NASA Astrophysics Data System (ADS)

Ueno, Akinori; Shiogai, Yuuki; Ishiyama, Yoji

A system for monitoring electrocardiogram (ECG) through clothes inserted between the measuring electrodes and the body surface of a subject when lying on a mattress has been proposed. The principle of the system is based on capacitive coupling involving the electrode, the clothes, and the skin. Validation of the system revealed the following: (1) In spite of the gain attenuation in the pass band of the system, distortion of the detected signal was subtle even when clothes thicker than 1mm were inserted, (2) The system was able to yield a stable ECG from a subject particularly during sound sleep, (3) The system succeeded in detecting ECG after changing the posture into any of supine, right lateral, or left lateral positions by adopting a newly devised electrode configuration. Therefore, the proposed system appears promising for application to bedding as a non-invasive and awareness-free system for ECG monitoring during sleep.

Automatic detection of ECG cable interchange by analyzing both morphology and interlead relations.

PubMed

Han, Chengzong; Gregg, Richard E; Feild, Dirk Q; Babaeizadeh, Saeed

2014-01-01

ECG cable interchange can generate erroneous diagnoses. For algorithms detecting ECG cable interchange, high specificity is required to maintain a low total false positive rate because the prevalence of interchange is low. In this study, we propose and evaluate an improved algorithm for automatic detection and classification of ECG cable interchange. The algorithm was developed by using both ECG morphology information and redundancy information. ECG morphology features included QRS-T and P-wave amplitude, frontal axis and clockwise vector loop rotation. The redundancy features were derived based on the EASI™ lead system transformation. The classification was implemented using linear support vector machine. The development database came from multiple sources including both normal subjects and cardiac patients. An independent database was used to test the algorithm performance. Common cable interchanges were simulated by swapping either limb cables or precordial cables. For the whole validation database, the overall sensitivity and specificity for detecting precordial cable interchange were 56.5% and 99.9%, and the sensitivity and specificity for detecting limb cable interchange (excluding left arm-left leg interchange) were 93.8% and 99.9%. Defining precordial cable interchange or limb cable interchange as a single positive event, the total false positive rate was 0.7%. When the algorithm was designed for higher sensitivity, the sensitivity for detecting precordial cable interchange increased to 74.6% and the total false positive rate increased to 2.7%, while the sensitivity for detecting limb cable interchange was maintained at 93.8%. The low total false positive rate was maintained at 0.6% for the more abnormal subset of the validation database including only hypertrophy and infarction patients. The proposed algorithm can detect and classify ECG cable interchanges with high specificity and low total false positive rate, at the cost of decreased sensitivity for

Response of the ECG to short-term diuresis in patients with heart failure.

PubMed

Madias, John E; Song, Jessica; White, C Michael; Kalus, James S; Kluger, Jeffrey

2005-07-01

Increase in the amplitude of electrocardiogram (ECG) QRS complexes has been observed in patients treated for heart failure (HF), but the underlying mechanism has not been delineated. Also, correlation of augmentation of the QRS potentials with loss of weight has been noted in patients recovering from anasarca of varying etiology, or after hemodialysis. We assessed the effect of diuresis-based fluid loss in patients treated for HF on the amplitude of ECG QRS complexes. This is a cohort study based on ECG and other data from a previously published investigation of patients with HF conducted at a university affiliated hospital, which used new measurements and analysis, performed by a totally blinded investigator based at another institution. Twenty-one patients (10 men) aged 70.5+/-12.7 years, 13 with ischemic, and 8 with nonischemic cardiomyopathy, were admitted to the hospital for management of exacerbated HF and were observed for 48 hours. The patients received diuresis, and had routine laboratory testing, documentation of the net fluid lost, and recording of ECGs prior to the initiation of therapy and at 24 and 48 hours. Percent change (%Delta) over the course of observation in the sums of the amplitude of QRS complexes from 12 leads (SigmaQRS12), 6-limb leads (SigmaQRS6), and leads 1+2 (SigmaQRS2) in mm of standard ECGs were correlated with net fluid loss corrected for admission weight in mL/kg. Fluid loss amounted to 3204.9+/-1399.5 mL in the course of 40+/-23 hours of diuresis. SigmaQRS12 was 160.9+/-42.3 mm before and 170.0+/-50.7 mm after diuresis (P=0. 024). Percent change in SigmaQRS12, SigmaQRS6, and SigmaQRS2 correlated well with the net fluid loss (r=-0.70, -0.82, -0.61, and P=0.002, 0.0005, 0.001) correspondingly. Changes in sums of the amplitude of QRS complexes of the standard ECG correlates well with net fluid loss in response to short-term diuresis in patients with HF. Change in the SigmaQRS12, SigmaQRS6, and SigmaQRS2 from ECGs before and after

CardioGuard: A Brassiere-Based Reliable ECG Monitoring Sensor System for Supporting Daily Smartphone Healthcare Applications

PubMed Central

Kwon, Sungjun; Kim, Jeehoon; Kang, Seungwoo; Lee, Youngki; Baek, Hyunjae

2014-01-01

Abstract We propose CardioGuard, a brassiere-based reliable electrocardiogram (ECG) monitoring sensor system, for supporting daily smartphone healthcare applications. It is designed to satisfy two key requirements for user-unobtrusive daily ECG monitoring: reliability of ECG sensing and usability of the sensor. The system is validated through extensive evaluations. The evaluation results showed that the CardioGuard sensor reliably measure the ECG during 12 representative daily activities including diverse movement levels; 89.53% of QRS peaks were detected on average. The questionnaire-based user study with 15 participants showed that the CardioGuard sensor was comfortable and unobtrusive. Additionally, the signal-to-noise ratio test and the washing durability test were conducted to show the high-quality sensing of the proposed sensor and its physical durability in practical use, respectively. PMID:25405527

A Modular Low-Complexity ECG Delineation Algorithm for Real-Time Embedded Systems.

PubMed

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.

Antimyotonic therapy with tocainide under ECG control in the myotonic dystrophy of Curschmann-Steinert.

PubMed

Mielke, U; Haass, A; Sen, S; Schmidt, W

1985-01-01

Ten patients suffering from advanced myotonic dystrophy with severe myotonic symptoms were treated with 800-1200 mg/day of the anti-arrhythmic drug tocainide (Xylotocan). All patients reported a marked subjective improvement of myotonia, which was confirmed by objective tests. Except for a slight QT-prolongation in one patient, the ECG was not significantly altered by the treatment. Twenty-four-hour ECG after treatment disclosed that pre-existing ventricular arrhythmia disappeared in three cases. The occurrence of complex ventricular arrhythmia in two patients under treatment was not necessarily due to specific effects of the drug but might be explained by the high spontaneous variability of rhythm disorders. In these patients suffering from myotonic dystrophy with typical cardiomyopathy no deleterious effects of the drug were observed, especially no cardiac arrhythmias which would have necessitated interruption of treatment. Therefore, the authors recommend symptomatic therapy with tocainide for myotonia and paramyotonia congenita, as well as in myotonic dystrophy patients suffering from marked myotonic stiffness. ECG and 24-h ECG should be carefully recorded as necessary in any treatment with anti-arrhythmic drugs.

[Regression of left ventricular hypertophy in the ECG during antihypertensive treatment: preliminary observations (author's transl)].

PubMed

Manegold, C; Patzschke, U

1979-06-08

Typical signs of left ventricular hypertrophy (LVH) were present in the ECG of 36 (10 women, 26 men) of 127 persons with essential hypertension (46 women, 81 men). After a two-year course of combined drug treatment (chlortalidone, reserpine, methyl-dopa, hydralazine) with effective blood-pressure reduction LVH was still present in the ECG of 29, after a four-year course of only 15 among 36, i. e. a reduction in the presence of LVH of nearly 60%. Since the patients' body-weight remained unchanged during this period, the regression in ECG changes is ascribed to the effectiveness of the drug treatment.

Smart ECG Monitoring Patch with Built-in R-Peak Detection for Long-Term HRV Analysis.

PubMed

Lee, W K; Yoon, H; Park, K S

2016-07-01

Since heart rate variability (HRV) analysis is widely used to evaluate the physiological status of the human body, devices specifically designed for such applications are needed. To this end, we developed a smart electrocardiography (ECG) patch. The smart patch measures ECG using three electrodes integrated into the patch, filters the measured signals to minimize noise, performs analog-to-digital conversion, and detects R-peaks. The measured raw ECG data and the interval between the detected R-peaks can be recorded to enable long-term HRV analysis. Experiments were performed to evaluate the performance of the built-in R-wave detection, robustness of the device under motion, and applicability to the evaluation of mental stress. The R-peak detection results obtained with the device exhibited a sensitivity of 99.29%, a positive predictive value of 100.00%, and an error of 0.71%. The device also exhibited less motional noise than conventional ECG recording, being stable up to a walking speed of 5 km/h. When applied to mental stress analysis, the device evaluated the variation in HRV parameters in the same way as a normal ECG, with very little difference. This device can help users better understand their state of health and provide physicians with more reliable data for objective diagnosis.

A cancelable biometric scheme based on multi-lead ECGs.

PubMed

Peng-Tzu Chen; Shun-Chi Wu; Jui-Hsuan Hsieh

2017-07-01

Biometric technologies offer great advantages over other recognition methods, but there are concerns that they may compromise the privacy of individuals. In this paper, an electrocardiogram (ECG)-based cancelable biometric scheme is proposed to relieve such concerns. In this scheme, distinct biometric templates for a given beat bundle are constructed via "subspace collapsing." To determine the identity of any unknown beat bundle, the multiple signal classification (MUSIC) algorithm, incorporating a "suppression and poll" strategy, is adopted. Unlike the existing cancelable biometric schemes, knowledge of the distortion transform is not required for recognition. Experiments with real ECGs from 285 subjects are presented to illustrate the efficacy of the proposed scheme. The best recognition rate of 97.58 % was achieved under the test condition N train = 10 and N test = 10.

Four ECG left ventricular hypertrophy criteria and the risk of cardiovascular events and mortality in patients with vascular disease.

PubMed

van Kleef, Monique E A M; Visseren, Frank L J; Vernooij, Joris W P; Nathoe, Hendrik M; Cramer, Maarten-Jan M; Bemelmans, Remy H H; van der Graaf, Yolanda; Spiering, Wilko

2018-06-06

The relation between different electrocardiographic left ventricular hypertrophy (ECG-LVH) criteria and cardiovascular risk in patients with clinical manifest arterial disease is unclear. Therefore, we determined the association between four ECG-LVH criteria: Sokolow-Lyon, Cornell product, Cornell/strain index and Framingham criterion; and risk of cardiovascular events and mortality in this population. Risk of cardiovascular events was estimated in 6913 adult patients with clinical manifest arterial disease originating from the Secondary Manifestations of ARTerial disease (SMART) cohort. Cox proportional regression analysis was used to estimate the risk of the four ECG-LVH criteria and the primary composite outcome: myocardial infarction (MI), stroke or cardiovascular death; and secondary outcomes: MI, stroke and all-cause mortality; adjusted for confounders. The highest prevalence of ECG-LVH was observed for Cornell product (10%) and Cornell/strain index (9%). All four ECG-LVH criteria were associated with an increased risk of the primary composite endpoint: Sokolow-Lyon (hazard ratio 1.37, 95% CI 1.13-1.66), Cornell product (hazard ratio 1.54, 95% CI 1.30-1.82), Cornell/strain index (hazard ratio 1.70, 95% CI 1.44-2.00) and Framingham criterion (hazard ratio 1.78, 95% CI 1.21-2.62). Cornell product, Cornell/strain index and Framingham criterion ECG-LVH were additionally associated with an elevated risk of secondary outcomes. Cardiovascular risk increased whenever two, or three or more ECG-LVH criteria were present concurrently. All four ECG-LVH criteria are associated with an increased risk of cardiovascular events. As Cornell/strain index is both highly prevalent and carries a high cardiovascular risk, this is likely the most relevant ECG-LVH criterion for clinical practice.

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.

[Detection of Heart Rate of Fetal ECG Based on STFT and BSS].

PubMed

Wang, Xu; Cai, Kun

2016-01-01

Changes in heart rate of fetal is function regulating performance of the circulatory system and the central nervous system, it is significant to detect heart rate of fetus in perinatal fetal. This paper puts forward the fetal heart rate detection method based on short time Fourier transform and blind source separation. First of all, the mixed ECG signal was preprocessed, and then the wavelet transform technique was used to separate the fetal ECG signal with noise from mixed ECG signal, after that, the short-time Fourier transform and the blind separation were carried on it, and then calculated the correlation coefficient of it, Finally, An independent component that it has strongest correlation with the original signal was selected to make FECG peak detection and calculated the fetal instantaneous heart rate. The experimental results show that the method can improve the detection rate of the FECG peak (R), and it has high accuracy in fixing peak(R) location in the case of low signal-noise ratio.

Labview Based ECG Patient Monitoring System for Cardiovascular Patient Using SMTP Technology.

PubMed

Singh, Om Prakash; Mekonnen, Dawit; Malarvili, M B

2015-01-01

This paper leads to developing a Labview based ECG patient monitoring system for cardiovascular patient using Simple Mail Transfer Protocol technology. The designed device has been divided into three parts. First part is ECG amplifier circuit, built using instrumentation amplifier (AD620) followed by signal conditioning circuit with the operation amplifier (lm741). Secondly, the DAQ card is used to convert the analog signal into digital form for the further process. Furthermore, the data has been processed in Labview where the digital filter techniques have been implemented to remove the noise from the acquired signal. After processing, the algorithm was developed to calculate the heart rate and to analyze the arrhythmia condition. Finally, SMTP technology has been added in our work to make device more communicative and much more cost-effective solution in telemedicine technology which has been key-problem to realize the telediagnosis and monitoring of ECG signals. The technology also can be easily implemented over already existing Internet.

Labview Based ECG Patient Monitoring System for Cardiovascular Patient Using SMTP Technology

PubMed Central

Singh, Om Prakash; Mekonnen, Dawit; Malarvili, M. B.

2015-01-01

This paper leads to developing a Labview based ECG patient monitoring system for cardiovascular patient using Simple Mail Transfer Protocol technology. The designed device has been divided into three parts. First part is ECG amplifier circuit, built using instrumentation amplifier (AD620) followed by signal conditioning circuit with the operation amplifier (lm741). Secondly, the DAQ card is used to convert the analog signal into digital form for the further process. Furthermore, the data has been processed in Labview where the digital filter techniques have been implemented to remove the noise from the acquired signal. After processing, the algorithm was developed to calculate the heart rate and to analyze the arrhythmia condition. Finally, SMTP technology has been added in our work to make device more communicative and much more cost-effective solution in telemedicine technology which has been key-problem to realize the telediagnosis and monitoring of ECG signals. The technology also can be easily implemented over already existing Internet. PMID:27006940

Ultrasound measurement of the brachial artery flow-mediated dilation without ECG gating.

PubMed

Gemignani, Vincenzo; Bianchini, Elisabetta; Faita, Francesco; Giannarelli, Chiara; Plantinga, Yvonne; Ghiadoni, Lorenzo; Demi, Marcello

2008-03-01

The methods commonly used for noninvasive ultrasound assessment of endothelium-dependent flow-mediated dilation (FMD) require an electrocardiogram (ECG) signal to synchronize the measurements with the cardiac cycle. In this article, we present a method for assessing FMD that does not require ECG gating. The approach is based on temporal filtering of the diameter-time curve, which is obtained by means of a B-mode image processing system. The method was tested on 22 healthy volunteers without cardiovascular risk factors. The measurements obtained with the proposed approach were compared with those obtained with ECG gating and with both systolic and end-diastolic measurements. Results showed good agreement between the methods and a higher precision of the new method due to the fact that it is based on a larger number of measurements. Further advantages were also found both in terms of reliability of the measure and simplification of the instrumentation. (E-mail: gemi@ifc.cnr.it).

A New Strategy for ECG Baseline Wander Elimination Using Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Shahbakhti, Mohammad; Bagheri, Hamed; Shekarchi, Babak; Mohammadi, Somayeh; Naji, Mohsen

2016-06-01

Electrocardiogram (ECG) signals might be affected by various artifacts and noises that have biological and external sources. Baseline wander (BW) is a low-frequency artifact that may be caused by breathing, body movements and loose sensor contact. In this paper, a novel method based on empirical mode decomposition (EMD) for removal of baseline noise from ECG is presented. When compared to other EMD-based methods, the novelty of this research is to reach the optimized number of decomposed levels for ECG BW de-noising using mean power frequency (MPF), while the reduction of processing time is considered. To evaluate the performance of the proposed method, a fifth-order Butterworth high pass filtering (BHPF) with cut-off frequency at 0.5Hz and wavelet approach are applied. Three performance indices, signal-to-noise ratio (SNR), mean square error (MSE) and correlation coefficient (CC), between pure and filtered signals have been utilized for qualification of presented techniques. Results suggest that the EMD-based method outperforms the other filtering method.

Mobile cloud-computing-based healthcare service by noncontact ECG monitoring.

PubMed

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.

Multiple ECG Fiducial Points-Based Random Binary Sequence Generation for Securing Wireless Body Area Networks.

PubMed

Zheng, Guanglou; Fang, Gengfa; Shankaran, Rajan; Orgun, Mehmet A; Zhou, Jie; Qiao, Li; Saleem, Kashif

2017-05-01

Generating random binary sequences (BSes) is a fundamental requirement in cryptography. A BS is a sequence of N bits, and each bit has a value of 0 or 1. For securing sensors within wireless body area networks (WBANs), electrocardiogram (ECG)-based BS generation methods have been widely investigated in which interpulse intervals (IPIs) from each heartbeat cycle are processed to produce BSes. Using these IPI-based methods to generate a 128-bit BS in real time normally takes around half a minute. In order to improve the time efficiency of such methods, this paper presents an ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm. The technique of discrete wavelet transforms is employed to detect arrival time of these fiducial points, such as P, Q, R, S, and T peaks. Time intervals between them, including RR, RQ, RS, RP, and RT intervals, are then calculated based on this arrival time, and are used as ECG features to generate random BSes with low latency. According to our analysis on real ECG data, these ECG feature values exhibit the property of randomness and, thus, can be utilized to generate random BSes. Compared with the schemes that solely rely on IPIs to generate BSes, this MFBSG algorithm uses five feature values from one heart beat cycle, and can be up to five times faster than the solely IPI-based methods. So, it achieves a design goal of low latency. According to our analysis, the complexity of the algorithm is comparable to that of fast Fourier transforms. These randomly generated ECG BSes can be used as security keys for encryption or authentication in a WBAN system.

An optimized compression algorithm for real-time ECG data transmission in wireless network of medical information systems.

PubMed

Cho, Gyoun-Yon; Lee, Seo-Joon; Lee, Tae-Ro

2015-01-01

Recent medical information systems are striving towards real-time monitoring models to care patients anytime and anywhere through ECG signals. However, there are several limitations such as data distortion and limited bandwidth in wireless communications. In order to overcome such limitations, this research focuses on compression. Few researches have been made to develop a specialized compression algorithm for ECG data transmission in real-time monitoring wireless network. Not only that, recent researches' algorithm is not appropriate for ECG signals. Therefore this paper presents a more developed algorithm EDLZW for efficient ECG data transmission. Results actually showed that the EDLZW compression ratio was 8.66, which was a performance that was 4 times better than any other recent compression method widely used today.

Continuous control systems for non-contact ECG

NASA Astrophysics Data System (ADS)

Kodkin, Vladimir L.; Yakovleva, Galina V.; Smirnov, Alexey S.

2017-03-01

South Ural State University is still conducting the research work dedicated to innovations in biomedicine. Development of system for continuous control and diagnosis of the functional state in large groups of people is based on studies of non-contact ECG recording reported by the authors at the SPIE conference in 2016. The next stage of studies has been performed this year.

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…

The intracavitary ECG method for positioning the tip of central venous access devices in pediatric patients: results of an Italian multicenter study.

PubMed

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.

Automated detection of heart ailments from 12-lead ECG using complex wavelet sub-band bi-spectrum features.

PubMed

Tripathy, Rajesh Kumar; Dandapat, Samarendra

2017-04-01

The complex wavelet sub-band bi-spectrum (CWSB) features are proposed for detection and classification of myocardial infarction (MI), heart muscle disease (HMD) and bundle branch block (BBB) from 12-lead ECG. The dual tree CW transform of 12-lead ECG produces CW coefficients at different sub-bands. The higher-order CW analysis is used for evaluation of CWSB. The mean of the absolute value of CWSB, and the number of negative phase angle and the number of positive phase angle features from the phase of CWSB of 12-lead ECG are evaluated. Extreme learning machine and support vector machine (SVM) classifiers are used to evaluate the performance of CWSB features. Experimental results show that the proposed CWSB features of 12-lead ECG and the SVM classifier are successful for classification of various heart pathologies. The individual accuracy values for MI, HMD and BBB classes are obtained as 98.37, 97.39 and 96.40%, respectively, using SVM classifier and radial basis function kernel function. A comparison has also been made with existing 12-lead ECG-based cardiac disease detection techniques.

Automated detection of heart ailments from 12-lead ECG using complex wavelet sub-band bi-spectrum features

PubMed Central

Dandapat, Samarendra

2017-01-01

The complex wavelet sub-band bi-spectrum (CWSB) features are proposed for detection and classification of myocardial infarction (MI), heart muscle disease (HMD) and bundle branch block (BBB) from 12-lead ECG. The dual tree CW transform of 12-lead ECG produces CW coefficients at different sub-bands. The higher-order CW analysis is used for evaluation of CWSB. The mean of the absolute value of CWSB, and the number of negative phase angle and the number of positive phase angle features from the phase of CWSB of 12-lead ECG are evaluated. Extreme learning machine and support vector machine (SVM) classifiers are used to evaluate the performance of CWSB features. Experimental results show that the proposed CWSB features of 12-lead ECG and the SVM classifier are successful for classification of various heart pathologies. The individual accuracy values for MI, HMD and BBB classes are obtained as 98.37, 97.39 and 96.40%, respectively, using SVM classifier and radial basis function kernel function. A comparison has also been made with existing 12-lead ECG-based cardiac disease detection techniques. PMID:28894589

Ischemic ECG abnormalities are associated with an increased risk for death among subjects with COPD, also among those without known heart disease.

PubMed

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.

ECG-ViEW II, a freely accessible electrocardiogram database

PubMed Central

Park, Man Young; Lee, Sukhoon; Jeon, Min Seok; Yoon, Dukyong; Park, Rae Woong

2017-01-01

The Electrocardiogram Vigilance with Electronic data Warehouse II (ECG-ViEW II) is a large, single-center database comprising numeric parameter data of the surface electrocardiograms of all patients who underwent testing from 1 June 1994 to 31 July 2013. The electrocardiographic data include the test date, clinical department, RR interval, PR interval, QRS duration, QT interval, QTc interval, P axis, QRS axis, and T axis. These data are connected with patient age, sex, ethnicity, comorbidities, age-adjusted Charlson comorbidity index, prescribed drugs, and electrolyte levels. This longitudinal observational database contains 979,273 electrocardiograms from 461,178 patients over a 19-year study period. This database can provide an opportunity to study electrocardiographic changes caused by medications, disease, or other demographic variables. ECG-ViEW II is freely available at http://www.ecgview.org. PMID:28437484

Surface ECG and Fluoroscopy are Not Predictive of Right Ventricular Septal Lead Position Compared to Cardiac CT.

PubMed

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.

Inter-lead correlation analysis for automated detection of cable reversals in 12/16-lead ECG.

PubMed

Jekova, Irena; Krasteva, Vessela; Leber, Remo; Schmid, Ramun; Twerenbold, Raphael; Müller, Christian; Reichlin, Tobias; Abächerli, Roger

2016-10-01

A crucial factor for proper electrocardiogram (ECG) interpretation is the correct electrode placement in standard 12-lead ECG and extended 16-lead ECG for accurate diagnosis of acute myocardial infarctions. In the context of optimal patient care, we present and evaluate a new method for automated detection of reversals in peripheral and precordial (standard, right and posterior) leads, based on simple rules with inter-lead correlation dependencies. The algorithm for analysis of cable reversals relies on scoring of inter-lead correlations estimated over 4s snapshots with time-coherent data from multiple ECG leads. Peripheral cable reversals are detected by assessment of nine correlation coefficients, comparing V6 to limb leads: (I, II, III, -I, -II, -III, -aVR, -aVL, -aVF). Precordial lead reversals are detected by analysis of the ECG pattern cross-correlation progression within lead sets (V1-V6), (V4R, V3R, V3, V4), and (V4, V5, V6, V8, V9). Disturbed progression identifies the swapped leads. A test-set, including 2239 ECGs from three independent sources-public 12-lead (PTB, CSE) and proprietary 16-lead (Basel University Hospital) databases-is used for algorithm validation, reporting specificity (Sp) and sensitivity (Se) as true negative and true positive detection of simulated lead swaps. Reversals of limb leads are detected with Se = 95.5-96.9% and 100% when right leg is involved in the reversal. Among all 15 possible pairwise reversals in standard precordial leads, adjacent lead reversals are detected with Se = 93.8% (V5-V6), 95.6% (V2-V3), 95.9% (V3-V4), 97.1% (V1-V2), and 97.8% (V4-V5), increasing to 97.8-99.8% for reversals of anatomically more distant electrodes. The pairwise reversals in the four extra precordial leads are detected with Se = 74.7% (right-sided V4R-V3R), 91.4% (posterior V8-V9), 93.7% (V4R-V9), and 97.7% (V4R-V8, V3R-V9, V3R-V8). Higher true negative rate is achieved with Sp > 99% (standard 12-lead ECG), 81.9% (V4R-V3R), 91

Intersubject variability and intrasubject reproducibility of 12-lead ECG metrics: Implications for human verification.

PubMed

Jekova, Irena; Krasteva, Vessela; Leber, Remo; Schmid, Ramun; Twerenbold, Raphael; Müller, Christian; Reichlin, Tobias; Abächerli, Roger

Electrocardiogram (ECG) biometrics is an advanced technology, not yet covered by guidelines on criteria, features and leads for maximal authentication accuracy. This study aims to define the minimal set of morphological metrics in 12-lead ECG by optimization towards high reliability and security, and validation in a person verification model across a large population. A standard 12-lead resting ECG database from 574 non-cardiac patients with two remote recordings (>1year apart) was used. A commercial ECG analysis module (Schiller AG) measured 202 morphological features, including lead-specific amplitudes, durations, ST-metrics, and axes. Coefficient of variation (CV, intersubject variability) and percent-mean-absolute-difference (PMAD, intrasubject reproducibility) defined the optimization (PMAD/CV→min) and restriction (CV<30%) criteria for selection of the most stable and distinctive features. Linear discriminant analysis (LDA) validated the non-redundant feature set for person verification. Maximal LDA verification sensitivity (85.3%) and specificity (86.4%) were validated for 11 optimal features: R-amplitude (I,II,V1,V2,V3,V5), S-amplitude (V1,V2), Tnegative-amplitude (aVR), and R-duration (aVF,V1). Copyright © 2016 Elsevier Inc. All rights reserved.

Construction and Use of Resting 12-Lead High Fidelity ECG "SuperScores" in Screening for Heart Disease

NASA Technical Reports Server (NTRS)

Schlegel, T. T.; Arenare, B.; Greco, E. C.; DePalma, J. L.; Starc, V.; Nunez, T.; Medina, R.; Jugo, D.; Rahman, M.A.; Delgado, R.

2007-01-01

We investigated the accuracy of several conventional and advanced resting ECG parameters for identifying obstructive coronary artery disease (CAD) and cardiomyopathy (CM). Advanced high-fidelity 12-lead ECG tests (approx. 5-min supine) were first performed on a "training set" of 99 individuals: 33 with ischemic or dilated CM and low ejection fraction (EF less than 40%); 33 with catheterization-proven obstructive CAD but normal EF; and 33 age-/gender-matched healthy controls. Multiple conventional and advanced ECG parameters were studied for their individual and combined retrospective accuracies in detecting underlying disease, the advanced parameters falling within the following categories: 1) Signal averaged ECG, including 12-lead high frequency QRS (150-250 Hz) plus multiple filtered and unfiltered parameters from the derived Frank leads; 2) 12-lead P, QRS and T-wave morphology via singular value decomposition (SVD) plus signal averaging; 3) Multichannel (12-lead, derived Frank lead, SVD lead) beat-to-beat QT interval variability; 4) Spatial ventricular gradient (and gradient component) variability; and 5) Heart rate variability. Several multiparameter ECG SuperScores were derivable, using stepwise and then generalized additive logistic modeling, that each had 100% retrospective accuracy in detecting underlying CM or CAD. The performance of these same SuperScores was then prospectively evaluated using a test set of another 120 individuals (40 new individuals in each of the CM, CAD and control groups, respectively). All 12-lead ECG SuperScores retrospectively generated for CM continued to perform well in prospectively identifying CM (i.e., areas under the ROC curve greater than 0.95), with one such score (containing just 4 components) maintaining 100% prospective accuracy. SuperScores retrospectively generated for CAD performed somewhat less accurately, with prospective areas under the ROC curve typically in the 0.90-0.95 range. We conclude that resting 12-lead

Treatment with eCG decreases the vascular density and increases the glandular density of the bovine uterus.

PubMed

Mona e Pinto, J; Pavanelo, V; Alves de Fátima, L; Medeiros de Carvalho Sousa, L M; Pacheco Mendes, G; Machado Ferreira, R; Ayres, H; Sampaio Baruselli, P; Palma Rennó, F; de Carvallo Papa, P

2014-06-01

The uterus plays an essential role in mammalian reproduction and is a target of several hormonal protocols used to improve fertility in cattle. Many studies highlighted the importance of eCG treatment following fixed-time artificial insemination in improving follicular growth, ovulation and pregnancy rates in cattle. Moreover, eCG has been implicated in angiogenesis, leading to important changes in uterine blood flow and vascularisation. However, there is still a lack of information regarding the specific alterations induced by eCG upon glandular and vascular characteristics of bovine uterus. To investigate the influence of eCG on: uterine thickness and area; uterine artery diameter and area; uterine vascular and gland density; and the expression of the VEGFA-system, the uteri of crossbred beef cows were collected. All cows were submitted to follicular wave emergence synchronization. On day four of protocol, cows submitted to superovulation (n = 6) received 2000 IU eCG, on day eight, after expected follicular deviation, cows submitted to stimulatory treatment (n = 5) received 400 IU eCG. Control cows (n = 5) did not receive eCG. On day five po cows were subjected to ultrassonographic evaluation and slaughtered for uterine tissue sampling on day six po. Uterine vessels and glands were quantified by the counting point stereological method. The VEGFA-system was localized in different cellular types, showing no qualitative or quantitative differences in the site of expression or the intensity of the positive signal among the groups. Vascular density was decreased in the endometrium of stimulated and myometrium of superovulated cows compared with the control ones, which showed higher vascular density in the myometrium and endometrium of the ipsilateral uterine horn. The uterine gland density was higher in superovulated compared with stimulated and control cows. Thus, we can infer that stimulatory or superovulatory treatments with eCG influence the vascular

Are 12-lead ECG findings associated with the risk of cardiovascular events after ischemic stroke in young adults?

PubMed

Pirinen, Jani; Putaala, Jukka; Aarnio, Karoliina; Aro, Aapo L; Sinisalo, Juha; Kaste, Markku; Haapaniemi, Elena; Tatlisumak, Turgut; Lehto, Mika

2016-11-01

Ischemic stroke (IS) in a young patient is a disaster and recurrent cardiovascular events could add further impairment. Identifying patients with high risk of such events is therefore important. The prognostic relevance of ECG for this population is unknown. A total of 690 IS patients aged 15-49 years were included. A 12-lead ECG was obtained 1-14 d after the onset of stroke. We adjusted for demographic factors, comorbidities, and stroke characteristics, Cox regression models were used to identify independent ECG parameters associated with long-term risks of (1) any cardiovascular event, (2) cardiac events, and (3) recurrent stroke. Median follow-up time was 8.8 years. About 26.4% of patients experienced a cardiovascular event, 14.5% had cardiac events, and 14.6% recurrent strokes. ECG parameters associated with recurrent cardiovascular events were bundle branch blocks, P-terminal force, left ventricular hypertrophy, and a broader QRS complex. Furthermore, more leftward P-wave axis, prolonged QTc, and P-wave duration >120 ms were associated with increased risks of cardiac events. No ECG parameters were independently associated with recurrent stroke. A 12-lead ECG can be used for risk prediction of cardiovascular events but not for recurrent stroke in young IS patients. KEY MESSAGES ECG is an easy, inexpensive, and useful tool for identifying young ischemic stroke patients with a high risk for recurrent cardiovascular events and it has a statistically significant association with these events even after adjusting for confounding factors. Bundle branch blocks, P-terminal force, broader QRS complex, LVH according to Cornell voltage duration criteria, more leftward P-wave axis, prolonged QTc, and P-wave duration >120 ms are predictors for future cardiovascular or cardiac events in these patients. No ECG parameters were independently associated with recurrent stroke.

Measurement of ECG abnormalities and cardiovascular risk classification: a cohort study of primary care patients in the Netherlands

PubMed Central

Groot, Anne; Bots, Michiel L; Rutten, Frans H; den Ruijter, Hester M; Numans, Mattijs E; Vaartjes, Ilonca

2015-01-01

Background GPs need accurate tools for cardiovascular (CV) risk assessment. Abnormalities in resting electrocardiograms (ECGs) relate to increased CV risk. Aim To determine whether measurement of ECG abnormalities on top of established risk estimation (SCORE) improves CV risk classification in a primary care population. Design and setting A cohort study of patients enlisted with academic general practices in the Netherlands (the Utrecht Health Project [UHP]). Method Incident CV events were extracted from the GP records. MEANS algorithm was used to assess ECG abnormalities. Cox proportional hazards modelling was applied to relate ECG abnormalities to CV events. For a prediction model only with SCORE variables, and a model with SCORE+ECG abnormalities, the discriminative value (area under the receiver operator curve [AUC]) and the net reclassification improvement (NRI) were estimated. Results A total of 2370 participants aged 38–74 years were included, all eligible for CV risk assessment. During a mean follow-up of 7.8 years, 172 CV events occurred. In 19% of the participants at least one ECG abnormality was found (Lausanne criteria). Presence of atrial fibrillation/flutter (AF) and myocardial infarction (MI) were significantly related to CV events. The AUC of the SCORE risk factors was 0.75 (95% CI = 0.71 to 0.79). Addition of MI or AF resulted in an AUC of 0.76 (95% CI = 0.72 to 0.79) and 0.75 (95% CI = 0.72 to 0.79), respectively. The NRI with the addition of ECG abnormalities was small (MI 1.0%; 95% CI = −3.2% to 6.9%; AF 0.5%; 95% CI = −3.5% to 3.3%). Conclusion Performing a resting ECG in a primary care population does not seem to improve risk classification when SCORE information — age, sex, smoking, systolic blood pressure, and total cholesterol/HDL ratio — is already available. PMID:25548311

Measurement of ECG abnormalities and cardiovascular risk classification: a cohort study of primary care patients in the Netherlands.

PubMed

Groot, Anne; Bots, Michiel L; Rutten, Frans H; den Ruijter, Hester M; Numans, Mattijs E; Vaartjes, Ilonca

2015-01-01

GPs need accurate tools for cardiovascular (CV) risk assessment. Abnormalities in resting electrocardiograms (ECGs) relate to increased CV risk. To determine whether measurement of ECG abnormalities on top of established risk estimation (SCORE) improves CV risk classification in a primary care population. A cohort study of patients enlisted with academic general practices in the Netherlands (the Utrecht Health Project [UHP]). Incident CV events were extracted from the GP records. MEANS algorithm was used to assess ECG abnormalities. Cox proportional hazards modelling was applied to relate ECG abnormalities to CV events. For a prediction model only with SCORE variables, and a model with SCORE+ECG abnormalities, the discriminative value (area under the receiver operator curve [AUC]) and the net reclassification improvement (NRI) were estimated. A total of 2370 participants aged 38-74 years were included, all eligible for CV risk assessment. During a mean follow-up of 7.8 years, 172 CV events occurred. In 19% of the participants at least one ECG abnormality was found (Lausanne criteria). Presence of atrial fibrillation/flutter (AF) and myocardial infarction (MI) were significantly related to CV events. The AUC of the SCORE risk factors was 0.75 (95% CI = 0.71 to 0.79). Addition of MI or AF resulted in an AUC of 0.76 (95% CI = 0.72 to 0.79) and 0.75 (95% CI = 0.72 to 0.79), respectively. The NRI with the addition of ECG abnormalities was small (MI 1.0%; 95% CI = -3.2% to 6.9%; AF 0.5%; 95% CI = -3.5% to 3.3%). Performing a resting ECG in a primary care population does not seem to improve risk classification when SCORE information - age, sex, smoking, systolic blood pressure, and total cholesterol/HDL ratio - is already available. © British Journal of General Practice 2015.

ECG CHANGES AFTER X-RAY IRRADIATION OF THE HEART REGION (in German)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gral, T.; Gral, J.

1963-03-01

The problem of radioinduced damage of the myocardium after irradiation of the heart region for mammary carcinoma or intrathoracic tumors is discussed. Analysis of patient material, including 34 cases with mammary carcinomas on the left side and 14 cases with intrathoracic tumors, showed considerable ECG-changes (ECG = electrocardiogram) in 18 and in 6 cases, respectively. Because of these results, it is assumed that damage of the myocardium caused by irradiation is possible during tangential irradiation of mammary carcinomas on the left side. This could be of importance in the future wellbeing of the patients. (auth)

Design of a wearable device for ECG continuous monitoring using wireless technology.

PubMed

Led, Santiago; Fernández, Jorge; Serrano, Luis

2004-01-01

This project focuses on the design and implementation of an intelligent wearable device for ECG continuous acquisition and transmission to some remote gateway using Bluetooth technology. The acquisition device has been designed for having very low power consumption and reduced size. The Analog Devices' ADuC831 Micro-Converter for achieving the analog to digital conversion and the CSR's BlueCore2 chip for the Bluetooth transmission are the core of the device. The designed device is an important component of a complete prototype for remote ECG continuous monitoring of patients with diverse cardiac diseases.

Adaptive Fourier decomposition based R-peak detection for noisy ECG Signals.

PubMed

Ze Wang; Chi Man Wong; Feng Wan

2017-07-01

An adaptive Fourier decomposition (AFD) based R-peak detection method is proposed for noisy ECG signals. Although lots of QRS detection methods have been proposed in literature, most detection methods require high signal quality. The proposed method extracts the R waves from the energy domain using the AFD and determines the R-peak locations based on the key decomposition parameters, achieving the denoising and the R-peak detection at the same time. Validated by clinical ECG signals in the MIT-BIH Arrhythmia Database, the proposed method shows better performance than the Pan-Tompkin (PT) algorithm in both situations of a native PT and the PT with a denoising process.

High Resolution ECG for Evaluation of Heart Function During Exposure to Subacute Hypobaric Hypoxia

NASA Technical Reports Server (NTRS)

Zupet, Petra; Finderle, Zarko; Schlegel, Todd T.; Princi, Tanja; Starc, Vito

2010-01-01

High altitude climbing presents a wide spectrum of health risks, including exposure to hypobaric hypoxia. Risks are also typically exacerbated by the difficulty in appropriately monitoring for early signs of organ dysfunction in remote areas. We investigated whether high resolution advanced ECG analysis might be helpful as a non-invasive and easy-to-use tool (e.g., instead of Doppler echocardiography) for evaluating early signs of heart overload in hypobaric hypoxia. Nine non-acclimatized healthy trained alpine rescuers (age 43.7 plus or minus 7.3 years) climbed in four days to the altitude of 4,200 m on Mount Ararat. Five-minute high-resolution 12-lead electrocardiograms (ECGs) were recorded (Cardiosoft) in each subject at rest in the supine position on different days but at the same time of day at four different altitudes: 400 m (reference altitude), 1,700 m, 3,200 m and 4,200 m. Changes in conventional and advanced resting ECG parameters, including in beat-to-beat QT and RR variability, waveform complexity, signal-averaged, high-frequency and spatial/spatiotemporal ECG was estimated by calculation of the regression coefficients in independent linear regression models. A p-value of less than 0.05 was adopted as statistically significant. As expected, the RR interval and its variability both decreased with increasing altitude, with trends k = -96 ms/1000 m with p = 0.000 and k = -9 ms/1000 m with p = 0.001, respectively. Significant changes were found in P-wave amplitude, which nearly doubled from the lowest to the highest altitude (k = 41.6 microvolt/1000 m with p = 0.000), and nearly significant changes in P-wave duration (k = 2.9 ms/1000 m with p = 0.059). Changes were less significant or non-significant in other studied parameters including those of waveform complexity, signal-averaged, high-frequency and spatial/spatiotemporal ECG. High resolution ECG analysis, particularly of the P wave, shows promise as a tool for monitoring early changes in heart function

New system for digital to analog transformation and reconstruction of 12-lead ECGs.

PubMed

Kothadia, Roshni; Kulecz, Walter B; Kofman, Igor S; Black, Adam J; Grier, James W; Schlegel, Todd T

2013-01-01

We describe initial validation of a new system for digital to analog conversion (DAC) and reconstruction of 12-lead ECGs. The system utilizes an open and optimized software format with a commensurately optimized DAC hardware configuration to accurately reproduce, from digital files, the original analog electrocardiographic signals of previously instrumented patients. By doing so, the system also ultimately allows for transmission of data collected on one manufacturer's 12-lead ECG hardware/software into that of any other. To initially validate the system, we compared original and post-DAC re-digitized 12-lead ECG data files (∼5-minutes long) in two types of validation studies in 10 patients. The first type quantitatively compared the total waveform voltage differences between the original and re-digitized data while the second type qualitatively compared the automated electrocardiographic diagnostic statements generated by the original versus re-digitized data. The grand-averaged difference in root mean squared voltage between the original and re-digitized data was 20.8 µV per channel when re-digitization involved the same manufacturer's analog to digital converter (ADC) as the original digitization, and 28.4 µV per channel when it involved a different manufacturer's ADC. Automated diagnostic statements generated by the original versus reconstructed data did not differ when using the diagnostic algorithm from the same manufacturer on whose device the original data were collected, and differed only slightly for just 1 of 10 patients when using a third-party diagnostic algorithm throughout. Original analog 12-lead ECG signals can be reconstructed from digital data files with accuracy sufficient for clinical use. Such reconstructions can readily enable automated second opinions for difficult-to-interpret 12-lead ECGs, either locally or remotely through the use of dedicated or cloud-based servers.

New System for Digital to Analog Transformation and Reconstruction of 12-Lead ECGs

PubMed Central

Kothadia, Roshni; Kulecz, Walter B.; Kofman, Igor S.; Black, Adam J.; Grier, James W.; Schlegel, Todd T.

2013-01-01

Introduction We describe initial validation of a new system for digital to analog conversion (DAC) and reconstruction of 12-lead ECGs. The system utilizes an open and optimized software format with a commensurately optimized DAC hardware configuration to accurately reproduce, from digital files, the original analog electrocardiographic signals of previously instrumented patients. By doing so, the system also ultimately allows for transmission of data collected on one manufacturer's 12-lead ECG hardware/software into that of any other. Materials and Methods To initially validate the system, we compared original and post-DAC re-digitized 12-lead ECG data files (∼5-minutes long) in two types of validation studies in 10 patients. The first type quantitatively compared the total waveform voltage differences between the original and re-digitized data while the second type qualitatively compared the automated electrocardiographic diagnostic statements generated by the original versus re-digitized data. Results The grand-averaged difference in root mean squared voltage between the original and re-digitized data was 20.8 µV per channel when re-digitization involved the same manufacturer's analog to digital converter (ADC) as the original digitization, and 28.4 µV per channel when it involved a different manufacturer's ADC. Automated diagnostic statements generated by the original versus reconstructed data did not differ when using the diagnostic algorithm from the same manufacturer on whose device the original data were collected, and differed only slightly for just 1 of 10 patients when using a third-party diagnostic algorithm throughout. Conclusion Original analog 12-lead ECG signals can be reconstructed from digital data files with accuracy sufficient for clinical use. Such reconstructions can readily enable automated second opinions for difficult-to-interpret 12-lead ECGs, either locally or remotely through the use of dedicated or cloud-based servers. PMID:23613787

The evolution of ambulatory ECG monitoring.

PubMed

Kennedy, Harold L

2013-01-01

Ambulatory Holter electrocardiographic (ECG) monitoring has undergone continuous technological evolution since its invention and development in the 1950s era. With commercial introduction in 1963, there has been an evolution of Holter recorders from 1 channel to 12 channel recorders with increasingly smaller storage media, and there has evolved Holter analysis systems employing increasingly technologically advanced electronics providing a myriad of data displays. This evolution of smaller physical instruments with increasing technological capacity has characterized the development of electronics over the past 50 years. Currently the technology has been focused upon the conventional continuous 24 to 48 hour ambulatory ECG examination, and conventional extended ambulatory monitoring strategies for infrequent to rare arrhythmic events. However, the emergence of the Internet, Wi-Fi, cellular networks, and broad-band transmission has positioned these modalities at the doorway of the digital world. This has led to an adoption of more cost-effective strategies to these conventional methods of performing the examination. As a result, the emergence of the mobile smartphone coupled with this digital capacity is leading to the recent development of Holter smartphone applications. The potential of point-of-care applications utilizing the Holter smartphone and a vast array of new non-invasive sensors is evident in the not too distant future. The Holter smartphone is anticipated to contribute significantly in the future to the field of global health. © 2013.

ECG-based gating in ultra high field cardiovascular magnetic resonance using an independent component analysis approach.

PubMed

Krug, Johannes W; Rose, Georg; Clifford, Gari D; Oster, Julien

2013-11-19

In Cardiovascular Magnetic Resonance (CMR), the synchronization of image acquisition with heart motion is performed in clinical practice by processing the electrocardiogram (ECG). The ECG-based synchronization is well established for MR scanners with magnetic fields up to 3 T. However, this technique is prone to errors in ultra high field environments, e.g. in 7 T MR scanners as used in research applications. The high magnetic fields cause severe magnetohydrodynamic (MHD) effects which disturb the ECG signal. Image synchronization is thus less reliable and yields artefacts in CMR images. A strategy based on Independent Component Analysis (ICA) was pursued in this work to enhance the ECG contribution and attenuate the MHD effect. ICA was applied to 12-lead ECG signals recorded inside a 7 T MR scanner. An automatic source identification procedure was proposed to identify an independent component (IC) dominated by the ECG signal. The identified IC was then used for detecting the R-peaks. The presented ICA-based method was compared to other R-peak detection methods using 1) the raw ECG signal, 2) the raw vectorcardiogram (VCG), 3) the state-of-the-art gating technique based on the VCG, 4) an updated version of the VCG-based approach and 5) the ICA of the VCG. ECG signals from eight volunteers were recorded inside the MR scanner. Recordings with an overall length of 87 min accounting for 5457 QRS complexes were available for the analysis. The records were divided into a training and a test dataset. In terms of R-peak detection within the test dataset, the proposed ICA-based algorithm achieved a detection performance with an average sensitivity (Se) of 99.2%, a positive predictive value (+P) of 99.1%, with an average trigger delay and jitter of 5.8 ms and 5.0 ms, respectively. Long term stability of the demixing matrix was shown based on two measurements of the same subject, each being separated by one year, whereas an averaged detection performance of Se = 99.4% and +P

Spatiotemporal Characteristics of QRS Complexes Enable the Diagnosis of Brugada Syndrome Regardless of the Appearance of a Type 1 ECG.

PubMed

Guillem, Maria S; Climent, Andreu M; Millet, José; Berne, Paola; Ramos, Rafael; Brugada, Josep; Brugada, Ramon

2016-05-01

The diagnosis of Brugada syndrome based on the ECG is hampered by the dynamic nature of its ECG manifestations. Brugada syndrome patients are only 25% likely to present a type 1 ECG. The objective of this study is to provide an ECG diagnostic criterion for Brugada syndrome patients that can be applied consistently even in the absence of a type 1 ECG. We recorded 67-lead body surface potential maps from 94 Brugada syndrome patients and 82 controls (including right bundle branch block patients and healthy individuals). The spatial propagation direction during the last r' wave and the slope at the end of the QRS complex were measured and compared between patients groups. Receiver-operating characteristic curves were constructed for half of the database to identify optimal cutoff values; sensitivity and specificity for these cutoff values were measured in the other half of the database. A spontaneous type 1 ECG was present in only 30% of BrS patients. An orientation in the sagittal plane < 101º during the last r' wave and a descending slope < 9.65 mV/s enables the diagnosis of the syndrome with a sensitivity of 69% and a specificity of 97% in non-type 1 Brugada syndrome patients. Spatiotemporal characteristics of surface ECG recordings can enable a robust identification of BrS even without the presence of a type 1 ECG. © 2016 Wiley Periodicals, Inc.

Reproductive performance of seasonally anovular mixed-bred dairy goats induced to ovulate with a combination of progesterone and eCG or estradiol.

PubMed

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.

Underestimated and unreported prolonged QTc by automated ECG analysis in patients on methadone: can we rely on computer reading?

PubMed

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.

Reliability of Left Ventricular Hypertrophy by ECG Criteria in Children with Syncope: Do the Criteria Need to be Revised?

PubMed

Banerjee, Maalika M; Ramesh Iyer, V; Nandi, Deipanjan; Vetter, Victoria L; Banerjee, Anirban

2016-04-01

In the outpatient setting, children who present with syncope routinely undergo electrocardiograms (ECG). Because of concerns for hypertrophic cardiomyopathy, children with syncope meeting ECG criteria for left ventricular hypertrophy (LVH) will frequently undergo an echocardiogram. Our objectives were to determine whether Davignon criteria for ECG waves overestimate LVH in children presenting with syncope, and to study the usefulness of echocardiography in these children. We hypothesize that the Davignon criteria presently used for interpretation of ECGs overestimate LVH, resulting in unnecessary echocardiography in this clinical setting. The clinical database of The Children's Hospital of Philadelphia was evaluated from 2002 to 2012 to identify children between 9 and 16 years of age, who presented with non-exercise-induced, isolated syncope. From this group of patients, only those with clear-cut evidence of LVH (by Davignon criteria), who also underwent an echocardiogram, were selected. A total of 136 children with syncope were identified as having LVH by Davignon ECG criteria. None of these patients manifested any evidence of hypertrophic cardiomyopathy, with normal ventricular septum (average Z-score -0.68 ± 0.84), LV posterior wall (average Z-score -0.66 ± 1.18) and LV mass (average Z-score 0.52 ± 1.29). No significant correlation was found between summed RV6 plus SV1 and LV mass. Correlations between additional ECG parameters and measures of LVH by echocardiography were similarly poor. In children presenting with syncope and LVH by ECG, there was no evidence of true LVH by echocardiography. We propose that the Davignon ECG criteria for interpreting LVH in children overestimate the degree of hypertrophy in these children and the yield of echocardiography is extremely low.

Graphite Based Electrode for ECG Monitoring: Evaluation under Freshwater and Saltwater Conditions.

PubMed

Thap, Tharoeun; Yoon, Kwon-Ha; Lee, Jinseok

2016-04-15

We proposed new electrodes that are applicable for electrocardiogram (ECG) monitoring under freshwater- and saltwater-immersion conditions. Our proposed electrodes are made of graphite pencil lead (GPL), a general-purpose writing pencil. We have fabricated two types of electrode: a pencil lead solid type (PLS) electrode and a pencil lead powder type (PLP) electrode. In order to assess the qualities of the PLS and PLP electrodes, we compared their performance with that of a commercial Ag/AgCl electrode, under a total of seven different conditions: dry, freshwater immersion with/without movement, post-freshwater wet condition, saltwater immersion with/without movement, and post-saltwater wet condition. In both dry and post-freshwater wet conditions, all ECG-recorded PQRST waves were clearly discernible, with all types of electrodes, Ag/AgCl, PLS, and PLP. On the other hand, under the freshwater- and saltwater-immersion conditions with/without movement, as well as post-saltwater wet conditions, we found that the proposed PLS and PLP electrodes provided better ECG waveform quality, with significant statistical differences compared with the quality provided by Ag/AgCl electrodes.

Closed-Loop Control of Humidification for Artifact Reduction in Capacitive ECG Measurements.

PubMed

Leicht, Lennart; Eilebrecht, Benjamin; Weyer, Soren; Leonhardt, Steffen; Teichmann, Daniel

2017-04-01

Recording biosignals without the need for direct skin contact offers new opportunities for ubiquitous health monitoring. Electrodes with capacitive coupling have been shown to be suitable for the monitoring of electrical potentials on the body surface, in particular ECG. However, due to triboelectric charge generation and motion artifacts, signal and thus diagnostic quality is inferior to galvanic coupling. Active closed-loop humidification of capacitive electrodes is proposed in this work as a new concept to improve signal quality. A capacitive ECG recording system integrated into a common car seat is presented. It can regulate the micro climate at the interface of electrode and patient by actively dispensing water vapour and monitoring humidity in a closed-loop approach. As a regenerative water reservoir, silica gel is used. The system was evaluated with respect to subjective and objective ECG signal quality. Active humidification was found to have a significant positive effect in case of previously poor quality. Also, it had no diminishing effect in case of already good signal quality.

Investigating the effect of traditional Persian music on ECG signals in young women using wavelet transform and neural networks.

PubMed

Abedi, Behzad; Abbasi, Ataollah; Goshvarpour, Atefeh

2017-05-01

In the past few decades, several studies have reported the physiological effects of listening to music. The physiological effects of different music types on different people are different. In the present study, we aimed to examine the effects of listening to traditional Persian music on electrocardiogram (ECG) signals in young women. Twenty-two healthy females participated in this study. ECG signals were recorded under two conditions: rest and music. For each ECG signal, 20 morphological and wavelet-based features were selected. Artificial neural network (ANN) and probabilistic neural network (PNN) classifiers were used for the classification of ECG signals during and before listening to music. Collected data were separated into two data sets: train and test. Classification accuracies of 88% and 97% were achieved in train data sets using ANN and PNN, respectively. In addition, the test data set was employed for evaluating the classifiers, and classification rates of 84% and 93% were obtained using ANN and PNN, respectively. The present study investigated the effect of music on ECG signals based on wavelet transform and morphological features. The results obtained here can provide a good understanding on the effects of music on ECG signals to researchers.

Residual motion compensation in ECG-gated interventional cardiac vasculature reconstruction

NASA Astrophysics Data System (ADS)

Schwemmer, C.; Rohkohl, C.; Lauritsch, G.; Müller, K.; Hornegger, J.

2013-06-01

Three-dimensional reconstruction of cardiac vasculature from angiographic C-arm CT (rotational angiography) data is a major challenge. Motion artefacts corrupt image quality, reducing usability for diagnosis and guidance. Many state-of-the-art approaches depend on retrospective ECG-gating of projection data for image reconstruction. A trade-off has to be made regarding the size of the ECG-gating window. A large temporal window is desirable to avoid undersampling. However, residual motion will occur in a large window, causing motion artefacts. We present an algorithm to correct for residual motion. Our approach is based on a deformable 2D-2D registration between the forward projection of an initial, ECG-gated reconstruction, and the original projection data. The approach is fully automatic and does not require any complex segmentation of vasculature, or landmarks. The estimated motion is compensated for during the backprojection step of a subsequent reconstruction. We evaluated the method using the publicly available CAVAREV platform and on six human clinical datasets. We found a better visibility of structure, reduced motion artefacts, and increased sharpness of the vessels in the compensated reconstructions compared to the initial reconstructions. At the time of writing, our algorithm outperforms the leading result of the CAVAREV ranking list. For the clinical datasets, we found an average reduction of motion artefacts by 13 ± 6%. Vessel sharpness was improved by 25 ± 12% on average.

Mobile Cloud-Computing-Based Healthcare Service by Noncontact ECG Monitoring

PubMed Central

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

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals.

PubMed

Hwang, Bosun; You, Jiwoo; Vaessen, Thomas; Myin-Germeys, Inez; Park, Cheolsoo; Zhang, Byoung-Tak

2018-02-08

Stress recognition using electrocardiogram (ECG) signals requires the intractable long-term heart rate variability (HRV) parameter extraction process. This study proposes a novel deep learning framework to recognize the stressful states, the Deep ECGNet, using ultra short-term raw ECG signals without any feature engineering methods. The Deep ECGNet was developed through various experiments and analysis of ECG waveforms. We proposed the optimal recurrent and convolutional neural networks architecture, and also the optimal convolution filter length (related to the P, Q, R, S, and T wave durations of ECG) and pooling length (related to the heart beat period) based on the optimization experiments and analysis on the waveform characteristics of ECG signals. The experiments were also conducted with conventional methods using HRV parameters and frequency features as a benchmark test. The data used in this study were obtained from Kwangwoon University in Korea (13 subjects, Case 1) and KU Leuven University in Belgium (9 subjects, Case 2). Experiments were designed according to various experimental protocols to elicit stressful conditions. The proposed framework to recognize stress conditions, the Deep ECGNet, outperformed the conventional approaches with the highest accuracy of 87.39% for Case 1 and 73.96% for Case 2, respectively, that is, 16.22% and 10.98% improvements compared with those of the conventional HRV method. We proposed an optimal deep learning architecture and its parameters for stress recognition, and the theoretical consideration on how to design the deep learning structure based on the periodic patterns of the raw ECG data. Experimental results in this study have proved that the proposed deep learning model, the Deep ECGNet, is an optimal structure to recognize the stress conditions using ultra short-term ECG data.

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.

Patient ECG recording control for an automatic implantable defibrillator

NASA Technical Reports Server (NTRS)

Fountain, Glen H. (Inventor); Lee, Jr., David G. (Inventor); Kitchin, David A. (Inventor)

1986-01-01

An implantable automatic defibrillator includes sensors which are placed on or near the patient's heart to detect electrical signals indicative of the physiology of the heart. The signals are digitally converted and stored into a FIFO region of a RAM by operation of a direct memory access (DMA) controller. The DMA controller operates transparently with respect to the microprocessor which is part of the defibrillator. The implantable defibrillator includes a telemetry communications circuit for sending data outbound from the defibrillator to an external device (either a patient controller or a physician's console or other) and a receiver for sensing at least an externally generated patient ECG recording command signal. The patient recording command signal is generated by the hand held patient controller. Upon detection of the patient ECG recording command, DMA copies the contents of the FIFO into a specific region of the RAM.

Analyzing Thorough QT Study 1 & 2 in the Telemetric and Holter ECG Warehouse (THEW) using Hannover ECG System HES : A validation study.

PubMed

Khawaja, A; Petrovic, R; Safer, A; Baas, T; Dössel, O; Fischer, R

2010-01-01

Following the ICH E14 clinical evaluation guideline [1], the measurement of QT/QTc interval prolongation has become the standard surrogate biomarker for cardiac drug safety assessment and the faith of a drug development. In Thorough QT (TQT) study, a so-called positive control is employed to assess the ability of this study to detect the endpoint of interest, i.e. the QT prolongation by about five milliseconds. In other words the lower bound of the one-sided 95% confidence interval (CI) must be above 0 [ms]. Fully automated detection of ECG fiducial points and measurement of the corresponding intervals including QT intervals and RR intervals vary between different computerized algorithms. In this work we demonstrate the ability and reliability of Hannover ECG System (HES(®)) to assess drug effects by detecting QT/QTc prolongation effects that meet the threshold of regulatory concern as mentioned by using THEW database studies namely TQT studies one and two.

Electrical performance of PEDOT:PSS-based textile electrodes for wearable ECG monitoring: a comparative study.

PubMed

Castrillón, Reinel; Pérez, Jairo J; Andrade-Caicedo, Henry

2018-04-02

Wearable textile electrodes for the detection of biopotentials are a promising tool for the monitoring and early diagnosis of chronic diseases. We present a comparative study of the electrical characteristics of four textile electrodes manufactured from common fabrics treated with a conductive polymer, a commercial fabric, and disposable Ag/AgCl electrodes. These characteristics will allow identifying the performance of the materials when used as ECG electrodes. The electrodes were subjected to different electrical tests, and complemented with conductivity calculations and microscopic images to determine their feasibility in the detection of ECG signals. We evaluated four electrical characteristics: contact impedance, electrode polarization, noise, and long-term performance. We analyzed PEDOT:PSS treated fabrics based on cotton, cotton-polyester, lycra and polyester; also a commercial fabric made of silver-plated nylon Shielde® Med-Tex P130, and commercial Ag/AgCl electrodes. We calculated conductivity from the surface resistance and, analyzed their surface at a microscopic level. Rwizard was used in the statistical analysis. The results showed that textile electrodes treated with PEDOT:PSS are suitable for the detection of ECG signals. The error detecting features of the ECG signal was lower than 2% and the electrodes kept working properly after 36 h of continuous use. Even though the contact impedance and the polarization level in textile electrodes were greater than in commercial electrodes, these parameters did not affect the acquisition of the ECG signals. Fabrics conductivity calculations were consistent to the contact impedance.

A miniature on-chip multi-functional ECG signal processor with 30 µW ultra-low power consumption.

PubMed

Liu, Xin; Zheng, Yuan Jin; Phyu, Myint Wai; Zhao, Bin; Je, Minkyu; Yuan, Xiao Jun

2010-01-01

In this paper, a miniature low-power Electrocardiogram (ECG) signal processing application specific integrated circuit (ASIC) chip is proposed. This chip provides multiple critical functions for ECG analysis using a systematic wavelet transform algorithm and a novel SRAM-based ASIC architecture, while achieves low cost and high performance. Using 0.18 µm CMOS technology and 1 V power supply, this ASIC chip consumes only 29 µW and occupies an area of 3 mm(2). This on-chip ECG processor is highly suitable for reliable real-time cardiac status monitoring applications.

The Application of Root Mean Square Electrocardiography (RMS ECG) for the Detection of Acquired and Congenital Long QT Syndrome

PubMed Central

Lux, Robert L.; Sower, Christopher Todd; Allen, Nancy; Etheridge, Susan P.; Tristani-Firouzi, Martin; Saarel, Elizabeth V.

2014-01-01

Background Precise measurement of the QT interval is often hampered by difficulty determining the end of the low amplitude T wave. Root mean square electrocardiography (RMS ECG) provides a novel alternative measure of ventricular repolarization. Experimental data have shown that the interval between the RMS ECG QRS and T wave peaks (RTPK) closely reflects the mean ventricular action potential duration while the RMS T wave width (TW) tracks the dispersion of repolarization timing. Here, we tested the precision of RMS ECG to assess ventricular repolarization in humans in the setting of drug-induced and congenital Long QT Syndrome (LQTS). Methods RMS ECG signals were derived from high-resolution 24 hour Holter monitor recordings from 68 subjects after receiving placebo and moxifloxacin and from standard 12 lead ECGs obtained in 97 subjects with LQTS and 97 age- and sex-matched controls. RTPK, QTRMS and RMS TW intervals were automatically measured using custom software and compared to traditional QT measures using lead II. Results All measures of repolarization were prolonged during moxifloxacin administration and in LQTS subjects, but the variance of RMS intervals was significantly smaller than traditional lead II measurements. TW was prolonged during moxifloxacin and in subjects with LQT-2, but not LQT-1 or LQT-3. Conclusion These data validate the application of RMS ECG for the detection of drug-induced and congenital LQTS. RMS ECG measurements are more precise than the current standard of care lead II measurements. PMID:24454918

The application of root mean square electrocardiography (RMS ECG) for the detection of acquired and congenital long QT syndrome.

PubMed

Lux, Robert L; Sower, Christopher Todd; Allen, Nancy; Etheridge, Susan P; Tristani-Firouzi, Martin; Saarel, Elizabeth V

2014-01-01

Precise measurement of the QT interval is often hampered by difficulty determining the end of the low amplitude T wave. Root mean square electrocardiography (RMS ECG) provides a novel alternative measure of ventricular repolarization. Experimental data have shown that the interval between the RMS ECG QRS and T wave peaks (RTPK) closely reflects the mean ventricular action potential duration while the RMS T wave width (TW) tracks the dispersion of repolarization timing. Here, we tested the precision of RMS ECG to assess ventricular repolarization in humans in the setting of drug-induced and congenital Long QT Syndrome (LQTS). RMS ECG signals were derived from high-resolution 24 hour Holter monitor recordings from 68 subjects after receiving placebo and moxifloxacin and from standard 12 lead ECGs obtained in 97 subjects with LQTS and 97 age- and sex-matched controls. RTPK, QTRMS and RMS TW intervals were automatically measured using custom software and compared to traditional QT measures using lead II. All measures of repolarization were prolonged during moxifloxacin administration and in LQTS subjects, but the variance of RMS intervals was significantly smaller than traditional lead II measurements. TW was prolonged during moxifloxacin and in subjects with LQT-2, but not LQT-1 or LQT-3. These data validate the application of RMS ECG for the detection of drug-induced and congenital LQTS. RMS ECG measurements are more precise than the current standard of care lead II measurements.

Physical examination and ECG screening in relation to echocardiography findings in young healthy adults.

PubMed

Landau, Dan-Avi; Grossman, Alon; Sherer, Yaniv; Harpaz, David; Azaria, Bella; Carter, Dan; Barenboim, Erez; Goldstein, Liav

2008-01-01

Cardiovascular screening in young adults is an important tool in many occupational settings. Our aim was to test whether screening physical examination and ECG influence the rate of abnormal echocardiogarphic findings in young healthy subjects. Consecutive echocardiography results of 18- to 20-year-old flight candidates were analyzed retrospectively. Echocardiographies were performed as part of a screening protocol, which includes ECG, physical examination and referral for echocardiography for any positive finding. A second stage includes universal echocardiography for all candidates. 1,066 subjects were evaluated; 489 subjects underwent echocardiography following referral because of abnormal auscultatory or ECG findings. Findings (mostly mild valvular insufficiencies) were demonstrated in 12.7%, with only 0.6% of subjects disqualified. In subjects who underwent universal echocardiography (n = 577), findings (mostly mild valvular insufficiencies) were detected in 18%, with only 0.5% of subjects disqualified. The rate of significant echocardiography findings is extremely low in this young and healthy population. The presence of abnormal findings on either physical examination or ECG screening was not demonstrated to alter the rate of abnormal echocardiographic findings. We suggest that the low yield of screening should be weighed against the cost of an unidentified congenital cardiac lesion in the specific setting. Copyright 2007 S. Karger AG, Basel.

Evaluation of heart rate variability indices using a real-time handheld remote ECG monitor.

PubMed

Singh, Swaroop S; Carlson, Barbara W; Hsiao, Henry S

2007-12-01

Studies on retrospective electrocardiogram (ECG) recordings of patients during cardiac arrest have shown significant changes in heart rate variability (HRV) indices prior to the onset of cardiac arrhythmia. The early detection of these changes in HRV indices increases the chances for a successful medical intervention by increasing the response time window. A portable, handheld remote ECG monitor designed in this research detects the QRS complex and calculates short-term HRV indices in real-time. The QRS detection of the ECG recordings of subjects from the MIT-Arrhythmia database yielded a mean sensitivity of 99.34% and a specificity of 99.31%. ECG recordings from normal subjects and subjects with congestive heart failure were used to identify the differences in HRV indices. An increase in heart rate, high-frequency spectral power (HFP), total spectral power, the ratio of HFP to low-frequency spectral power (LFP), and a decrease in root mean square sum of RR differences were observed. No difference was found on comparison of the standard deviation of normal to normal interval between adjacent R-waves, LFP, and very-low-frequency spectral power. Based on these, additional analytical calculations could be made to provide early warnings of impending cardiac conditions.

Tc-99m Glu-Cys-Gly-His-Gly-Lys (ECG-HGK), a novel Tc-99m labeled hexapeptide for molecular tumor imaging.

PubMed

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.

Smartphone ECG for evaluation of ST-segment elevation myocardial infarction (STEMI): Design of the ST LEUIS International Multicenter Study.

PubMed

Barbagelata, Alejandro; Bethea, Charles F; Severance, Harry W; Mentz, Robert J; Albert, David; Barsness, Gregory W; Le, Viet T; Anderson, Jeffrey L; Bunch, T Jared; Yanowitz, Frank; Chisum, Benjamin; Ronnow, Brianna S; Muhlestein, Joseph B

In patients experiencing an ST-elevation myocardial infarction (STEMI), rapid diagnosis and immediate access to reperfusion therapy leads to optimal clinical outcomes. The rate-limiting step in STEMI diagnosis is the availability and performance of a 12-lead ECG. Recent technology has provided access to a reliable means of obtaining an ECG reading through a smartphone application (app) that works with an attachment providing all 12-leads of a standard ECG system. The ST LEUIS study was designed to validate the smartphone ECG app and its ability to accurately assess the presence or absence of STEMI in patients presenting with chest pain compared with the gold standard 12-lead ECG. We aimed to support the diagnostic utility of smartphone technology to provide a timely diagnosis and treatment of STEMI. The study will take place over 12months at five institutions. Approximately 60 patients will be enrolled per institution, for a total recruitment of 300 patients. Copyright © 2017 Elsevier Inc. All rights reserved.

A markup language for electrocardiogram data acquisition and analysis (ecgML)

PubMed Central

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

Smart Helmet: Wearable Multichannel ECG and EEG

PubMed Central

Chanwimalueang, Theerasak; Goverdovsky, Valentin; Looney, David; Sharp, David; Mandic, Danilo P.

2016-01-01

Modern wearable technologies have enabled continuous recording of vital signs, however, for activities such as cycling, motor-racing, or military engagement, a helmet with embedded sensors would provide maximum convenience and the opportunity to monitor simultaneously both the vital signs and the electroencephalogram (EEG). To this end, we investigate the feasibility of recording the electrocardiogram (ECG), respiration, and EEG from face-lead locations, by embedding multiple electrodes within a standard helmet. The electrode positions are at the lower jaw, mastoids, and forehead, while for validation purposes a respiration belt around the thorax and a reference ECG from the chest serve as ground truth to assess the performance. The within-helmet EEG is verified by exposing the subjects to periodic visual and auditory stimuli and screening the recordings for the steady-state evoked potentials in response to these stimuli. Cycling and walking are chosen as real-world activities to illustrate how to deal with the so-induced irregular motion artifacts, which contaminate the recordings. We also propose a multivariate R-peak detection algorithm suitable for such noisy environments. Recordings in real-world scenarios support a proof of concept of the feasibility of recording vital signs and EEG from the proposed smart helmet. PMID:27957405

Evaluation of Digital Compressed Sensing for Real-Time Wireless ECG System with Bluetooth low Energy.

PubMed

Wang, Yishan; Doleschel, Sammy; Wunderlich, Ralf; Heinen, Stefan

2016-07-01

In this paper, a wearable and wireless ECG system is firstly designed with Bluetooth Low Energy (BLE). It can detect 3-lead ECG signals and is completely wireless. Secondly the digital Compressed Sensing (CS) is implemented to increase the energy efficiency of wireless ECG sensor. Different sparsifying basis, various compression ratio (CR) and several reconstruction algorithms are simulated and discussed. Finally the reconstruction is done by the android application (App) on smartphone to display the signal in real time. The power efficiency is measured and compared with the system without CS. The optimum satisfying basis built by 3-level decomposed db4 wavelet coefficients, 1-bit Bernoulli random matrix and the most suitable reconstruction algorithm are selected by the simulations and applied on the sensor node and App. The signal is successfully reconstructed and displayed on the App of smartphone. Battery life of sensor node is extended from 55 h to 67 h. The presented wireless ECG system with CS can significantly extend the battery life by 22 %. With the compact characteristic and long term working time, the system provides a feasible solution for the long term homecare utilization.

Telemetry-assisted early detection of STEMI in patients with atypical symptoms by paramedic-performed 12-lead ECG with subsequent cardiological analysis.

PubMed

Campo Dell' Orto, Marco; Hamm, Christian; Liebetrau, Christoph; Hempel, Dorothea; Merbs, Reinhold; Cuca, Colleen; Breitkreutz, Raoul

2017-08-01

ECG is an essential diagnostic tool in patients with acute coronary syndrome. We aimed to determine how many patients presenting with atypical symptoms for an acute myocardial infarction show ST-segment elevations on prehospital ECG. We also aimed to study the feasibility of telemetric-assisted prehospital ECG analysis. Between April 2010 and February 2011, consecutive emergency patients presenting with atypical symptoms such as nausea, vomiting, atypical chest pain, palpitations, hypertension, syncope, or dizziness were included in the study. After basic measures were completed, a 12-lead ECG was written and telemetrically transmitted to the cardiac center, where it was analyzed by attending physicians. Any identification of an ST-elevation myocardial infarction resulted in patient admission at the closest coronary angiography facility. A total of 313 emergency patients presented with the following symptoms: dyspnea, nausea, vomiting, dizziness/collapse, or acute hypertension. Thirty-four (11%) patients of this cohort were found to show ST-segment elevations on the 12-lead ECG. These patients were directly admitted to the closest coronary catheterization facility rather than the closest hospital. The time required for transmission and analysis of the ECG was 3.6±1.2 min. Telemetry-assisted 12-lead ECG analysis in a prehospital setting may lead to earlier detection of ST-elevation myocardial infarction in patients with atypical symptoms. Thus, a 12-lead ECG should be considered in all prehospital patients both with typical and atypical symptoms.

The Zigbee wireless ECG measurement system design with a motion artifact remove algorithm by using adaptive filter and moving weighted factor

NASA Astrophysics Data System (ADS)

Kwon, Hyeokjun; Oh, Sechang; Varadan, Vijay K.

2012-04-01

The Electrocardiogram(ECG) signal is one of the bio-signals to check body status. Traditionally, the ECG signal was checked in the hospital. In these days, as the number of people who is interesting with periodic their health check increase, the requirement of self-diagnosis system development is being increased as well. Ubiquitous concept is one of the solutions of the self-diagnosis system. Zigbee wireless sensor network concept is a suitable technology to satisfy the ubiquitous concept. In measuring ECG signal, there are several kinds of methods in attaching electrode on the body called as Lead I, II, III, etc. In addition, several noise components occurred by different measurement situation such as experimenter's respiration, sensor's contact point movement, and the wire movement attached on sensor are included in pure ECG signal. Therefore, this paper is based on the two kinds of development concept. The first is the Zibee wireless communication technology, which can provide convenience and simpleness, and the second is motion artifact remove algorithm, which can detect clear ECG signal from measurement subject. The motion artifact created by measurement subject's movement or even respiration action influences to distort ECG signal, and the frequency distribution of the noises is around from 0.2Hz to even 30Hz. The frequencies are duplicated in actual ECG signal frequency, so it is impossible to remove the artifact without any distortion of ECG signal just by using low-pass filter or high-pass filter. The suggested algorithm in this paper has two kinds of main parts to extract clear ECG signal from measured original signal through an electrode. The first part is to extract motion noise signal from measured signal, and the second part is to extract clear ECG by using extracted motion noise signal and measured original signal. The paper suggests several techniques in order to extract motion noise signal such as predictability estimation theory, low pass filter

ECG strain pattern in hypertension is associated with myocardial cellular expansion and diffuse interstitial fibrosis: a multi-parametric cardiac magnetic resonance study

PubMed Central

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

ECG strain pattern in hypertension is associated with myocardial cellular expansion and diffuse interstitial fibrosis: a multi-parametric cardiac magnetic resonance study.

PubMed

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

Development and validation of a novel algorithm based on the ECG magnet response for rapid identification of any unknown pacemaker.

PubMed

Squara, Fabien; Chik, William W; Benhayon, Daniel; Maeda, Shingo; Latcu, Decebal Gabriel; Lacaze-Gadonneix, Jonathan; Tibi, Thierry; Thomas, Olivier; Cooper, Joshua M; Duthoit, Guillaume

2014-08-01

Pacemaker (PM) interrogation requires correct manufacturer identification. However, an unidentified PM is a frequent occurrence, requiring time-consuming steps to identify the device. The purpose of this study was to develop and validate a novel algorithm for PM manufacturer identification, using the ECG response to magnet application. Data on the magnet responses of all recent PM models (≤15 years) from the 5 major manufacturers were collected. An algorithm based on the ECG response to magnet application to identify the PM manufacturer was subsequently developed. Patients undergoing ECG during magnet application in various clinical situations were prospectively recruited in 7 centers. The algorithm was applied in the analysis of every ECG by a cardiologist blinded to PM information. A second blinded cardiologist analyzed a sample of randomly selected ECGs in order to assess the reproducibility of the results. A total of 250 ECGs were analyzed during magnet application. The algorithm led to the correct single manufacturer choice in 242 ECGs (96.8%), whereas 7 (2.8%) could only be narrowed to either 1 of 2 manufacturer possibilities. Only 2 (0.4%) incorrect manufacturer identifications occurred. The algorithm identified Medtronic and Sorin Group PMs with 100% sensitivity and specificity, Biotronik PMs with 100% sensitivity and 99.5% specificity, and St. Jude and Boston Scientific PMs with 92% sensitivity and 100% specificity. The results were reproducible between the 2 blinded cardiologists with 92% concordant findings. Unknown PM manufacturers can be accurately identified by analyzing the ECG magnet response using this newly developed algorithm. Copyright © 2014 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

PubMed

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.

Improving ECG Competence in Medical Trainees in a UK District General Hospital

PubMed Central

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

Fetal ECG extraction from abdominal signals: a review on suppression of fundamental power line interference component and its harmonics.

PubMed

Ţarălungă, Dragoş-Daniel; Ungureanu, Georgeta-Mihaela; Gussi, Ilinca; Strungaru, Rodica; Wolf, Werner

2014-01-01

Interference of power line (PLI) (fundamental frequency and its harmonics) is usually present in biopotential measurements. Despite all countermeasures, the PLI still corrupts physiological signals, for example, electromyograms (EMG), electroencephalograms (EEG), and electrocardiograms (ECG). When analyzing the fetal ECG (fECG) recorded on the maternal abdomen, the PLI represents a particular strong noise component, being sometimes 10 times greater than the fECG signal, and thus impairing the extraction of any useful information regarding the fetal health state. Many signal processing methods for cancelling the PLI from biopotentials are available in the literature. In this review study, six different principles are analyzed and discussed, and their performance is evaluated on simulated data (three different scenarios), based on five quantitative performance indices.

Fetal ECG Extraction from Abdominal Signals: A Review on Suppression of Fundamental Power Line Interference Component and Its Harmonics

PubMed Central

Ţarălungă, Dragoş-Daniel; Ungureanu, Georgeta-Mihaela; Gussi, Ilinca; Strungaru, Rodica; Wolf, Werner

2014-01-01

Interference of power line (PLI) (fundamental frequency and its harmonics) is usually present in biopotential measurements. Despite all countermeasures, the PLI still corrupts physiological signals, for example, electromyograms (EMG), electroencephalograms (EEG), and electrocardiograms (ECG). When analyzing the fetal ECG (fECG) recorded on the maternal abdomen, the PLI represents a particular strong noise component, being sometimes 10 times greater than the fECG signal, and thus impairing the extraction of any useful information regarding the fetal health state. Many signal processing methods for cancelling the PLI from biopotentials are available in the literature. In this review study, six different principles are analyzed and discussed, and their performance is evaluated on simulated data (three different scenarios), based on five quantitative performance indices. PMID:24660020

An ultra-low power (ULP) bandage-type ECG sensor for efficient cardiac disease management.

PubMed

Shin, Kunsoo; Park, G G; Kim, J P; Lee, T H; Ko, B H; Kim, Y H

2013-01-01

This paper proposed an ultra-low power bandage-type ECG sensor (the size: 76 × 34 × 3 (mm(3)) and the power consumption: 1 mW) which allows for a continuous and real-time monitoring of a user's ECG signals over 24h during daily activities. For its compact size and lower power consumption, we designed the analog front-end, the SRP (Samsung Reconfigurable Processor) based DSP of 30 uW/MHz, and the ULP wireless RF of 1 nJ/bit. Also, to tackle motion artifacts(MA), a MA monitoring technique based on the HCP (Half-cell Potential) is proposed which resulted in the high correlation between the MA and the HCP, the correlation coefficient of 0.75 ± 0.18. To assess its feasibility and validity as a wearable health monitor, we performed the comparison of two ECG signals recorded form it and a conventional Holter device. As a result, the performance of the former is a little lower as compared with the latter, although showing no statistical significant difference (the quality of the signal: 94.3% vs 99.4%; the accuracy of arrhythmia detection: 93.7% vs 98.7%). With those results, it has been confirmed that it can be used as a wearable health monitor due to its comfortability, its long operation lifetime and the good quality of the measured ECG signal.

Accuracy of ECG indices for diagnosis of left ventricular hypertrophy in people >65 years: results from the ActiFE study.

PubMed

Laszlo, Roman; Kunz, Katia; Dallmeier, Dhayana; Klenk, Jochen; Denkinger, Michael; Koenig, Wolfgang; Rothenbacher, Dietrich; Steinacker, Juergen Michael

2017-10-01

The detection of left ventricular hypertrophy (LVH) is still a common objective of electrocardiography (ECG) in clinical practice. The aim of our study was to evaluate the accuracy of LVH ECG indices in people older than 65 recruited from a population-based cohort (ActiFE-Ulm study). In 432 subjects (mean age 76.2 ± 5.5 years, 51% male), left ventricular mass was echocardiographically determined (Devereux formula) and indexed (LVMI) to body surface area. Several LVH ECG indices (Lewis voltage, Gubner-Ungerleider voltage, Sokolow-Lyon voltage/product, Cornell voltage/product) were calculated with the help of resting ECG data and compared with the echocardiographic assessment. Despite echocardiographic signs of LVH [LVMI > 115 (♂) or >95 g/m 2 (♀)] in 47.5% of all subjects, diagnostic performance of all ECG indices was generally low. Magnitude of all LVH-indices was mainly predicted by frontal QRS axis in multivariate linear regression analysis. In comparison with the literature data from younger subjects, average frontal QRS axis turned counterclockwise. Most probably, age-related counterclockwise turn of frontal QRS axis is mainly explanatory for the decreased magnitude of LVH ECG indices and consecutive worse diagnostic performance of these indices in the elderly. ECG indices for detection of LVH have insufficient predictive values in geriatric subjects and should therefore not be used clinically for this purpose. Nevertheless, due to its established relevancy in cardiac risk stratification in this age group, usage of some established ECG indices might keep its significance even in the age of modern cardiac imaging.

e-Learning versus lecture-based courses in ECG interpretation for undergraduate medical students: a randomized noninferiority study.

PubMed

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.

Trigger learning and ECG parameter customization for remote cardiac clinical care information system.

PubMed

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.

Predictable and reliable ECG monitoring over IEEE 802.11 WLANs within a hospital.

PubMed

Park, Juyoung; Kang, Kyungtae

2014-09-01

Telecardiology provides mobility for patients who require constant electrocardiogram (ECG) monitoring. However, its safety is dependent on the predictability and robustness of data delivery, which must overcome errors in the wireless channel through which the ECG data are transmitted. We report here a framework that can be used to gauge the applicability of IEEE 802.11 wireless local area network (WLAN) technology to ECG monitoring systems in terms of delay constraints and transmission reliability. For this purpose, a medical-grade WLAN architecture achieved predictable delay through the combination of a medium access control mechanism based on the point coordination function provided by IEEE 802.11 and an error control scheme based on Reed-Solomon coding and block interleaving. The size of the jitter buffer needed was determined by this architecture to avoid service dropout caused by buffer underrun, through analysis of variations in transmission delay. Finally, we assessed this architecture in terms of service latency and reliability by modeling the transmission of uncompressed two-lead electrocardiogram data from the MIT-BIH Arrhythmia Database and highlight the applicability of this wireless technology to telecardiology.

Pseudoaneurysm of the thoracic aorta sustained during exposure to a tornado diagnosed with ECG-synchronized CT aortography.

PubMed

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.

The De Winter ECG pattern: morphology and accuracy for diagnosing acute coronary occlusion: systematic review.

PubMed

Morris, Niall P; Body, Richard

2017-08-01

The De Winter ECG pattern has been reported to indicate acute left anterior descending coronary artery occlusion and is often considered to be an 'ST elevation myocardial infarction (STEMI) equivalent'. We aimed to investigate the morphology of the 'De Winter ECG pattern' and evaluate the test characteristics of the De Winter pattern for the diagnosis of acute coronary occlusion. We identified papers through the Medline, EMBASE and COCHRANE databases and screened for bias using QUADAS-2. First, measurements were recorded from every ECG reported in the literature and aggregated. Second, diagnostic accuracy data from eligible cohort studies were extracted. The primary outcome was defined as at least 70% angiographic stenosis of a major epicardial vessel. Thirteen papers reported data relevant to question 1 and three papers reported data relevant to question 2. All ECGs showed maximal up-sloping ST depression in lead V3 with a median amplitude of 0.3 mV (interquartile range: 0.2-4 mV). T-wave height peaked in lead V3 with a median amplitude 0.9 mV (interquartile range: 0.8-1.1 mV). The De Winter pattern had positive predictive values of 95.2% (95% confidence interval: 76.2-99.9%), 100% (69.2-100.0%) and 100% (51.7-100%) in the three respective diagnostic studies. There is limited evidence that the De Winter ECG pattern is a 'STEMI equivalent'. The available data suggest that the pattern has high positive predictive value for acute occlusion. Further research is required to evaluate specificity and to determine whether rapid revascularization improves mortality.

Capillaroscopy and ECG parameters in children and adolescents with diabetes mellitus type I.

PubMed

Chakhunashvili, G; Jobava, N; Chakhunashvili, K; Shvangiradze, M; Chakhunashvili, D; Pagava, K

2012-09-01

Evaluate ECG parameters and detect changes in capillaroscopy parameters in children and adolescents with Diabetes mellitus type 1 (DMT1). ECG and capillaroscopy were performed in 32 children and adolescents (6-15 years old, 17 boys,15 girls) with DMT1. Disease duration - less than 2 years -13, 2-4 years - 10, 5-10 years - 9 cases. The patients were divided into two groups: I group - 12 patients with no complications of DMT1 (in all them duration of disease was less than 2 years), II group - 20 patients with diagnosed cardiac complications of DMT1 (diabetic cardiomyopathy, angiopathy). Additionally 6 of them had diabetic encephalopathy , 4 - diabetic encephalopathy and peripheral neuropathy, 4 - nephropathy and retinal antipathy. Level of glycosides hemoglobin was 8-11%, level of glucose 4 to 15 mmole/L. Control group included 20 healthy children of the same age. In group I ECG is less informative. Hypertrophies of left ventricle and atrium and disorders of repolarization were mainly found in group II. In 62.5% of cases rhythm and conduction disorders were revealed, which were more often in group II. Capillaroscopy changes (pale and cyanotic background, decreasing of the number of capillaries in sight, dilated and contracted diameter, pathological shape and order of capillaries, slow blood flow) were seen both in I and II groups with more prevalence and intensity in the latter one. In children and adolescents with Diabetes mellitus type 1 ECG and capillaroscopy should be performed on the regular basis in order to reveal early changes and start the appropriate treatment in time.

An Autonomous Wireless Sensor Node With Asynchronous ECG Monitoring in 0.18 μ m CMOS.

PubMed

Mansano, Andre L; Li, Yongjia; Bagga, Sumit; Serdijn, Wouter A

2016-06-01

The design of a 13.56 MHz/402 MHz autonomous wireless sensor node with asynchronous ECG monitoring for near field communication is presented. The sensor node consists of an RF energy harvester (RFEH), a power management unit, an ECG readout, a data encoder and an RF backscattering transmitter. The energy harvester supplies the system with 1.25 V and offers a power conversion efficiency of 19% from a -13 dBm RF source at 13.56 MHz. The power management unit regulates the output voltage of the RFEH to supply the ECG readout with VECG = 0.95 V and the data encoder with VDE = 0.65 V . The ECG readout comprises an analog front-end (low noise amplifier and programmable voltage to current converter) and an asynchronous level crossing ADC with 8 bits resolution. The ADC output is encoded by a pulse generator that drives a backscattering transmitter at 402 MHz. The total power consumption of the sensor node circuitry is 9.7 μ W for a data rate of 90 kb/s and a heart rate of 70 bpm. The chip has been designed in a 0.18 μm CMOS process and shows superior RF input power sensitivity and lower power consumption when compared to previous works.

Food and Insulin Effect on QT/QTC Interval of ECG

ClinicalTrials.gov

2014-08-19

Effects of Different Meals on the QT/QTc Interval; Insulin and Oral Hypoglycemic [Antidiabetic] Drugs Causing Adverse Effects in Therapeutic Use; C-Peptide Effects on the QT/QTc Interval; Moxifloxacin ECG Profile in Fed and Fasted State; Japanese vs. Caucasian TQT Comparison

Discussion of "Computational Electrocardiography: Revisiting Holter ECG Monitoring".

PubMed

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.

Feasibility and cost-effectiveness of stroke prevention through community screening for atrial fibrillation using iPhone ECG in pharmacies. The SEARCH-AF study.

PubMed

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.

Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2s of ECG signals.

PubMed

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.

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

[Dynamics of ECG voltage in changing gravity].

PubMed

Saltykova, M M; At'kov, O Iu; Capderou, A; Morgun, V V; Gusakov, V A; Kheĭmets, G I; Konovalov, G A; Kondratiuk, L L; Kataev, Iu V; Voronin, L I; Kaspranskiĭ, R R; Vaida, P

2006-01-01

Comparative analysis of the QRS voltage response to gravity variations was made using the data about 26 normal human subjects collected in parabolic flights (CNERS-AIRBUS A300 Zero-G, n=23; IL-76MD, n=3) and during the tilt test (head-up tilt at 70 degrees for a min and head-down tilt at-15 degrees for 5 min, n=14). Both the parabolic flights and provocative tilt tests affected R-amplitude in the Z lead. During the hypergravity episodes it was observed in 95% of cases with the mean gain of 16% and maximal--56%. On transition to the horizontal position, the Rz-amplitude showed a rise in each subject (16% on the average). In microgravity, the Rz-amplitude reduced in 95% of the observations. The voltage decline averaged 18% and reached 49% at the maximum. The head-down tilt was conducive to Rz reduction in 78% of observations averaging 2%. Analysis of the ECG records under changing gravity when blood redistribution developed within few seconds not enough for serious metabolic shifts still revealed QRS deviations associated exclusively with the physical factors, i.e., alteration in tissue conduction and distance to electrodes. Our findings can stand in good stead in evaluation of the dynamics of predictive ECG parameters during long-term experiments leading to changes as in tissue conduction, so metabolism.

ECG-gated imaging of the left atrium and pulmonary veins: Intra-individual comparison of CTA and MRA.

PubMed

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.

Effects of cuff inflation and deflation on pulse transit time measured from ECG and multi-wavelength PPG.

PubMed

Liu, Jing; Li, Yao; Ding, Xiao-Rong; Dai, Wen-Xuan; Zhang, Yuan-Ting

2015-01-01

Pulse transit time (PTT), which refers to the time it takes a pulse wave to travel between two arterial sites is a promising index for cuff-less blood pressure (BP) estimation, as well as non-invasive assessment of arterial functions. However, it has not been investigated whether PTTs measured from ECG and different wavelength PPG are equally affected by the arterial status. Furthermore, comparison between the changes of different PTTs can provide enlightenment on the hardware implementation of the PTT-based BP estimation method. This work mainly studied the changes of PTTs calculated from electrocardiogram (ECG) and multi-wavelength photoplethysmogram (PPG) after exerting cuff pressure on the upper arm. A four-channel PPG acquisition system was developed to collect the multi-wavelength PPG signals of red, yellow, green and blue light at the fingertip simultaneously. Ten subjects participated in the experiment and their PTTs measured from different PPG and ECG signals before and after exerting cuff pressure were compared. This study found that within one minute after the four-minute cuff inflation and deflation process, the PTT measured from ECG and yellow PPG experienced a significant increase (p<;0.05) while the PTT from ECG and blue PPG had no statistical difference (p>0.9) compared with that before exerting cuff pressure. This indicates that PTTs calculated from different wavelength PPG have different recoverability from smooth muscle relaxation. Another interesting finding is that the PTT calculated from ECG and yellow PPG had a strong correlation (|r|>0.7) with the time difference between yellow PPG and other PPG signals, which implies the potential of the time difference between yellow PPG and other PPGs as a complementary to PTT-based model for blood pressure estimation.

Efficient Skin Temperature Sensor and Stable Gel-Less Sticky ECG Sensor for a Wearable Flexible Healthcare Patch.

PubMed

Yamamoto, Yuki; Yamamoto, Daisuke; Takada, Makoto; Naito, Hiroyoshi; Arie, Takayuki; Akita, Seiji; Takei, Kuniharu

2017-09-01

Wearable, flexible healthcare devices, which can monitor health data to predict and diagnose disease in advance, benefit society. Toward this future, various flexible and stretchable sensors as well as other components are demonstrated by arranging materials, structures, and processes. Although there are many sensor demonstrations, the fundamental characteristics such as the dependence of a temperature sensor on film thickness and the impact of adhesive for an electrocardiogram (ECG) sensor are yet to be explored in detail. In this study, the effect of film thickness for skin temperature measurements, adhesive force, and reliability of gel-less ECG sensors as well as an integrated real-time demonstration is reported. Depending on the ambient conditions, film thickness strongly affects the precision of skin temperature measurements, resulting in a thin flexible film suitable for a temperature sensor in wearable device applications. Furthermore, by arranging the material composition, stable gel-less sticky ECG electrodes are realized. Finally, real-time simultaneous skin temperature and ECG signal recordings are demonstrated by attaching an optimized device onto a volunteer's chest. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design of Secure ECG-Based Biometric Authentication in Body Area Sensor Networks

PubMed Central

Peter, Steffen; Pratap Reddy, Bhanu; Momtaz, Farshad; Givargis, Tony

2016-01-01

Body area sensor networks (BANs) utilize wireless communicating sensor nodes attached to a human body for convenience, safety, and health applications. Physiological characteristics of the body, such as the heart rate or Electrocardiogram (ECG) signals, are promising means to simplify the setup process and to improve security of BANs. This paper describes the design and implementation steps required to realize an ECG-based authentication protocol to identify sensor nodes attached to the same human body. Therefore, the first part of the paper addresses the design of a body-area sensor system, including the hardware setup, analogue and digital signal processing, and required ECG feature detection techniques. A model-based design flow is applied, and strengths and limitations of each design step are discussed. Real-world measured data originating from the implemented sensor system are then used to set up and parametrize a novel physiological authentication protocol for BANs. The authentication protocol utilizes statistical properties of expected and detected deviations to limit the number of false positive and false negative authentication attempts. The result of the described holistic design effort is the first practical implementation of biometric authentication in BANs that reflects timing and data uncertainties in the physical and cyber parts of the system. PMID:27110785

Block sparsity-based joint compressed sensing recovery of multi-channel ECG signals.

PubMed

Singh, Anurag; Dandapat, Samarendra

2017-04-01

In recent years, compressed sensing (CS) has emerged as an effective alternative to conventional wavelet based data compression techniques. This is due to its simple and energy-efficient data reduction procedure, which makes it suitable for resource-constrained wireless body area network (WBAN)-enabled electrocardiogram (ECG) telemonitoring applications. Both spatial and temporal correlations exist simultaneously in multi-channel ECG (MECG) signals. Exploitation of both types of correlations is very important in CS-based ECG telemonitoring systems for better performance. However, most of the existing CS-based works exploit either of the correlations, which results in a suboptimal performance. In this work, within a CS framework, the authors propose to exploit both types of correlations simultaneously using a sparse Bayesian learning-based approach. A spatiotemporal sparse model is employed for joint compression/reconstruction of MECG signals. Discrete wavelets transform domain block sparsity of MECG signals is exploited for simultaneous reconstruction of all the channels. Performance evaluations using Physikalisch-Technische Bundesanstalt MECG diagnostic database show a significant gain in the diagnostic reconstruction quality of the MECG signals compared with the state-of-the art techniques at reduced number of measurements. Low measurement requirement may lead to significant savings in the energy-cost of the existing CS-based WBAN systems.

Design of Secure ECG-Based Biometric Authentication in Body Area Sensor Networks.

PubMed

Peter, Steffen; Reddy, Bhanu Pratap; Momtaz, Farshad; Givargis, Tony

2016-04-22

Body area sensor networks (BANs) utilize wireless communicating sensor nodes attached to a human body for convenience, safety, and health applications. Physiological characteristics of the body, such as the heart rate or Electrocardiogram (ECG) signals, are promising means to simplify the setup process and to improve security of BANs. This paper describes the design and implementation steps required to realize an ECG-based authentication protocol to identify sensor nodes attached to the same human body. Therefore, the first part of the paper addresses the design of a body-area sensor system, including the hardware setup, analogue and digital signal processing, and required ECG feature detection techniques. A model-based design flow is applied, and strengths and limitations of each design step are discussed. Real-world measured data originating from the implemented sensor system are then used to set up and parametrize a novel physiological authentication protocol for BANs. The authentication protocol utilizes statistical properties of expected and detected deviations to limit the number of false positive and false negative authentication attempts. The result of the described holistic design effort is the first practical implementation of biometric authentication in BANs that reflects timing and data uncertainties in the physical and cyber parts of the system.

[Stress-ECG is adequate to detect myocardial ischemia: when are additional diagnostic tests needed?].

PubMed

Baer, F M

2007-09-01

The stress-ECG is the most often adopted and most cost effective initial diagnostic test for the assessment of myocardial ischemia in patients with suspected coronary artery disease (CAD). Prerequisites for the diagnostic usefullness of stress-ECG are a clearly interpretable ST-segment, ability to reach the predicted work load, an intermediate pretest probability for CAD ranging between 10% and 90% and the absence of any contraindications for dynamic exercise. Because of the limited diagnostic sensitivity of about 70%, and a high percentage of patients, who are unable to exercise, a negative stress ECG can definitely not exclude hemodynamically significant CAD. Therefore, stress imaging techniques like myocardial scintigraphy, stress-echocardiography and stress magnetic resonance imaging play a major role in the stepwise diagnostic work-up of patients with suspected CAD. These stress imaging techniques are basically interchangeable since no method is definitely superior to one of the others. However, each method has its specific pros and cons and inherent contraindications. Therefore the choice of the stress imaging method and the form of stress applied should be based on the individual patients characteristics to gain optimal image quality and diagnostic accuracy. Moreover, the decision for one method should take the local availability and institutional expertise of diagnostic centers into account. Although partly substituted by stress imaging techniques the stress-ECG still remains the workhorse for a stepwise diagnostic work-up of patients with suspected CAD.

An intelligent telecardiology system using a wearable and wireless ECG to detect atrial fibrillation.

PubMed

Lin, Chin-Teng; Chang, Kuan-Cheng; Lin, Chun-Ling; Chiang, Chia-Cheng; Lu, Shao-Wei; Chang, Shih-Sheng; Lin, Bor-Shyh; Liang, Hsin-Yueh; Chen, Ray-Jade; Lee, Yuan-Teh; Ko, Li-Wei

2010-05-01

This study presents a novel wireless, ambulatory, real-time, and autoalarm intelligent telecardiology system to improve healthcare for cardiovascular disease, which is one of the most prevalent and costly health problems in the world. This system consists of a lightweight and power-saving wireless ECG device equipped with a built-in automatic warning expert system. This device is connected to a mobile and ubiquitous real-time display platform. The acquired ECG signals are instantaneously transmitted to mobile devices, such as netbooks or mobile phones through Bluetooth, and then, processed by the expert system. An alert signal is sent to the remote database server, which can be accessed by an Internet browser, once an abnormal ECG is detected. The current version of the expert system can identify five types of abnormal cardiac rhythms in real-time, including sinus tachycardia, sinus bradycardia, wide QRS complex, atrial fibrillation (AF), and cardiac asystole, which is very important for both the subjects who are being monitored and the healthcare personnel tracking cardiac-rhythm disorders. The proposed system also activates an emergency medical alarm system when problems occur. Clinical testing reveals that the proposed system is approximately 94% accurate, with high sensitivity, specificity, and positive prediction rates for ten normal subjects and 20 AF patients. We believe that in the future a business-card-like ECG device, accompanied with a mobile phone, can make universal cardiac protection service possible.

A lightweight QRS detector for single lead ECG signals using a max-min difference algorithm.

PubMed

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

An ECG storage and retrieval system embedded in client server HIS utilizing object-oriented DB.

PubMed

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.

A novel method for the detection of R-peaks in ECG based on K-Nearest Neighbors and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

He, Runnan; Wang, Kuanquan; Li, Qince; Yuan, Yongfeng; Zhao, Na; Liu, Yang; Zhang, Henggui

2017-12-01

Cardiovascular diseases are associated with high morbidity and mortality. However, it is still a challenge to diagnose them accurately and efficiently. Electrocardiogram (ECG), a bioelectrical signal of the heart, provides crucial information about the dynamical functions of the heart, playing an important role in cardiac diagnosis. As the QRS complex in ECG is associated with ventricular depolarization, therefore, accurate QRS detection is vital for interpreting ECG features. In this paper, we proposed a real-time, accurate, and effective algorithm for QRS detection. In the algorithm, a proposed preprocessor with a band-pass filter was first applied to remove baseline wander and power-line interference from the signal. After denoising, a method combining K-Nearest Neighbor (KNN) and Particle Swarm Optimization (PSO) was used for accurate QRS detection in ECGs with different morphologies. The proposed algorithm was tested and validated using 48 ECG records from MIT-BIH arrhythmia database (MITDB), achieved a high averaged detection accuracy, sensitivity and positive predictivity of 99.43, 99.69, and 99.72%, respectively, indicating a notable improvement to extant algorithms as reported in literatures.

Cardiac Electrophysiology: Normal and Ischemic Ionic Currents and the ECG

ERIC Educational Resources Information Center

Klabunde, Richard E.

2017-01-01

Basic cardiac electrophysiology is foundational to understanding normal cardiac function in terms of rate and rhythm and initiation of cardiac muscle contraction. The primary clinical tool for assessing cardiac electrical events is the electrocardiogram (ECG), which provides global and regional information on rate, rhythm, and electrical…

A novel ECG detector performance metric and its relationship with missing and false heart rate limit alarms.

PubMed

Daluwatte, Chathuri; Vicente, Jose; Galeotti, Loriano; Johannesen, Lars; Strauss, David G; Scully, Christopher G

Performance of ECG beat detectors is traditionally assessed on long intervals (e.g.: 30min), but only incorrect detections within a short interval (e.g.: 10s) may cause incorrect (i.e., missed+false) heart rate limit alarms (tachycardia and bradycardia). We propose a novel performance metric based on distribution of incorrect beat detection over a short interval and assess its relationship with incorrect heart rate limit alarm rates. Six ECG beat detectors were assessed using performance metrics over long interval (sensitivity and positive predictive value over 30min) and short interval (Area Under empirical cumulative distribution function (AUecdf) for short interval (i.e., 10s) sensitivity and positive predictive value) on two ECG databases. False heart rate limit and asystole alarm rates calculated using a third ECG database were then correlated (Spearman's rank correlation) with each calculated performance metric. False alarm rates correlated with sensitivity calculated on long interval (i.e., 30min) (ρ=-0.8 and p<0.05) and AUecdf for sensitivity (ρ=0.9 and p<0.05) in all assessed ECG databases. Sensitivity over 30min grouped the two detectors with lowest false alarm rates while AUecdf for sensitivity provided further information to identify the two beat detectors with highest false alarm rates as well, which was inseparable with sensitivity over 30min. Short interval performance metrics can provide insights on the potential of a beat detector to generate incorrect heart rate limit alarms. Published by Elsevier Inc.

Autophagic effects of Hibiscus sabdariffa leaf polyphenols and epicatechin gallate (ECG) against oxidized LDL-induced injury of human endothelial cells.

PubMed

Chen, Jing-Hsien; Lee, Ming-Shih; Wang, Chi-Ping; Hsu, Cheng-Chin; Lin, Hui-Hsuan

2017-08-01

Oxidized low-density lipoprotein (ox-LDL) contributes to the pathogenesis of atherosclerosis by promoting vascular endothelial cell injury. Hibiscus sabdariffa leaf polyphenols (HLP), rich in flavonoids, have been shown to possess antioxidant and antiatherosclerotic activities. In this study, we examined the protective role of HLP and its main compound (-)-epicatechin gallate (ECG) in human umbilical vein endothelial cells (HUVECs) exposed to ox-LDL in vitro. In a model of ox-LDL-impaired HUVECs, assessments of cell viability, cytotoxicity, cell proliferation, apoptosis, and autophagy were detected. To highlight the mechanisms of the antiapoptotic effects of HLP and ECG, the expressions of molecular proteins were measured by Western blotting, real-time PCR, and so on. HLP or ECG improved the survival of HUVECs from ox-LDL-induced viability loss. In addition, HLP or ECG showed potential in reducing ox-LDL-dependent apoptosis. Next, the ox-LDL-induced formation of acidic vesicular organelles and upregulation of the autophagy-related genes were increased by HLP or ECG. The HLP-triggered autophagic flux was further confirmed by increasing the LC3-II level under the pretreatment of an autophagy inhibitor chloroquine. Molecular data indicated the autophagic effect of HLP or ECG might be mediated via class III PI3K/Beclin-1 and PTEN/class I PI3K/Akt cascade signaling, as demonstrated by the usage of a class III PI3K inhibitor 3-methyladenine (3-MA) and a PTEN inhibitor SF1670. Our data imply that ECG-enriched HLP upregulates the autophagic pathway, which in turn led to reduce ox-LDL-induced HUVECs injury and apoptosis and provide a new mechanism for its antiatherosclerotic activity.

Design, fabrication and skin-electrode contact analysis of polymer microneedle-based ECG electrodes

NASA Astrophysics Data System (ADS)

O'Mahony, Conor; Grygoryev, Konstantin; Ciarlone, Antonio; Giannoni, Giuseppe; Kenthao, Anan; Galvin, Paul

2016-08-01

Microneedle-based ‘dry’ electrodes have immense potential for use in diagnostic procedures such as electrocardiography (ECG) analysis, as they eliminate several of the drawbacks associated with the conventional ‘wet’ electrodes currently used for physiological signal recording. To be commercially successful in such a competitive market, it is essential that dry electrodes are manufacturable in high volumes and at low cost. In addition, the topographical nature of these emerging devices means that electrode performance is likely to be highly dependent on the quality of the skin-electrode contact. This paper presents a low-cost, wafer-level micromoulding technology for the fabrication of polymeric ECG electrodes that use microneedle structures to make a direct electrical contact to the body. The double-sided moulding process can be used to eliminate post-process via creation and wafer dicing steps. In addition, measurement techniques have been developed to characterize the skin-electrode contact force. We perform the first analysis of signal-to-noise ratio dependency on contact force, and show that although microneedle-based electrodes can outperform conventional gel electrodes, the quality of ECG recordings is significantly dependent on temporal and mechanical aspects of the skin-electrode interface.

A portable ECG monitoring device with Bluetooth and Holter capabilities for telemedicine applications.

PubMed

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.

Smartphone ECG aids real time diagnosis of palpitations in the competitive college athlete.

PubMed

Peritz, David C; Howard, Austin; Ciocca, Mario; Chung, Eugene H

2015-01-01

Rapidly detecting dangerous arrhythmias in a symptomatic athlete continues to be an elusive goal. The use of handheld smartphone electrocardiogram (ECG) monitors could represent a helpful tool connecting the athletic trainer to the cardiologist. Six college athletes presented to their athletic trainers complaining of palpitations during exercise. A single lead ECG was performed using the AliveCor Heart Monitor and sent wirelessly to the Team Cardiologist who confirmed an absence of dangerous arrhythmia. AliveCor monitoring has the potential to enhance evaluation of symptomatic athletes by allowing trainers and team physicians to make diagnosis in real-time and facilitate faster return to play. Copyright © 2015 Elsevier Inc. All rights reserved.

CT coronary angiography and exercise ECG in a population with chest pain and low-to-intermediate pre-test likelihood of coronary artery disease.

PubMed

Maffei, Erica; Seitun, Sara; Martini, Chiara; Palumbo, Alessandro; Tarantini, Giuseppe; Berti, Elena; Grilli, Roberto; Tedeschi, Carlo; Messalli, Giancarlo; Guaricci, Andrea; Weustink, Annick C; Mollet, Nico Ra; Cademartiri, Filippo

2010-12-01

To evaluate diagnostic accuracy of exercise ECG (ex-ECG) versus 64-slice CT coronary angiography (CT-CA) for the detection of significant coronary artery stenosis in a population with low-to-intermediate pre-test likelihood of coronary artery disease (CAD). Retrospective single centre. Tertiary academic hospital. 177 consecutive patients (88 men, 89 women, mean age 53.5±7.6 years) with chest pain and low-to-intermediate pre-test likelihood of CAD were retrospectively enrolled. All patients underwent ex-ECG, CT-CA and invasive coronary angiography (ICA). A lumen diameter reduction of ≥50% was considered as significant stenosis for CT-CA. Ex-ECG was classified as positive, negative or non-diagnostic. were compared with ICA. Diagnostic accuracy of CT-CA and ex-ECG was calculated using ICA as the reference standard. A parallel comparative analysis using a cut-off value of 70% for significant lumen reduction was also performed too. Results ICA disclosed an absence of significant stenosis (≥50% luminal narrowing) in 85.3% (151/177) patients, single-vessel disease in 9.0% (16/177) patients and multivessel disease in 5.6% (10/177) patients. Prevalence of obstructive disease at ICA was 14.7% (26/177). Sensitivity, specificity, positive and negative predictive values at the patient level were 100.0%, 98.7%, 92.9%, 100%, respectively, for CT-CA and 46.2%, 16.6%, 8.7%, 64.1%, respectively, for ex-ECG. Agreement between CT-CA and ex-ECG was 20.9%. CT-CA performed equally well in men and women, while ex-ECG had a better performance in men. After considering the cut-off value of 70% for significant stenosis, the difference between CT-CA and ex-ECG remained significant (p<0.01), with a low agreement (21.5%). CT-CA provides optimal diagnostic performance in patients with atypical chest pain and low-to-intermediate risk of CAD. Ex-ECG has poor diagnostic accuracy in this population. Concerns are related to risk of radiation dose versus the benefits of correct disease

A Combined Independent Source Separation and Quality Index Optimization Method for Fetal ECG Extraction from Abdominal Maternal Leads

PubMed Central

Billeci, Lucia; Varanini, Maurizio

2017-01-01

The non-invasive fetal electrocardiogram (fECG) technique has recently received considerable interest in monitoring fetal health. The aim of our paper is to propose a novel fECG algorithm based on the combination of the criteria of independent source separation and of a quality index optimization (ICAQIO-based). The algorithm was compared with two methods applying the two different criteria independently—the ICA-based and the QIO-based methods—which were previously developed by our group. All three methods were tested on the recently implemented Fetal ECG Synthetic Database (FECGSYNDB). Moreover, the performance of the algorithm was tested on real data from the PhysioNet fetal ECG Challenge 2013 Database. The proposed combined method outperformed the other two algorithms on the FECGSYNDB (ICAQIO-based: 98.78%, QIO-based: 97.77%, ICA-based: 97.61%). Significant differences were obtained in particular in the conditions when uterine contractions and maternal and fetal ectopic beats occurred. On the real data, all three methods obtained very high performances, with the QIO-based method proving slightly better than the other two (ICAQIO-based: 99.38%, QIO-based: 99.76%, ICA-based: 99.37%). The findings from this study suggest that the proposed method could potentially be applied as a novel algorithm for accurate extraction of fECG, especially in critical recording conditions. PMID:28509860

Robust QRS detection for HRV estimation from compressively sensed ECG measurements for remote health-monitoring systems.

PubMed

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.

Development of three methods for extracting respiration from the surface ECG: a review.

PubMed

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

Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy.

PubMed

Mishra, Vikas; Gautier, Nicole M; Glasscock, Edward

2018-01-29

In epilepsy, seizures can evoke cardiac rhythm disturbances such as heart rate changes, conduction blocks, asystoles, and arrhythmias, which can potentially increase risk of sudden unexpected death in epilepsy (SUDEP). Electroencephalography (EEG) and electrocardiography (ECG) are widely used clinical diagnostic tools to monitor for abnormal brain and cardiac rhythms in patients. Here, a technique to simultaneously record video, EEG, and ECG in mice to measure behavior, brain, and cardiac activities, respectively, is described. The technique described herein utilizes a tethered (i.e., wired) recording configuration in which the implanted electrode on the head of the mouse is hard-wired to the recording equipment. Compared to wireless telemetry recording systems, the tethered arrangement possesses several technical advantages such as a greater possible number of channels for recording EEG or other biopotentials; lower electrode costs; and greater frequency bandwidth (i.e., sampling rate) of recordings. The basics of this technique can also be easily modified to accommodate recording other biosignals, such as electromyography (EMG) or plethysmography for assessment of muscle and respiratory activity, respectively. In addition to describing how to perform the EEG-ECG recordings, we also detail methods to quantify the resulting data for seizures, EEG spectral power, cardiac function, and heart rate variability, which we demonstrate in an example experiment using a mouse with epilepsy due to Kcna1 gene deletion. Video-EEG-ECG monitoring in mouse models of epilepsy or other neurological disease provides a powerful tool to identify dysfunction at the level of the brain, heart, or brain-heart interactions.

A New Algorithm to Diagnose Atrial Ectopic Origin from Multi Lead ECG Systems - Insights from 3D Virtual Human Atria and Torso

PubMed Central

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

Architecture design of the multi-functional wavelet-based ECG microprocessor for realtime detection of abnormal cardiac events.

PubMed

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.

The effect of administering equine chorionic gonadotropin (eCG) and human chorionic gonadotropin (hCG) post artificial insemination on fertility of lactating dairy cows.

PubMed

Bartolome, J A; Wallace, S Perez; de la Sota, R L; Thatcher, W W

2012-09-15

The objective was to evaluate the effect of equine chorionic gonadotropin (eCG) and hCG post artificial insemination (AI) on fertility of lactating dairy cows. In Experiment 1, cows were either treated with eCG on Day 22 post AI (400 IU; n = 80) or left untreated (n = 84). On Day 29, pregnant cows were either treated with hCG (2500 IU; n = 32) or left untreated (n = 36). Pregnancy and progesterone were evaluated on Days 29 and 45. In Experiment 2, cows (n = 28) were either treated with eCG on Day 22 (n = 13) or left untreated (n = 15) and either treated with hCG on Day 29 (n = 14) or left untreated (n = 14). Blood sampling and ultrasonography were conducted between Days 22 and 45. In Experiment 3, cows were either treated with eCG on Day 22 post AI (n = 229) or left untreated (n = 241). Pregnancy was evaluated on Days 36 and 85. In Experiment 1, eCG on Day 22 increased (P < 0.02) the number of pregnant cows on Day 29 (50.0 vs. 33.3%) and on Day 45, the increase was higher (P < 0.01) in cows with timed AI (41.2 vs. 6.5%) than in cows AI at detected estrus (50.0 vs. 37.8%). Pregnancy losses were reduced by eCG and hCG, but increased in cows that did not receive eCG but were given hCG (P < 0.01). Treatment with hCG tended (P < 0.06) to increase progesterone in control cows, but not in cows treated with eCG. In Experiment 2, hCG increased (P < 0.01) the number of accessory CLs on Day 35 (28.5 vs. 0.0%) and tended (P < 0.07) to increase progesterone. In Experiment 3, eCG increased the number of pregnant cows (P < 0.05) on Days 36 and 85, but only in cows with low body condition (eCG = 45.6 and 43.5%; Control = 22.9 and 22.9%). In conclusion, eCG at 22 days post insemination increased fertility, primarily in cows with low body condition and reduced pregnancy losses when given 7 days before hCG; hCG induced accessory CLs and slightly increased progesterone, but hCG given in the absence of a prior eCG treatment reduced fertility. Copyright © 2012 Elsevier Inc. All rights

Biomedical implementation of liquid metal ink as drawable ECG electrode and skin circuit.

PubMed

Yu, Yang; Zhang, Jie; Liu, Jing