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

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.

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

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.

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

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.

Observer agreement for detection of cardiac arrhythmias on telemetric ECG recordings obtained at rest, during and after exercise in 10 Warmblood horses.

PubMed

Trachsel, D S; Bitschnau, C; Waldern, N; Weishaupt, M A; Schwarzwald, C C

2010-11-01

Frequent supraventricular or ventricular arrhythmias during and after exercise are considered pathological in horses. Prevalence of arrhythmias seen in apparently healthy horses is still a matter of debate and may depend on breed, athletic condition and exercise intensity. To determine intra- and interobserver agreement for detection of arrhythmias at rest, during and after exercise using a telemetric electrocardiography device. The electrocardiogram (ECG) recordings of 10 healthy Warmblood horses (5 of which had an intracardiac catheter in place) undergoing a standardised treadmill exercise test were analysed at rest (R), during warm-up (W), during exercise (E), as well as during 0-5 min (PE(0-5)) and 6-45 min (PE(6-45)) recovery after exercise. The number and time of occurrence of physiological and pathological 'rhythm events' were recorded. Events were classified according to origin and mode of conduction. The agreement of 3 independent, blinded observers with different experience in ECG reading was estimated considering time of occurrence and classification of events. For correct timing and classification, intraobserver agreement for observer 1 was 97% (R), 100% (W), 20% (E), 82% (PE(0-5)) and 100% (PE(6-45)). Interobserver agreement between observer 1 vs. observer 2 and between observer 1 vs. 3, respectively, was 96 and 92.6% (R), 83 and 31% (W), 0 and 13% (E), 23 and 18% (PE(0-5)), and 67 and 55% (PE(6-45)). When including the events with correct timing but disagreement for classification, the intraobserver agreement increased to 94% during PE(0-5) and the interobserver agreement reached 83 and 50% (W), 20 and 50% (E), 41 and 47% (PE(0-5)), and 83.5 and 65% (PE(6-45)). The interobserver agreement increased with observer experience. Intra- and interobserver agreement for recognition and classification of events was good at R, but poor during E and poor-moderate during recovery periods. These results highlight the limitations of stress ECG in horses and the

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.

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.

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.

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.

Influence of ECG measurement accuracy on ECG diagnostic statements.

PubMed

Zywietz, C; Celikag, D; Joseph, G

1996-01-01

Computer analysis of electrocardiograms (ECGs) provides a large amount of ECG measurement data, which may be used for diagnostic classification and storage in ECG databases. Until now, neither error limits for ECG measurements have been specified nor has their influence on diagnostic statements been systematically investigated. An analytical method is presented to estimate the influence of measurement errors on the accuracy of diagnostic ECG statements. Systematic (offset) errors will usually result in an increase of false positive or false negative statements since they cause a shift of the working point on the receiver operating characteristics curve. Measurement error dispersion broadens the distribution function of discriminative measurement parameters and, therefore, usually increases the overlap between discriminative parameters. This results in a flattening of the receiver operating characteristics curve and an increase of false positive and false negative classifications. The method developed has been applied to ECG conduction defect diagnoses by using the proposed International Electrotechnical Commission's interval measurement tolerance limits. These limits appear too large because more than 30% of false positive atrial conduction defect statements and 10-18% of false intraventricular conduction defect statements could be expected due to tolerated measurement errors. To assure long-term usability of ECG measurement databases, it is recommended that systems provide its error tolerance limits obtained on a defined test set.

Panoramic ECG display versus conventional ECG: ischaemia detection by critical care nurses.

PubMed

Wilson, Nick; Hassani, Aimen; Gibson, Vanessa; Lightfoot, Timothy; Zizzo, Claudio

2012-01-01

To compare accuracy and certainty of diagnosis of cardiac ischaemia using the Panoramic ECG display tool plus conventional 12-lead electrocardiogram (ECG) versus 12-lead ECG alone by UK critical care nurses who were members of the British Association of Critical Care Nurses (BACCN). Critically ill patients are prone to myocardial ischaemia. Symptoms may be masked by sedation or analgesia, and ECG changes may be the only sign. Critical care nurses have an essential role in detecting ECG changes promptly. Despite this, critical care nurses may lack expertise in interpreting ECGs and myocardial ischaemia often goes undetected by critical care staff. British Association of Critical Care Nurses (BACCN) members were invited to complete an online survey to evaluate the analysis of two sets of eight ECGs displayed alone and with the new display device. Data from 82 participants showed diagnostic accuracy improved from 67·1% reading ECG traces alone, to 96·0% reading ECG plus Panoramic ECG display tool (P < 0·01, significance level α = 0·05). Participants' diagnostic certainty score rose from 41·7% reading ECG alone to 66·8% reading ECG plus Panoramic ECG display tool (P < 0·01, α = 0·05). The Panoramic ECG display tool improves both accuracy and certainty of detecting ST segment changes among critical care nurses, when compared to conventional 12-lead ECG alone. This benefit was greatest with early ischaemic changes. Critical care nurses who are least confident in reading conventional ECGs benefit the most from the new display. Critical care nurses have an essential role in the monitoring of critically ill patients. However, nurses do not always have the expertise to detect subtle ischaemic ECG changes promptly. Introduction of the Panoramic ECG display tool into clinical practice could lead to patients receiving treatment for myocardial ischaemia sooner with the potential for reduction in morbidity and mortality. © 2012 The Authors. Nursing in Critical Care �

Multichannel ECG and Noise Modeling: Application to Maternal and Fetal ECG Signals

NASA Astrophysics Data System (ADS)

Sameni, Reza; Clifford, Gari D.; Jutten, Christian; Shamsollahi, Mohammad B.

2007-12-01

A three-dimensional dynamic model of the electrical activity of the heart is presented. The model is based on the single dipole model of the heart and is later related to the body surface potentials through a linear model which accounts for the temporal movements and rotations of the cardiac dipole, together with a realistic ECG noise model. The proposed model is also generalized to maternal and fetal ECG mixtures recorded from the abdomen of pregnant women in single and multiple pregnancies. The applicability of the model for the evaluation of signal processing algorithms is illustrated using independent component analysis. Considering the difficulties and limitations of recording long-term ECG data, especially from pregnant women, the model described in this paper may serve as an effective means of simulation and analysis of a wide range of ECGs, including adults and fetuses.

Resting electrocardiogram and stress myocardial perfusion imaging in the determination of left ventricular systolic function: an assessment enhancing the performance of gated SPET.

PubMed

Moralidis, Efstratios; Spyridonidis, Tryfon; Arsos, Georgios; Skeberis, Vassilios; Anagnostopoulos, Constantinos; Gavrielidis, Stavros

2010-01-01

This study aimed to determine systolic dysfunction and estimate resting left ventricular ejection fraction (LVEF) from information collected during routine evaluation of patients with suspected or known coronary heart disease. This approach was then compared to gated single photon emission tomography (SPET). Patients having undergone stress (201)Tl myocardial perfusion imaging followed by equilibrium radionuclide angiography (ERNA) were separated into derivation (n=954) and validation (n=309) groups. Logistic regression analysis was used to develop scoring systems, containing clinical, electrocardiographic (ECG) and scintigraphic data, for the discrimination of an ERNA-LVEF<0.50. Linear regression analysis provided equations predicting ERNA-LVEF from those scores. In 373 patients LVEF was also assessed with (201)Tl gated SPET. Our results showed that an ECG-Scintigraphic scoring system was the best simple predictor of an ERNA-LVEF<0.50 in comparison to other models including ECG, clinical and scintigraphic variables in both the derivation and validation subpopulations. A simple linear equation was derived also for the assessment of resting LVEF from the ECG-Scintigraphic model. Equilibrium radionuclide angiography-LVEF had a good correlation with the ECG-Scintigraphic model LVEF (r=0.716, P=0.000), (201)Tl gated SPET LVEF (r=0.711, P=0.000) and the average LVEF from those assessments (r=0.796, P=0.000). The Bland-Altman statistic (mean+/-2SD) provided values of 0.001+/-0.176, 0.071+/-0.196 and 0.040+/-0.152, respectively. The average LVEF was a better discriminator of systolic dysfunction than gated SPET-LVEF in receiver operating characteristic (ROC) analysis and identified more patients (89%) with a resting left ventricular systolic dysfunction can be determined effectively from simple resting ECG and stress myocardial perfusion imaging variables. This model provides reliable LVEF

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

Assessing ECG signal quality indices to discriminate ECGs with artefacts from pathologically different arrhythmic ECGs.

PubMed

Daluwatte, C; Johannesen, L; Galeotti, L; Vicente, J; Strauss, D G; Scully, C G

2016-08-01

False and non-actionable alarms in critical care can be reduced by developing algorithms which assess the trueness of an arrhythmia alarm from a bedside monitor. Computational approaches that automatically identify artefacts in ECG signals are an important branch of physiological signal processing which tries to address this issue. Signal quality indices (SQIs) derived considering differences between artefacts which occur in ECG signals and normal QRS morphology have the potential to discriminate pathologically different arrhythmic ECG segments as artefacts. Using ECG signals from the PhysioNet/Computing in Cardiology Challenge 2015 training set, we studied previously reported ECG SQIs in the scientific literature to differentiate ECG segments with artefacts from arrhythmic ECG segments. We found that the ability of SQIs to discriminate between ECG artefacts and arrhythmic ECG varies based on arrhythmia type since the pathology of each arrhythmic ECG waveform is different. Therefore, to reduce the risk of SQIs classifying arrhythmic events as noise it is important to validate and test SQIs with databases that include arrhythmias. Arrhythmia specific SQIs may also minimize the risk of misclassifying arrhythmic events as noise.

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.

Experimental evaluations of wearable ECG monitor.

PubMed

Ha, Kiryong; Kim, Youngsung; Jung, Junyoung; Lee, Jeunwoo

2008-01-01

Healthcare industry is changing with ubiquitous computing environment and wearable ECG measurement is one of the most popular approaches in this healthcare industry. Reliability and performance of healthcare device is fundamental issue for widespread adoptions, and interdisciplinary perspectives of wearable ECG monitor make this more difficult. In this paper, we propose evaluation criteria considering characteristic of both ECG measurement and ubiquitous computing. With our wearable ECG monitors, various levels of experimental analysis are performed based on evaluation strategy.

Competency in ECG Interpretation Among Medical Students

PubMed Central

Kopeć, Grzegorz; Magoń, Wojciech; Hołda, Mateusz; Podolec, Piotr

2015-01-01

Background Electrocardiogram (ECG) is commonly used in diagnosis of heart diseases, including many life-threatening disorders. We aimed to assess skills in ECG interpretation among Polish medical students and to analyze the determinants of these skills. Material/Methods Undergraduates from all Polish medical schools were asked to complete a web-based survey containing 18 ECG strips. Questions concerned primary ECG parameters (rate, rhythm, and axis), emergencies, and common ECG abnormalities. Analysis was restricted to students in their clinical years (4th–6th), and students in their preclinical years (1st–3rd) were used as controls. Results We enrolled 536 medical students (females: n=299; 55.8%), aged 19 to 31 (23±1.6) years from all Polish medical schools. Most (72%) were in their clinical years. The overall rate of good response was better in students in years 4th–5th than those in years 1st–3rd (66% vs. 56%; p<0.0001). Competency in ECG interpretation was higher in students who reported ECG self-learning (69% vs. 62%; p<0.0001) but no difference was found between students who attended or did not attend regular ECG classes (66% vs. 66%; p=0.99). On multivariable analysis (p<0.0001), being in clinical years (OR: 2.45 [1.35–4.46] and self-learning (OR: 2.44 [1.46–4.08]) determined competency in ECG interpretation. Conclusions Polish medical students in their clinical years have a good level of competency in interpreting the primary ECG parameters, but their ability to recognize ECG signs of emergencies and common heart abnormalities is low. ECG interpretation skills are determined by self-education but not by attendance at regular ECG classes. Our results indicate qualitative and quantitative deficiencies in teaching ECG interpretation at medical schools. PMID:26541993

Influence of ECG sampling rate in fetal heart rate variability analysis.

PubMed

De Jonckheere, J; Garabedian, C; Charlier, P; Champion, C; Servan-Schreiber, E; Storme, L; Debarge, V; Jeanne, M; Logier, R

2017-07-01

Fetal hypoxia results in a fetal blood acidosis (pH<;7.10). In such a situation, the fetus develops several adaptation mechanisms regulated by the autonomic nervous system. Many studies demonstrated significant changes in heart rate variability in hypoxic fetuses. So, fetal heart rate variability analysis could be of precious help for fetal hypoxia prediction. Commonly used fetal heart rate variability analysis methods have been shown to be sensitive to the ECG signal sampling rate. Indeed, a low sampling rate could induce variability in the heart beat detection which will alter the heart rate variability estimation. In this paper, we introduce an original fetal heart rate variability analysis method. We hypothesize that this method will be less sensitive to ECG sampling frequency changes than common heart rate variability analysis methods. We then compared the results of this new heart rate variability analysis method with two different sampling frequencies (250-1000 Hz).

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.

The Normal Electrocardiogram: Resting 12-Lead and Electrocardiogram Monitoring in the Hospital.

PubMed

Harris, Patricia R E

2016-09-01

The electrocardiogram (ECG) is a well-established diagnostic tool extensively used in clinical settings. Knowledge of cardiac rhythm and mastery of cardiac waveform interpretation are fundamental for intensive care nurses. Recognition of the normal findings for the 12-lead ECG and understanding the significance of changes from baseline in continuous cardiac monitoring are essential steps toward ensuring safe patient care. This article highlights historical developments in electrocardiography, describes the normal resting 12-lead ECG, and discusses the need for continuous cardiac monitoring. In addition, future directions for the ECG are explored briefly. Copyright © 2016 Elsevier Inc. All rights reserved.

Plasma electrolytes, pH, and ECG during and after exhaustive exercise.

NASA Technical Reports Server (NTRS)

Coester, N.; Elliott, J. C.; Luft, U. C.

1973-01-01

Ten men worked on a bicycle ergometer at increasing work loads to exhaustion in 15 min. Each performed one test breathing air and another with added CO2 in random sequence. ECG was recorded during exercise and for 30 min of recovery. Arterial samples for blood gases, pH, and electrolytes were drawn at rest, in the last minute of exercise and at 1, 4, 10, 20, and 30 min thereafter. A striking increase in the amplitude of T and P waves was observed reaching a maximum in the first 2 min after exercise. All electrolytes measured were increased at the end of exercise, most markedly potassium (60%) and phosphorus (53%). Potassium dropped faster than all others to below resting values in 4 min coinciding with the lowest levels in plasma bicarbonate. ECG alterations were not closely related in time with any single factor such as potassium, but appeared to reflect an interaction of the transient mineral and acid-base imbalance during and immediately following exhaustive exercise.

Multi-purpose ECG telemetry system.

PubMed

Marouf, Mohamed; Vukomanovic, Goran; Saranovac, Lazar; Bozic, Miroslav

2017-06-19

The Electrocardiogram ECG is one of the most important non-invasive tools for cardiac diseases diagnosis. Taking advantage of the developed telecommunication infrastructure, several approaches that address the development of telemetry cardiac devices were introduced recently. Telemetry ECG devices allow easy and fast ECG monitoring of patients with suspected cardiac issues. Choosing the right device with the desired working mode, signal quality, and the device cost are still the main obstacles to massive usage of these devices. In this paper, we introduce design, implementation, and validation of a multi-purpose telemetry system for recording, transmission, and interpretation of ECG signals in different recording modes. The system consists of an ECG device, a cloud-based analysis pipeline, and accompanied mobile applications for physicians and patients. The proposed ECG device's mechanical design allows laypersons to easily record post-event short-term ECG signals, using dry electrodes without any preparation. Moreover, patients can use the device to record long-term signals in loop and holter modes, using wet electrodes. In order to overcome the problem of signal quality fluctuation due to using different electrodes types and different placements on subject's chest, customized ECG signal processing and interpretation pipeline is presented for each working mode. We present the evaluation of the novel short-term recorder design. Recording of an ECG signal was performed for 391 patients using a standard 12-leads golden standard ECG and the proposed patient-activated short-term post-event recorder. In the validation phase, a sample of validation signals followed peer review process wherein two experts annotated the signals in terms of signal acceptability for diagnosis.We found that 96% of signals allow detecting arrhythmia and other signal's abnormal changes. Additionally, we compared and presented the correlation coefficient and the automatic QRS delineation results

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

Amplitude/frequency differences in a supine resting single-lead electrocardiogram of normal versus coronary heart diseased males.

DOT National Transportation Integrated Search

1974-05-01

A resting 'normal' ECG can coexist with known angina pectoris, positive angiocardiography and previous myocardial infarction. In contemporary exercise ECG tests, a false positive/false negative total error of 10% is not unusual. Research aimed at imp...

Challenges of ECG monitoring and ECG interpretation in dialysis units.

PubMed

Poulikakos, Dimitrios; Malik, Marek

Patients on hemodialysis (HD) suffer from high cardiovascular morbidity and mortality due to high rates of coronary artery disease and arrhythmias. Electrocardiography (ECG) is often performed in the dialysis units as part of routine clinical assessment. However, fluid and electrolyte changes have been shown to affect all ECG morphologies and intervals. ECG interpretation thus depends on the time of the recording in relation to the HD session. In addition, arrhythmias during HD are common, and dialysis-related ECG artifacts mimicking arrhythmias have been reported. Studies using advanced ECG analyses have examined the impact of the HD procedure on selected repolarization descriptors and heart rate variability indices. Despite the challenges related to the impact of the fluctuant fluid and electrolyte status on conventional and advanced ECG parameters, further research in ECG monitoring during dialysis has the potential to provide clinically meaningful and practically useful information for diagnostic and risk stratification purposes. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

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.

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.

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.

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

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.

Radiotelemetry recording of electroencephalogram in piglets during rest.

PubMed

Saito, Toshiyuki; Watanabe, Yasuko; Nemoto, Tetsu; Kasuya, Etsuko; Sakumoto, Ryosuke

2005-04-13

A wireless recording system was developed to study the electroencephalogram (EEG) in unrestrained, male Landrace piglets. Under general anesthesia, ball-tipped silver/silver chloride electrodes for EEG recording were implanted onto the dura matter of the parietal and frontal cortex of the piglets. A pair of miniature preamplifiers and transmitters was then mounted on the surface of the skull. To examine whether other bioelectrical activities interfere with the EEG measurements, an electrocardiogram (ECG) or electromyogram (EMG) of the neck was simultaneously recorded with the EEG. Next, wire electrodes for recording movement of the eyelid were implanted with EEG electrodes, and EEG and eyelid movements were simultaneously measured. Power spectral analysis using a Fast Fourier Transformation (FFT) algorithm indicates that EEG was successfully recorded in unrestrained piglets, at rest, during the daytime in the absence of interference from ECG, EMG or eyelid movements. These data indicate the feasibility of using our radiotelemetry system for measurement of EEG under these conditions.

Use of echocardiography in outpatients with chest pain and normal resting electrocardiograms referred to Mayo Clinic Rochester.

PubMed

Gibbons, Raymond J; Carryer, Damita; Liu, Hongfang; Brady, Peter A; Askew, John Wells; Hodge, David; Ammash, Naser; Ebbert, Jon O; Roger, Veronique L

2018-02-01

To determine how often unnecessary resting echocardiograms that are "not recommended" by clinical practice guidelines are performed in patients with stable chest pain and normal resting electrocardiograms (ECGs). There are scant data to indicate how often Class III recommendations are ignored in clinical practice. We searched electronically all medical records of referral outpatients seen at Mayo Clinic Rochester from January 1, 2010, through December 31, 2013, to identify patients with stable chest pain and known or suspected coronary artery disease who underwent resting echocardiography and had normal resting ECGs and no other indication for echocardiography. Of the 15,529 referral outpatients who were evaluated at Mayo Clinic Rochester with chest pain, 3976 (25.6%) had resting echocardiograms. Eight hundred seventy of these 3976 patients (21.9%) had normal resting ECGs. Six hundred nineteen of these 870 patients (71.1%) had other indications for echocardiography. The remaining 251 patients (6.3% of all echocardiograms and 1.6% of all patients) had normal resting ECGs and no other indication for echocardiography. Two hundred thirty-nine of these 251 patients (95.2%) had normal echocardiograms. Of the 12 abnormal echocardiograms, only 4 led to any change in clinical management. Sixty-one of these 251 echocardiograms (24.3%) were "preordered" before the provider (physicians, nurses, physician assistants) visit. Echocardiograms were performed in 1 in 4 referral outpatients with chest pain seen at Mayo Clinic Rochester. However, only 1 in 16 of these echocardiograms was performed in violation of the class III recommendation in the American College of Cardiology Foundation/American Heart Association guidelines for the management of stable angina. These unnecessary echocardiograms were almost always normal, and had little impact on clinical management. The rate of unnecessary echocardiograms could be decreased by eliminating preordering. Copyright © 2017 Elsevier Inc

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

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.

Use of Echocardiography in Olmsted County Outpatients With Chest Pain and Normal Resting Electrocardiograms Seen at Mayo Clinic Rochester.

PubMed

Gibbons, Raymond J; Carryer, Damita; Liu, Hongfang; Brady, Peter A; Askew, J Wells; Hodge, David; Ammash, Naser; Ebbert, Jon O; Roger, Veronique L

2015-11-01

To determine how often unnecessary resting echocardiograms that are "not recommended" by clinical practice guidelines are performed in patients with stable chest pain and normal resting electrocardiograms (ECGs). We performed a retrospective search of electronic medical records of all outpatients seen at Mayo Clinic Rochester from January 1, 2010, through December 31, 2013, to identify residents of Olmsted County, Minnesota, with stable chest pain and known or suspected coronary artery disease who underwent resting echocardiography and had normal resting ECGs and no other indication for echocardiography. Of the 8280 outpatients from Olmsted County who were evaluated at Mayo Clinic Rochester with chest pain, 590 (7.1%) had resting echocardiograms. Ninety-two of these 590 patients (15.6%) had normal resting ECGs. Thirty-three of these 92 patients (35.9%) had other indications for echocardiography. The remaining 59 patients (10.0% of all echocardiograms and 0.7% of all patients) had normal resting ECGs and no other indication for echocardiography. Fifty-seven of these 59 patients (96.6%) had normal echocardiograms. Thirteen of these 59 echocardiograms (22.0%) were "preordered" before the provider (physicians, nurses, physician assistants) visit. The overall rate of echocardiography in Olmsted County outpatients with chest pain seen at Mayo Clinic Rochester is low. Only 1 in 10 of these echocardiograms was performed in violation of the class III recommendation in the American College of Cardiology Foundation/American Heart Association guidelines for the management of stable angina. These unnecessary echocardiograms were almost always normal. The rate of unnecessary echocardiograms could be decreased by eliminating preordering. Copyright © 2015 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

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.

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.

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

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.

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

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.

Accuracy of ECG interpretation in competitive athletes: the impact of using standised ECG criteria.

PubMed

Drezner, Jonathan A; Asif, Irfan M; Owens, David S; Prutkin, Jordan M; Salerno, Jack C; Fean, Robyn; Rao, Ashwin L; Stout, Karen; Harmon, Kimberly G

2012-04-01

Interpretation of ECGs in athletes is complicated by physiological changes related to training. The purpose of this study was to determine the accuracy of ECG interpretation in athletes among different physician specialties, with and without use of a standised ECG criteria tool. Physicians were asked to interpret 40 ECGs (28 normal ECGs from college athletes randomised with 12 abnormal ECGs from individuals with known ciovascular pathology) and classify each ECG as (1) 'normal or variant--no further evaluation and testing needed' or (2) 'abnormal--further evaluation and testing needed.' After reading the ECGs, participants received a two-page ECG criteria tool to guide interpretation of the ECGs again. A total of 60 physicians participated: 22 primary care (PC) residents, 16 PC attending physicians, 12 sports medicine (SM) physicians and 10 ciologists. At baseline, the total number of ECGs correctly interpreted was PC residents 73%, PC attendings 73%, SM physicians 78% and ciologists 85%. With use of the ECG criteria tool, all physician groups significantly improved their accuracy (p<0.0001): PC residents 92%, PC attendings 90%, SM physicians 91% and ciologists 96%. With use of the ECG criteria tool, specificity improved from 70% to 91%, sensitivity improved from 89% to 94% and there was no difference comparing ciologists versus all other physicians (p=0.053). Providing standised criteria to assist ECG interpretation in athletes significantly improves the ability to accurately distinguish normal from abnormal findings across physician specialties, even in physicians with little or no experience.

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.

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

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.

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.

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.

[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.

[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.

Disease Severity and Exercise Testing Reduce Subcutaneous Implantable Cardioverter-Defibrillator Left Sternal ECG Screening Success in Hypertrophic Cardiomyopathy.

PubMed

Srinivasan, Neil T; Patel, Kiran H; Qamar, Kashif; Taylor, Amy; Bacà, Marco; Providência, Rui; Tome-Esteban, Maria; Elliott, Perry M; Lambiase, Pier D

2017-04-01

The features of the hypertrophic cardiomyopathy (HCM) ECG make it a challenge for subcutaneous implantable cardioverter-defibrillator (S-ICD) screening. We aimed to investigate the causes of screening failure at rest and on exercise to inform optimal S-ICD ECG vector development. One hundred and thirty-one HCM patients (age, 50±16 years; 92 males and 39 females) with ≥1 HCM risk factor for sudden death underwent S-ICD ECG screening at rest and on exercise. Fifty patients (38%) were ineligible for S-ICD because of screening failure in every lead vector: 33 (66%) failed in the supine position, 12 (24%) failed in the standing position, and 5 (10%) failed on exercise. In patients who could exercise and passed screening at rest, 31 (44%) had 1 vector safety, 16 (23%) had 2 vector safety, and 24 (33%) had 3 vector safety. Increased R:T wave ratio in the S-ICD screening ECG (odds ratio, 4.0; confidence interval, 3.0-5.3; P <0.001) was associated with screening failure, while R/T ratio <3 in aVF (odds ratio, 0.3; confidence interval, 0.12-0.69; P =0.006) and increasing age (odds ratio, 0.97; confidence interval, 0.95-0.99; P =0.03) was associated with reduced screening failure. European Society of Cardiology risk score was higher in those failing screening (risk score 5.5% [interquartile range, 3.2-8.7] in failed versus 4.5% [interquartile range, 2.9-7.4] in passed; P =0.04). HCM patients have a significant incidence of screening failure, which is determined primarily by the increased R:T ratio on the screening ECG and lead aVF. High-risk patients have an increased screening failure rate. Optimization of sensing algorithms is required to ensure that the highest risk HCM patients can benefit from S-ICD implantation. © 2017 American Heart Association, Inc.

Wireless Self-Acquistion of 12-Lead ECG via Android Smart Phone

NASA Technical Reports Server (NTRS)

Schlegel, Todd T.

2012-01-01

Researchers at NASA s Johnson Space Center and at Orbital Research, Inc. (a NASA SBIR grant recipient) have recently developed a dry-electrode harness that allows for self-acquisition of resting 12-lead ECGs by minimally trained laypersons. When used in conjunction with commercial wireless (e.g., Bluetooth(TM) or 802.11-enabled) 12-lead ECG devices and custom smart phone-based software, the collected 12-lead ECG data can also immediately be forwarded from any geographic location within cellular range to the user s physician(s) of choice. The system can also be used to immediately forward to central receiving stations 12-lead ECG data collected during space flight or during activities in any remote terrestrial location supported by an internet or cellular phone infrastructure. The main novel aspects of the system are first, the dry-electrode 12-lead ECG harness itself, and second, an accompanying Android(TM) smart phone-based wireless 12-lead ECG capability. The ECG harness nominally employs dry electrodes manufactured by Orbital Research, Inc, recently cleared through the Food and Drug Administration (FDA). However, other dry electrodes that are not yet FDA cleared, for example those recently developed by Nanosonic, Inc as part of another NASA SBIR grant, can also be used. The various advantageous features of the harness include: 1) laypersons can be quickly instructed on its correct use, remotely if necessary; 2) all tangled "leadwire spaghetti" is eliminated, as is the common clinical problem of "leadwire reversal"; 3) all adhesives and disposables are also eliminated, the harness being fully reusable; if multiple individuals intend to use use the same harness, then standard antimicrobial wipes can be employed to sterilize the dry electrodes (and harness surface if needed) between users; 5) padded cushions at the lateral sides of the torso function to press the left arm (LA) and right arm (RA) dry electrodes mounted on the cushions against sideward or downward-rested

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.

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

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

Resting and Postexercise Heart Rate Detection From Fingertip and Facial Photoplethysmography Using a Smartphone Camera: A Validation Study

PubMed Central

Chan, Christy KY; Li, Christien KH; To, Olivia TL; Lai, William HS; Tse, Gary; Poh, Yukkee C; Poh, Ming-Zher

2017-01-01

Background Modern smartphones allow measurement of heart rate (HR) by detecting pulsatile photoplethysmographic (PPG) signals with built-in cameras from the fingertips or the face, without physical contact, by extracting subtle beat-to-beat variations of skin color. Objective The objective of our study was to evaluate the accuracy of HR measurements at rest and after exercise using a smartphone-based PPG detection app. Methods A total of 40 healthy participants (20 men; mean age 24.7, SD 5.2 years; von Luschan skin color range 14-27) underwent treadmill exercise using the Bruce protocol. We recorded simultaneous PPG signals for each participant by having them (1) facing the front camera and (2) placing their index fingertip over an iPhone’s back camera. We analyzed the PPG signals from the Cardiio-Heart Rate Monitor + 7 Minute Workout (Cardiio) smartphone app for HR measurements compared with a continuous 12-lead electrocardiogram (ECG) as the reference. Recordings of 20 seconds’ duration each were acquired at rest, and immediately after moderate- (50%-70% maximum HR) and vigorous- (70%-85% maximum HR) intensity exercise, and repeated successively until return to resting HR. We used Bland-Altman plots to examine agreement between ECG and PPG-estimated HR. The accuracy criterion was root mean square error (RMSE) ≤5 beats/min or ≤10%, whichever was greater, according to the American National Standards Institute/Association for the Advancement of Medical Instrumentation EC-13 standard. Results We analyzed a total of 631 fingertip and 626 facial PPG measurements. Fingertip PPG-estimated HRs were strongly correlated with resting ECG HR (r=.997, RMSE=1.03 beats/min or 1.40%), postmoderate-intensity exercise (r=.994, RMSE=2.15 beats/min or 2.53%), and postvigorous-intensity exercise HR (r=.995, RMSE=2.01 beats/min or 1.93%). The correlation of facial PPG-estimated HR was stronger with resting ECG HR (r=.997, RMSE=1.02 beats/min or 1.44%) than with postmoderate

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

Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks.

PubMed

Smitha, K A; Akhil Raja, K; Arun, K M; Rajesh, P G; Thomas, Bejoy; Kapilamoorthy, T R; Kesavadas, Chandrasekharan

2017-08-01

The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.

Accurate ECG diagnosis of atrial tachyarrhythmias using quantitative analysis: a prospective diagnostic and cost-effectiveness study.

PubMed

Krummen, David E; Patel, Mitul; Nguyen, Hong; Ho, Gordon; Kazi, Dhruv S; Clopton, Paul; Holland, Marian C; Greenberg, Scott L; Feld, Gregory K; Faddis, Mitchell N; Narayan, Sanjiv M

2010-11-01

Quantitative ECG Analysis. Optimal atrial tachyarrhythmia management is facilitated by accurate electrocardiogram interpretation, yet typical atrial flutter (AFl) may present without sawtooth F-waves or RR regularity, and atrial fibrillation (AF) may be difficult to separate from atypical AFl or rapid focal atrial tachycardia (AT). We analyzed whether improved diagnostic accuracy using a validated analysis tool significantly impacts costs and patient care. We performed a prospective, blinded, multicenter study using a novel quantitative computerized algorithm to identify atrial tachyarrhythmia mechanism from the surface ECG in patients referred for electrophysiology study (EPS). In 122 consecutive patients (age 60 ± 12 years) referred for EPS, 91 sustained atrial tachyarrhythmias were studied. ECGs were also interpreted by 9 physicians from 3 specialties for comparison and to allow healthcare system modeling. Diagnostic accuracy was compared to the diagnosis at EPS. A Markov model was used to estimate the impact of improved arrhythmia diagnosis. We found 13% of typical AFl ECGs had neither sawtooth flutter waves nor RR regularity, and were misdiagnosed by the majority of clinicians (0/6 correctly diagnosed by consensus visual interpretation) but correctly by quantitative analysis in 83% (5/6, P = 0.03). AF diagnosis was also improved through use of the algorithm (92%) versus visual interpretation (primary care: 76%, P < 0.01). Economically, we found that these improvements in diagnostic accuracy resulted in an average cost-savings of $1,303 and 0.007 quality-adjusted-life-years per patient. Typical AFl and AF are frequently misdiagnosed using visual criteria. Quantitative analysis improves diagnostic accuracy and results in improved healthcare costs and patient outcomes. © 2010 Wiley Periodicals, Inc.

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.

Central sleep apnea detection from ECG-derived respiratory signals. Application of multivariate recurrence plot analysis.

PubMed

Maier, C; Dickhaus, H

2010-01-01

This study examines the suitability of recurrence plot analysis for the problem of central sleep apnea (CSA) detection and delineation from ECG-derived respiratory (EDR) signals. A parameter describing the average length of vertical line structures in recurrence plots is calculated at a time resolution of 1 s as 'instantaneous trapping time'. Threshold comparison of this parameter is used to detect ongoing CSA. In data from 26 patients (duration 208 h) we assessed sensitivity for detection of CSA and mixed apnea (MSA) events by comparing the results obtained from 8-channel Holter ECGs to the annotations (860 CSA, 480 MSA) of simultaneously registered polysomnograms. Multivariate combination of the EDR from different ECG leads improved the detection accuracy significantly. When all eight leads were considered, an average instantaneous vertical line length above 5 correctly identified 1126 of the 1340 events (sensitivity 84%) with a total number of 1881 positive detections. We conclude that recurrence plot analysis is a promising tool for detection and delineation of CSA epochs from EDR signals with high time resolution. Moreover, the approach is likewise applicable to directly measured respiratory signals.

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).

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.

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.

[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.

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.

[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.

Resting and Postexercise Heart Rate Detection From Fingertip and Facial Photoplethysmography Using a Smartphone Camera: A Validation Study.

PubMed

Yan, Bryan P; Chan, Christy Ky; Li, Christien Kh; To, Olivia Tl; Lai, William Hs; Tse, Gary; Poh, Yukkee C; Poh, Ming-Zher

2017-03-13

Modern smartphones allow measurement of heart rate (HR) by detecting pulsatile photoplethysmographic (PPG) signals with built-in cameras from the fingertips or the face, without physical contact, by extracting subtle beat-to-beat variations of skin color. The objective of our study was to evaluate the accuracy of HR measurements at rest and after exercise using a smartphone-based PPG detection app. A total of 40 healthy participants (20 men; mean age 24.7, SD 5.2 years; von Luschan skin color range 14-27) underwent treadmill exercise using the Bruce protocol. We recorded simultaneous PPG signals for each participant by having them (1) facing the front camera and (2) placing their index fingertip over an iPhone's back camera. We analyzed the PPG signals from the Cardiio-Heart Rate Monitor + 7 Minute Workout (Cardiio) smartphone app for HR measurements compared with a continuous 12-lead electrocardiogram (ECG) as the reference. Recordings of 20 seconds' duration each were acquired at rest, and immediately after moderate- (50%-70% maximum HR) and vigorous- (70%-85% maximum HR) intensity exercise, and repeated successively until return to resting HR. We used Bland-Altman plots to examine agreement between ECG and PPG-estimated HR. The accuracy criterion was root mean square error (RMSE) ≤5 beats/min or ≤10%, whichever was greater, according to the American National Standards Institute/Association for the Advancement of Medical Instrumentation EC-13 standard. We analyzed a total of 631 fingertip and 626 facial PPG measurements. Fingertip PPG-estimated HRs were strongly correlated with resting ECG HR (r=.997, RMSE=1.03 beats/min or 1.40%), postmoderate-intensity exercise (r=.994, RMSE=2.15 beats/min or 2.53%), and postvigorous-intensity exercise HR (r=.995, RMSE=2.01 beats/min or 1.93%). The correlation of facial PPG-estimated HR was stronger with resting ECG HR (r=.997, RMSE=1.02 beats/min or 1.44%) than with postmoderate-intensity exercise (r=.982, RMSE=3.68 beats

EEG and ECG changes during simulator operation reflect mental workload and vigilance.

PubMed

Dussault, Caroline; Jouanin, Jean-Claude; Philippe, Matthieu; Guezennec, Charles-Yannick

2005-04-01

Performing mission tasks in a simulator influences many neurophysiological measures. Quantitative assessments of electroencephalography (EEG) and electrocardiography (ECG) have made it possible to develop indicators of mental workload and to estimate relative physiological responses to cognitive requirements. To evaluate the effects of mental workload without actual physical risk, we studied the cortical and cardiovascular changes that occurred during simulated flight. There were 12 pilots (8 novices and 4 experts) who simulated a flight composed of 10 sequences that induced several different mental workload levels. EEG was recorded at 12 electrode sites during rest and flight sequences; ECG activity was also recorded. Subjective tests were used to evaluate anxiety and vigilance levels. Theta band activity was lower during the two simulated flight rest sequences than during visual and instrument flight sequences at central, parietal, and occipital sites (p < 0.05). On the other hand, rest sequences resulted in higher beta (at the C4 site; p < 0.05) and gamma (at the central, parietal, and occipital sites; p < 0.05) power than active segments. The mean heart rate (HR) was not significantly different during any simulated flight sequence, but HR was lower for expert subjects than for novices. The subjective tests revealed no significant anxiety and high values for vigilance levels before and during flight. The different flight sequences performed on the simulator resulted in electrophysiological changes that expressed variations in mental workload. These results corroborate those found during study of real flights, particularly during sequences requiring the heaviest mental workload.

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.

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.

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.

Metabolic, respiratory, and cardiological measurements during exercise and rest

NASA Technical Reports Server (NTRS)

1971-01-01

Low concentration effects of CO2 on metabolic respiration and circulation were measured during work and at rest. The relationship between heart rate and metabolic rate is examined, as well as calibration procedures, and rate measurement during submaximal and standard exercise tests. Alterations in acid base and electrolytes were found during exhaustive exercise, including changes in ECG and metabolic alkalosis effects.

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).

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.

Sequential Total Variation Denoising for the Extraction of Fetal ECG from Single-Channel Maternal Abdominal ECG

PubMed Central

Lee, Kwang Jin; Lee, Boreom

2016-01-01

Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR. PMID:27376296

Sequential Total Variation Denoising for the Extraction of Fetal ECG from Single-Channel Maternal Abdominal ECG.

PubMed

Lee, Kwang Jin; Lee, Boreom

2016-07-01

Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR.

Extraction of fetal ECG signal by an improved method using extended Kalman smoother framework from single channel abdominal ECG signal.

PubMed

Panigrahy, D; Sahu, P K

2017-03-01

This paper proposes a five-stage based methodology to extract the fetal electrocardiogram (FECG) from the single channel abdominal ECG using differential evolution (DE) algorithm, extended Kalman smoother (EKS) and adaptive neuro fuzzy inference system (ANFIS) framework. The heart rate of the fetus can easily be detected after estimation of the fetal ECG signal. The abdominal ECG signal contains fetal ECG signal, maternal ECG component, and noise. To estimate the fetal ECG signal from the abdominal ECG signal, removal of the noise and the maternal ECG component presented in it is necessary. The pre-processing stage is used to remove the noise from the abdominal ECG signal. The EKS framework is used to estimate the maternal ECG signal from the abdominal ECG signal. The optimized parameters of the maternal ECG components are required to develop the state and measurement equation of the EKS framework. These optimized maternal ECG parameters are selected by the differential evolution algorithm. The relationship between the maternal ECG signal and the available maternal ECG component in the abdominal ECG signal is nonlinear. To estimate the actual maternal ECG component present in the abdominal ECG signal and also to recognize this nonlinear relationship the ANFIS is used. Inputs to the ANFIS framework are the output of EKS and the pre-processed abdominal ECG signal. The fetal ECG signal is computed by subtracting the output of ANFIS from the pre-processed abdominal ECG signal. Non-invasive fetal ECG database and set A of 2013 physionet/computing in cardiology challenge database (PCDB) are used for validation of the proposed methodology. The proposed methodology shows a sensitivity of 94.21%, accuracy of 90.66%, and positive predictive value of 96.05% from the non-invasive fetal ECG database. The proposed methodology also shows a sensitivity of 91.47%, accuracy of 84.89%, and positive predictive value of 92.18% from the set A of PCDB.

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.

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.

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.

Object-oriented analysis and design of an ECG storage and retrieval system integrated with an HIS.

PubMed

Wang, C; Ohe, K; Sakurai, T; Nagase, T; Kaihara, S

1996-03-01

For a hospital information system, object-oriented methodology plays an increasingly important role, especially for the management of digitized data, e.g., the electrocardiogram, electroencephalogram, electromyogram, spirogram, X-ray, CT and histopathological images, which are not yet computerized in most hospitals. As a first step in an object-oriented approach to hospital information management and storing medical data in an object-oriented database, we connected electrocardiographs to a hospital network and established the integration of ECG storage and retrieval systems with a hospital information system. In this paper, the object-oriented analysis and design of the ECG storage and retrieval systems is reported.

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.

Is Rest Really Rest? Resting State Functional Connectivity during Rest and Motor Task Paradigms.

PubMed

Jurkiewicz, Michael T; Crawley, Adrian P; Mikulis, David J

2018-04-18

Numerous studies have identified the default mode network (DMN) within the brain of healthy individuals, which has been attributed to the ongoing mental activity of the brain during the wakeful resting-state. While engaged during specific resting-state fMRI paradigms, it remains unclear as to whether traditional block-design simple movement fMRI experiments significantly influence the default mode network or other areas. Using blood-oxygen level dependent (BOLD) fMRI we characterized the pattern of functional connectivity in healthy subjects during a resting-state paradigm and compared this to the same resting-state analysis performed on motor task data residual time courses after regressing out the task paradigm. Using seed-voxel analysis to define the DMN, the executive control network (ECN), and sensorimotor, auditory and visual networks, the resting-state analysis of the residual time courses demonstrated reduced functional connectivity in the motor network and reduced connectivity between the insula and the ECN compared to the standard resting-state datasets. Overall, performance of simple self-directed motor tasks does little to change the resting-state functional connectivity across the brain, especially in non-motor areas. This would suggest that previously acquired fMRI studies incorporating simple block-design motor tasks could be mined retrospectively for assessment of the resting-state connectivity.

The future of remote ECG monitoring systems.

PubMed

Guo, Shu-Li; Han, Li-Na; Liu, Hong-Wei; Si, Quan-Jin; Kong, De-Feng; Guo, Fu-Su

2016-09-01

Remote ECG monitoring systems are becoming commonplace medical devices for remote heart monitoring. In recent years, remote ECG monitoring systems have been applied in the monitoring of various kinds of heart diseases, and the quality of the transmission and reception of the ECG signals during remote process kept advancing. However, there remains accompanying challenges. This report focuses on the three components of the remote ECG monitoring system: patient (the end user), the doctor workstation, and the remote server, reviewing and evaluating the imminent challenges on the wearable systems, packet loss in remote transmission, portable ECG monitoring system, patient ECG data collection system, and ECG signals transmission including real-time processing ST segment, R wave, RR interval and QRS wave, etc. This paper tries to clarify the future developmental strategies of the ECG remote monitoring, which can be helpful in guiding the research and development of remote ECG monitoring.

Sparse dictionary learning for resting-state fMRI analysis

NASA Astrophysics Data System (ADS)

Lee, Kangjoo; Han, Paul Kyu; Ye, Jong Chul

2011-09-01

Recently, there has been increased interest in the usage of neuroimaging techniques to investigate what happens in the brain at rest. Functional imaging studies have revealed that the default-mode network activity is disrupted in Alzheimer's disease (AD). However, there is no consensus, as yet, on the choice of analysis method for the application of resting-state analysis for disease classification. This paper proposes a novel compressed sensing based resting-state fMRI analysis tool called Sparse-SPM. As the brain's functional systems has shown to have features of complex networks according to graph theoretical analysis, we apply a graph model to represent a sparse combination of information flows in complex network perspectives. In particular, a new concept of spatially adaptive design matrix has been proposed by implementing sparse dictionary learning based on sparsity. The proposed approach shows better performance compared to other conventional methods, such as independent component analysis (ICA) and seed-based approach, in classifying the AD patients from normal using resting-state analysis.

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

Fully Textile, PEDOT:PSS Based Electrodes for Wearable ECG Monitoring Systems.

PubMed

Pani, Danilo; Dessi, Alessia; Saenz-Cogollo, Jose F; Barabino, Gianluca; Fraboni, Beatrice; Bonfiglio, Annalisa

2016-03-01

To evaluate a novel kind of textile electrodes based on woven fabrics treated with PSS, through an easy fabrication process, testing these electrodes for biopotential recordings. Fabrication is based on raw fabric soaking in PSS using a second dopant, squeezing and annealing. The electrodes have been tested on human volunteers, in terms of both skin contact impedance and quality of the ECG signals recorded at rest and during physical activity (power spectral density, baseline wandering, QRS detectability, and broadband noise). The electrodes are able to operate in both wet and dry conditions. Dry electrodes are more prone to noise artifacts, especially during physical exercise and mainly due to the unstable contact between the electrode and the skin. Wet (saline) electrodes present a stable and reproducible behavior, which is comparable or better than that of traditional disposable gelled Ag/AgCl electrodes. The achieved results reveal the capability of this kind of electrodes to work without the electrolyte, providing a valuable interface with the skin, due to mixed electronic and ionic conductivity of PSS. These electrodes can be effectively used for acquiring ECG signals. Textile electrodes based on PSS represent an important milestone in wearable monitoring, as they present an easy and reproducible fabrication process, very good performance in wet and dry (at rest) conditions and a superior level of comfort with respect to textile electrodes proposed so far. This paves the way to their integration into smart garments.

Exploring Neuro-Physiological Correlates of Drivers' Mental Fatigue Caused by Sleep Deprivation Using Simultaneous EEG, ECG, and fNIRS Data

PubMed Central

Ahn, Sangtae; Nguyen, Thien; Jang, Hyojung; Kim, Jae G.; Jun, Sung C.

2016-01-01

Investigations of the neuro-physiological correlates of mental loads, or states, have attracted significant attention recently, as it is particularly important to evaluate mental fatigue in drivers operating a motor vehicle. In this research, we collected multimodal EEG/ECG/EOG and fNIRS data simultaneously to develop algorithms to explore neuro-physiological correlates of drivers' mental states. Each subject performed simulated driving under two different conditions (well-rested and sleep-deprived) on different days. During the experiment, we used 68 electrodes for EEG/ECG/EOG and 8 channels for fNIRS recordings. We extracted the prominent features of each modality to distinguish between the well-rested and sleep-deprived conditions, and all multimodal features, except EOG, were combined to quantify mental fatigue during driving. Finally, a novel driving condition level (DCL) was proposed that distinguished clearly between the features of well-rested and sleep-deprived conditions. This proposed DCL measure may be applicable to real-time monitoring of the mental states of vehicle drivers. Further, the combination of methods based on each classifier yielded substantial improvements in the classification accuracy between these two conditions. PMID:27242483

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

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.

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.

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.

Deep Learning for ECG Classification

NASA Astrophysics Data System (ADS)

Pyakillya, B.; Kazachenko, N.; Mikhailovsky, N.

2017-10-01

The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG data. However, the main disadvantages of these ML results is use of heuristic hand-crafted or engineered features with shallow feature learning architectures. The problem relies in the possibility not to find most appropriate features which will give high classification accuracy in this ECG problem. One of the proposing solution is to use deep learning architectures where first layers of convolutional neurons behave as feature extractors and in the end some fully-connected (FCN) layers are used for making final decision about ECG classes. In this work the deep learning architecture with 1D convolutional layers and FCN layers for ECG classification is presented and some classification results are showed.

Fetal ECG Extraction From Maternal Body Surface Measurement Using Independent Component Analysis

DTIC Science & Technology

2001-10-25

Ibaraki 305-0901, Japan Abstract – A method applying independent component analysis (ICA) to detect the electrocardiogram of a prenatal cattle foetus is...monitoring the health status of an unborn cattle foetus is indispensable in preventing natural abortion and premature birth [3]. One of the applicable...and Y. Honda, “ECG and Heart Rate Detection of Prenatal Cattle Foetus Using Adaptive Digital Filtering,” World Congress on Med. Phys.& Biomed. Eng., Chicago TU-CXH-75, pp. 1-4, 2000.

A novel algorithm for Bluetooth ECG.

PubMed

Pandya, Utpal T; Desai, Uday B

2012-11-01

In wireless transmission of ECG, data latency will be significant when battery power level and data transmission distance are not maintained. In applications like home monitoring or personalized care, to overcome the joint effect of previous issues of wireless transmission and other ECG measurement noises, a novel filtering strategy is required. Here, a novel algorithm, identified as peak rejection adaptive sampling modified moving average (PRASMMA) algorithm for wireless ECG is introduced. This algorithm first removes error in bit pattern of received data if occurred in wireless transmission and then removes baseline drift. Afterward, a modified moving average is implemented except in the region of each QRS complexes. The algorithm also sets its filtering parameters according to different sampling rate selected for acquisition of signals. To demonstrate the work, a prototyped Bluetooth-based ECG module is used to capture ECG with different sampling rate and in different position of patient. This module transmits ECG wirelessly to Bluetooth-enabled devices where the PRASMMA algorithm is applied on captured ECG. The performance of PRASMMA algorithm is compared with moving average and S-Golay algorithms visually as well as numerically. The results show that the PRASMMA algorithm can significantly improve the ECG reconstruction by efficiently removing the noise and its use can be extended to any parameters where peaks are importance for diagnostic purpose.

Standard-compliant real-time transmission of ECGs: harmonization of ISO/IEEE 11073-PHD and SCP-ECG.

PubMed

Trigo, Jesús D; Chiarugi, Franco; Alesanco, Alvaro; Martínez-Espronceda, Miguel; Chronaki, Catherine E; Escayola, Javier; Martínez, Ignacio; García, José

2009-01-01

Ambient assisted living and integrated care in an aging society is based on the vision of the lifelong Electronic Health Record calling for HealthCare Information Systems and medical device interoperability. For medical devices this aim can be achieved by the consistent implementation of harmonized international interoperability standards. The ISO/IEEE 11073 (x73) family of standards is a reference standard for medical device interoperability. In its Personal Health Device (PHD) version several devices have been included, but an ECG device specialization is not yet available. On the other hand, the SCP-ECG standard for short-term diagnostic ECGs (EN1064) has been recently approved as an international standard ISO/IEEE 11073-91064:2009. In this paper, the relationships between a proposed x73-PHD model for an ECG device and the fields of the SCP-ECG standard are investigated. A proof-of-concept implementation of the proposed x73-PHD ECG model is also presented, identifying open issues to be addressed by standards development for the wider interoperability adoption of x73-PHD standards.

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.

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.

Rest and the associated benefits in restorative sleep: a concept analysis.

PubMed

Helvig, Ashley; Wade, Sonya; Hunter-Eades, Lee

2016-01-01

To report an analysis of the concept of rest. Consistency in the literature to describe the concept and use of rest is limited. Concept analysis may be advantageous in rendering an operational definition in the health care setting. This analysis is important to examine the concept of rest for structure and function to promote an understanding of the phenomenon. Rest is a vital component of restorative sleep which has implications for physical, mental and spiritual well-being. Concept analysis. A literature search was conducted in the following databases: PubMed, CINAHL, Medline, ProQuest and an online Internet search with the majority of articles published between 1995-2015. This concept analysis was implemented using the eight step approach developed by Walker and Avant. In health care, rest incorporates the cessation of activity used to promote physical and mental health. Defining attributes of rest include a pathway to calm, inner tranquillity and mental health; base of support; and stillness. Antecedents for rest are time, suitable environment and willingness. Resulting consequences include renewed physical energy, mental clarity and improved health. Rest is a concept that is used frequently in the discipline of nursing but also in various other disciplines. Rest is a basic necessity for restorative sleep to enhance well-being through the restoration of the body, mind and spirit. Defining the concept of rest in the practice of patient care is necessary for consistent use of the term in the development of holistic, patient-centred therapies. © 2015 John Wiley & Sons Ltd.

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.

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.

Beat-to-beat ECG restitution: A review and proposal for a new biomarker to assess cardiac stress and ventricular tachyarrhythmia vulnerability.

PubMed

Fossa, Anthony A

2017-09-01

Cardiac restitution is the ability of the heart to recover from one beat to the next. Ventricular arrhythmia vulnerability can occur when the heart does not properly adjust to sudden changes in rate or in hemodynamics leading to excessive temporal and/or spatial heterogeneity in conduction or repolarization. Restitution has historically been used to study, by invasive means, the dynamics of the relationship between action potential duration (APD) and diastolic interval (DI) in sedated subjects using various pacing protocols. Even though the analogous measures of APD and DI can be obtained using the surface ECG to acquire the respective QT and TQ intervals for ECG restitution, this methodology has not been widely adopted for a number of reasons. Recent development of more advanced software algorithms enables ECG intervals to be measured accurately, on a continuous beat-to-beat basis, in an automated manner, and under highly dynamic conditions (i.e., ambulatory or exercise) providing information beyond that available in the typical resting state. Current breakthroughs in ECG technology will allow ECG restitution measures to become a practical approach for providing quantitative measures of the risks for ventricular arrhythmias as well as cardiac stress in general. In addition to a review of the underlying principles and caveats of ECG restitution, a new approach toward an advancement of more integrated restitution biomarkers is proposed. © 2017 Wiley Periodicals, Inc.

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.

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."

Reliability and Reproducibility of Advanced ECG Parameters in Month-to-Month and Year-to-Year Recordings in Healthy Subjects

NASA Technical Reports Server (NTRS)

Starc, Vito; Abughazaleh, Ahmed S.; Schlegel, Todd T.

2014-01-01

Advanced resting ECG parameters such the spatial mean QRS-T angle and the QT variability index (QTVI) have important diagnostic and prognostic utility, but their reliability and reproducibility (R&R) are not well characterized. We hypothesized that the spatial QRS-T angle would have relatively higher R&R than parameters such as QTVI that are more responsive to transient changes in the autonomic nervous system. The R&R of several conventional and advanced ECG para-meters were studied via intraclass correlation coefficients (ICCs) and coefficients of variation (CVs) in: (1) 15 supine healthy subjects from month-to-month; (2) 27 supine healthy subjects from year-to-year; and (3) 25 subjects after transition from the supine to the seated posture. As hypothesized, for the spatial mean QRS-T angle and many conventional ECG parameters, ICCs we-re higher, and CVs lower than QTVI, suggesting that the former parameters are more reliable and reproducible.

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.

Nonlinear time series analysis of electrocardiograms

NASA Astrophysics Data System (ADS)

Bezerianos, A.; Bountis, T.; Papaioannou, G.; Polydoropoulos, P.

1995-03-01

In recent years there has been an increasing number of papers in the literature, applying the methods and techniques of Nonlinear Dynamics to the time series of electrical activity in normal electrocardiograms (ECGs) of various human subjects. Most of these studies are based primarily on correlation dimension estimates, and conclude that the dynamics of the ECG signal is deterministic and occurs on a chaotic attractor, whose dimension can distinguish between healthy and severely malfunctioning cases. In this paper, we first demonstrate that correlation dimension calculations must be used with care, as they do not always yield reliable estimates of the attractor's ``dimension.'' We then carry out a number of additional tests (time differencing, smoothing, principal component analysis, surrogate data analysis, etc.) on the ECGs of three ``normal'' subjects and three ``heavy smokers'' at rest and after mild exercising, whose cardiac rhythms look very similar. Our main conclusion is that no major dynamical differences are evident in these signals. A preliminary estimate of three to four basic variables governing the dynamics (based on correlation dimension calculations) is updated to five to six, when temporal correlations between points are removed. Finally, in almost all cases, the transition between resting and mild exercising seems to imply a small increase in the complexity of cardiac dynamics.

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.

Cost-effectiveness of pre-participation screening of athletes with ECG in Europe and Algeria.

PubMed

Assanelli, Deodato; Levaggi, Rosella; Carré, François; Sharma, Sanjay; Deligiannis, Asterios; Mellwig, Klaus Peter; Tahmi, Mohamed; Vinetti, Giovanni; Aliverti, Paola

2015-03-01

The aim of this study is to evaluate the cost-effectiveness of ECG in combination with family and personal history and physical examination in order to detect cardiovascular diseases that might cause sudden death in athletes. The study was conducted on a cohort of 6,634, mainly young professional and recreational athletes, 1,071 from Algeria and 5,563 from Europe (France, Germany and Greece). Each athlete underwent medical history, physical examination, and resting 12-lead ECG. 293 athletes (4.4 %), 149 in Europe (2.7 %) and 144 in Algeria (13.4 %) required further tests, and 56 were diagnosed with cardiovascular disease and thus disqualified. The cost-effectiveness ratio (CER) was calculated as the ratio between the cost of screening and the number of statistical life-years saved by the intervention. The estimated reduced risk of death deriving from treatment or disqualification resulted in the saving of 79.1 statistical life-years in Europe and 136.3 in Algeria. CER of screening was 4,071 purchasing-power-parity-adjusted US dollars ($PPP) in Europe and 582 $PPP in Algeria. The results of this study strongly support the utilisation of 12-lead ECG in the pre-participation screening of young athletes, especially in countries where secondary preventive care is not highly developed.

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.

High Resolution ECG for Evaluation of QT Interval Variability during Exposure to Acute Hypoxia

NASA Technical Reports Server (NTRS)

Zupet, P.; Finderle, Z.; Schlegel, Todd T.; Starc, V.

2010-01-01

Ventricular repolarization instability as quantified by the index of QT interval variability (QTVI) is one of the best predictors for risk of malignant ventricular arrhythmias and sudden cardiac death. Because it is difficult to appropriately monitor early signs of organ dysfunction at high altitude, we investigated whether high resolution advanced ECG (HR-ECG) analysis might be helpful as a non-invasive and easy-to-use tool for evaluating the risk of cardiac arrhythmias during exposure to acute hypoxia. 19 non-acclimatized healthy trained alpinists (age 37, 8 plus or minus 4,7 years) participated in the study. Five-minute high-resolution 12-lead electrocardiograms (ECGs) were recorded (Cardiosoft) in each subject at rest in the supine position breathing room air and then after breathing 12.5% oxygen for 30 min. For beat-to-beat RR and QT variability, the program of Starc was utilized to derive standard time domain measures such as root mean square of the successive interval difference (rMSSD) of RRV and QTV, the corrected QT interval (QTc) and the QTVI in lead II. Changes were evaluated with paired-samples t-test with p-values less than 0.05 considered statistically significant. As expected, the RR interval and its variability both decreased with increasing altitude, with p = 0.000 and p = 0.005, respectively. Significant increases were found in both the rMSSDQT and the QTVI in lead II, with p = 0.002 and p = 0.003, respectively. There was no change in QTc interval length (p = non significant). QT variability parameters may be useful for evaluating changes in ventricular repolarization caused by hypoxia. These changes might be driven by increases in sympathetic nervous system activity at ventricular level.

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

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.

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.

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

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

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.

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.

Screening for Cardiovascular Disease Risk With Resting or Exercise Electrocardiography: Evidence Report and Systematic Review for the US Preventive Services Task Force.

PubMed

Jonas, Daniel E; Reddy, Shivani; Middleton, Jennifer Cook; Barclay, Colleen; Green, Joshua; Baker, Claire; Asher, Gary N

2018-06-12

Cardiovascular disease (CVD) is the leading cause of death in the United States. To review the evidence on screening asymptomatic adults for CVD risk using electrocardiography (ECG) to inform the US Preventive Services Task Force. MEDLINE, Cochrane Library, and trial registries through May 2017; references; experts; literature surveillance through April 4, 2018. English-language randomized clinical trials (RCTs); prospective cohort studies reporting reclassification, calibration, or discrimination that compared risk assessment using ECG plus traditional risk factors vs traditional risk factors alone. For harms, additional study designs were eligible. Studies of persons with symptoms or a CVD diagnosis were excluded. Dual review of abstracts, full-text articles, and study quality; qualitative synthesis of findings. Mortality, cardiovascular events, reclassification, calibration, discrimination, and harms. Sixteen studies were included (N = 77 140). Two RCTs (n = 1151) found no significant improvement for screening with exercise ECG (vs no screening) in adults aged 50 to 75 years with diabetes for the primary cardiovascular composite outcomes (hazard ratios, 1.00 [95% CI, 0.59-1.71] and 0.85 [95% CI, 0.39-1.84] for each study). No RCTs evaluated screening with resting ECG. Evidence from 5 cohort studies (n = 9582) showed that adding exercise ECG to traditional risk factors such as age, sex, current smoking, diabetes, total cholesterol level, and high-density lipoprotein cholesterol level produced small improvements in discrimination (absolute improvements in area under the curve [AUC] or C statistics, 0.02-0.03, reported by 3 studies); whether calibration or appropriate risk classification improves is uncertain. Evidence from 9 cohort studies (n = 66 407) showed that adding resting ECG to traditional risk factors produced small improvements in discrimination (absolute improvement in AUC or C statistics, 0.001-0.05) and appropriate risk

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.

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.

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

Human Identification by Cross-Correlation and Pattern Matching of Personalized Heartbeat: Influence of ECG Leads and Reference Database Size.

PubMed

Jekova, Irena; Krasteva, Vessela; Schmid, Ramun

2018-01-27

Human identification (ID) is a biometric task, comparing single input sample to many stored templates to identify an individual in a reference database. This paper aims to present the perspectives of personalized heartbeat pattern for reliable ECG-based identification. The investigations are using a database with 460 pairs of 12-lead resting electrocardiograms (ECG) with 10-s durations recorded at time-instants T1 and T2 > T1 + 1 year. Intra-subject long-term ECG stability and inter-subject variability of personalized PQRST (500 ms) and QRS (100 ms) patterns is quantified via cross-correlation, amplitude ratio and pattern matching between T1 and T2 using 7 features × 12-leads. Single and multi-lead ID models are trained on the first 230 ECG pairs. Their validation on 10, 20, ... 230 reference subjects (RS) from the remaining 230 ECG pairs shows: (i) two best single-lead ID models using lead II for a small population RS = (10-140) with identification accuracy AccID = (89.4-67.2)% and aVF for a large population RS = (140-230) with AccID = (67.2-63.9)%; (ii) better performance of the 6-lead limb vs. the 6-lead chest ID model-(91.4-76.1)% vs. (90.9-70)% for RS = (10-230); (iii) best performance of the 12-lead ID model-(98.4-87.4)% for RS = (10-230). The tolerable reference database size, keeping AccID > 80%, is RS = 30 in the single-lead ID scenario (II); RS = 50 (6 chest leads); RS = 100 (6 limb leads), RS > 230-maximal population in this study (12-lead ECG).

Complex network analysis of resting-state fMRI of the brain.

PubMed

Anwar, Abdul Rauf; Hashmy, Muhammad Yousaf; Imran, Bilal; Riaz, Muhammad Hussnain; Mehdi, Sabtain Muhammad Muntazir; Muthalib, Makii; Perrey, Stephane; Deuschl, Gunther; Groppa, Sergiu; Muthuraman, Muthuraman

2016-08-01

Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.

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.

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

Improving the quality of the ECG signal by filtering in wavelet transform domain

NASA Astrophysics Data System (ADS)

DzierŻak, RóŻa; Surtel, Wojciech; Dzida, Grzegorz; Maciejewski, Marcin

2016-09-01

The article concerns the research methods of noise reduction occurring in the ECG signals. The method is based on the use of filtration in wavelet transform domain. The study was conducted on two types of signal - received during the rest of the patient and obtained during physical activity. For each of the signals 3 types of filtration were used. The study was designed to determine the effectiveness of various wavelets for de-noising signals obtained in both cases. The results confirm the suitability of the method for improving the quality of the electrocardiogram in case of both types of signals.

Cardiovascular screening in adolescents and young adults: a prospective study comparing the Pre-participation Physical Evaluation Monograph 4th Edition and ECG

PubMed Central

Fudge, Jessie; Harmon, Kimberly G; Owens, David S; Prutkin, Jordan M; Salerno, Jack C; Asif, Irfan M; Haruta, Alison; Pelto, Hank; Rao, Ashwin L; Toresdahl, Brett G; Drezner, Jonathan A

2015-01-01

Background This study compares the accuracy of cardiovascular screening in active adolescents and young adults using a standardised history, physical examination and resting 12-lead ECG. Methods Participants were prospectively screened using a standardised questionnaire based on the Pre-participation Physical Evaluation Monograph 4th Edition (PPE-4), physical examination and ECG interpreted using modern standards. Participants with abnormal findings had focused echocardiography and further evaluation. Primary outcomes included disorders associated with sudden cardiac arrest (SCA). Results From September 2010 to July 2011, 1339 participants underwent screening: age 13–24 (mean 16) years, 49% male, 68% Caucasian, 17% African-American and 1071 (80%) participating in organised sports. Abnormal history responses were reported on 916 (68%) questionnaires. After physician review, 495/ 916 (54%) participants with positive questionnaires were thought to have non-cardiac symptoms and/or a benign family history and did not warrant additional evaluation. Physical examination was abnormal in 124 (9.3%) participants, and 72 (5.4%) had ECG abnormalities. Echocardiograms were performed in 586 (44%) participants for abnormal history (31%), physical examination (8%) or ECG (5%). Five participants (0.4%) were identified with a disorder associated with SCA, all with ECG-detected Wolff-Parkinson-White. The false-positive rates for history, physical examination and ECG were 31.3%, 9.3% and 5%, respectively. Conclusions A standardised history and physical examination using the PPE-4 yields a high false-positive rate in a young active population with limited sensitivity to identify those at risk for SCA. ECG screening has a low false-positive rate using modern interpretation standards and improves detection of primary electrical disease at risk of SCA. PMID:24948082

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

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

Economic analysis of the use of coronary calcium scoring as an alternative to stress ECG in the non-invasive diagnosis of coronary artery disease.

PubMed

Raman, Vivek; McWilliams, Eric T M; Holmberg, Stephen R M; Miles, Ken

2012-03-01

To conduct an economic analysis (EA) of coronary calcium scoring (CCS) using a 0 score, as alternative to stress electrocardiography (sECG) in diagnosing coronary artery disease (CAD). A decision tree was constructed to compare four strategies for investigation of suspected CAD previously assessed in the formulation of clinical guidelines for the United Kingdom (UK) to two new strategies incorporating CCS. Sensitivity (96%; 95% CI 95.4-96.4%) and specificity (40%; 95% CI 38.7-41.4%) values for CCS were derived from a meta-analysis of 10,760 patients. Other input variables were obtained from a previous EA and average prices for hospital procedures in the UK. A threshold of £30,000/Quality-adjusted Life Year (QALY) was considered cost-effective. Using net monetary benefit calculations, CCS-based strategies were found to be cost-effective compared to sECG equivalents at all assessed prevalence of CAD. Using CCS prior to myocardial perfusion scintigraphy (MPS) and catheter angiography (CA) was found to be cost-effective at pre-test probabilities (PTP) below 30%. Adoption of CCS as an alternative to sECG in investigating suspected stable angina in low PTP population (<30%) would be cost-effective. In patients with PTP of CAD >30%, proceeding to MPS or CA would be more cost-effective than performing either CCS or sECG. Coronary calcium scoring (CCS) is useful for assessing coronary artery atherosclerosis It can be performed with multi-detector CT, which is now widely available It plays a role in excluding disease in suspected stable angina Our study assesses its role in this setting as alternative to stress-ECG Adoption of CCS as an alternative to sECG could prove cost-effective.

Analysis of the QRS complex for apnea-bradycardia characterization in preterm infants

PubMed Central

Altuve, Miguel; Carrault, Guy; Cruz, Julio; Beuchée, Alain; Pladys, Patrick; Hernandez, Alfredo I.

2009-01-01

This work presents an analysis of the information content of new features derived from the electrocardiogram (ECG) for the characterization of apnea-bradycardia events in preterm infants. Automatic beat detection and segmentation methods have been adapted to the ECG signals from preterm infants, through the application of two evolutionary algorithms. ECG data acquired from 32 preterm infants with persistent apnea-bradycardia have been used for quantitative evaluation. The adaptation procedure led to an improved sensitivity and positive predictive value, and a reduced jitter for the detection of the R-wave, QRS onset, QRS offset, and iso-electric level. Additionally, time series representing the RR interval, R-wave amplitude and QRS duration, were automatically extracted for periods at rest, before, during and after apnea-bradycardia episodes. Significant variations (p<0.05) were observed for all time-series when comparing the difference between values at rest versus values just before the bradycardia event, with the difference between values at rest versus values during the bradycardia event. These results reveal changes in the R-wave amplitude and QRS duration, appearing at the onset and termination of apnea-bradycardia episodes, which could be potentially useful for the early detection and characterization of these episodes. PMID:19963984

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.

Is computer-assisted instruction more effective than other educational methods in achieving ECG competence among medical students and residents? Protocol for a systematic review and meta-analysis.

PubMed

Viljoen, Charle André; Scott Millar, Rob; Engel, Mark E; Shelton, Mary; Burch, Vanessa

2017-12-26

Although ECG interpretation is an essential skill in clinical medicine, medical students and residents often lack ECG competence. Novel teaching methods are increasingly being implemented and investigated to improve ECG training. Computer-assisted instruction is one such method under investigation; however, its efficacy in achieving better ECG competence among medical students and residents remains uncertain. This article describes the protocol for a systematic review and meta-analysis that will compare the effectiveness of computer-assisted instruction with other teaching methods used for the ECG training of medical students and residents. Only studies with a comparative research design will be considered. Articles will be searched for in electronic databases (PubMed, Scopus, Web of Science, Academic Search Premier, CINAHL, PsycINFO, Education Resources Information Center, Africa-Wide Information and Teacher Reference Center). In addition, we will review citation indexes and conduct a grey literature search. Data extraction will be done on articles that met the predefined eligibility criteria. A descriptive analysis of the different teaching modalities will be provided and their educational impact will be assessed in terms of effect size and the modified version of Kirkpatrick framework for the evaluation of educational interventions. This systematic review aims to provide evidence as to whether computer-assisted instruction is an effective teaching modality for ECG training. It is hoped that the information garnered from this systematic review will assist in future curricular development and improve ECG training. As this research is a systematic review of published literature, ethical approval is not required. The results will be reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis statement and will be submitted to a peer-reviewed journal. The protocol and systematic review will be included in a PhD dissertation. CRD

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.

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.

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

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.

Continuous ECG monitoring for tracking down atrial fibrillation after stroke: Holter or automated analysis strategy?

PubMed

Suissa, Laurent; Lachaud, Sylvain; Mahagne, Marie-Hélène

2014-01-01

Tracking down atrial fibrillation (AF) in the stroke unit is a relevant challenge for the prevention of recurrent AF-related stroke. The optimal terms of use of continuous ECG monitoring (CEM) are unknown. We compared 24-hour routine Holter ECG with two different CEM analysis strategies for AF detection. We prospectively enrolled consecutive ischemic stroke patients. All AF-naïve patients received CEM during hospitalization. Two methods for reading CEM data were compared: manual analysis using the Holter function (hCEM) and semiautomated analysis using software (aCEM). The McNemar test was used to compare AF detection rates. Of the 362 patients included, 58 (16.0%) were non-AF-naïve patients and 304 were AF-naïve patients. AF-Naïve patients underwent CEM with a median duration of 5.3 days (3.4-9.7). We detected 22 new AF cases (7.2%) with first-24-hour hCEM, 31 (10.2%) with aCEM, and 42 (13.8%) with hCEM. hCEM and aCEM both significantly increased the AF detection rate compared to first-24-hour hCEM. hCEM detected more new AF cases than aCEM (+3.6%, p = 0.003). In stroke patients, early and prolonged aCEM and hCEM both increase the AF detection rate compared to first-24-hour hCEM. hCEM gives the best AF detection rate. We suggest that in aCEM, detection based only on the ventricular rhythm analysis explains its lower specificity and sensitivity. © 2014 S. Karger AG, Basel.

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.

Accuracy of pulse oximeters in estimating heart rate at rest and during exercise.

PubMed Central

Iyriboz, Y; Powers, S; Morrow, J; Ayers, D; Landry, G

1991-01-01

Pulse oximeters are being widely used for non-invasive, simultaneous assessment of haemoglobin oxygen saturation. They are reliable, accurate, relatively inexpensive and portable. Pulse oximeters are often used for estimating heart rate at rest and during exercise. However, at present the data available to validate their use as heart rate monitors are not sufficient. We evaluated the accuracy of two oximeters (Radiometer, ear and finger probe; Ohmeda 3700, ear probe) in monitoring heart rate during incremental exercise by comparing the pulse oximeters with simultaneous ECG readings. Data were collected on eight men (713 heart rate readings) during graded cycle ergometer and treadmill exercise to volitional fatigue. Analysis by linear regression revealed that general oximeter readings significantly correlated with those of ECG (r = 0.91, P less than 0.0001). However, comparison of heart rate at each level of work showed that oximeter readings significantly (P less than 0.05) under-estimated rates above 155 beats/min. These results indicate that the use of pulse oximeters as heart rate monitors during strenuous exercise is questionable. This inaccuracy may well originate from the instability of the probes, sweating, other artefacts during exercise, and measurement of different components in the cardiovascular cycle. PMID:1777787

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

Cardiovascular screening in adolescents and young adults: a prospective study comparing the Pre-participation Physical Evaluation Monograph 4th Edition and ECG.

PubMed

Fudge, Jessie; Harmon, Kimberly G; Owens, David S; Prutkin, Jordan M; Salerno, Jack C; Asif, Irfan M; Haruta, Alison; Pelto, Hank; Rao, Ashwin L; Toresdahl, Brett G; Drezner, Jonathan A

2014-08-01

This study compares the accuracy of cardiovascular screening in active adolescents and young adults using a standardised history, physical examination and resting 12-lead ECG. Participants were prospectively screened using a standardised questionnaire based on the Pre-participation Physical Evaluation Monograph 4th Edition (PPE-4), physical examination and ECG interpreted using modern standards. Participants with abnormal findings had focused echocardiography and further evaluation. Primary outcomes included disorders associated with sudden cardiac arrest (SCA). From September 2010 to July 2011, 1339 participants underwent screening: age 13-24 (mean 16) years, 49% male, 68% Caucasian, 17% African-American and 1071 (80%) participating in organised sports. Abnormal history responses were reported on 916 (68%) questionnaires. After physician review, 495/916 (54%) participants with positive questionnaires were thought to have non-cardiac symptoms and/or a benign family history and did not warrant additional evaluation. Physical examination was abnormal in 124 (9.3%) participants, and 72 (5.4%) had ECG abnormalities. Echocardiograms were performed in 586 (44%) participants for abnormal history (31%), physical examination (8%) or ECG (5%). Five participants (0.4%) were identified with a disorder associated with SCA, all with ECG-detected Wolff-Parkinson-White. The false-positive rates for history, physical examination and ECG were 31.3%, 9.3% and 5%, respectively. A standardised history and physical examination using the PPE-4 yields a high false-positive rate in a young active population with limited sensitivity to identify those at risk for SCA. ECG screening has a low false-positive rate using modern interpretation standards and improves detection of primary electrical disease at risk of SCA. 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.

Comparison of heart rate variability between resting state and external-cuff-inflation-and-deflation state: a pilot study.

PubMed

Ji, Lizhen; Liu, Chengyu; Li, Peng; Wang, Xinpei; Yan, Chang; Liu, Changchun

2015-10-01

Heart rate variability (HRV) has been widely used in clinical research to provide an insight into the autonomic control of the cardiovascular system. Measurement of HRV is generally performed under a relaxed resting state. The effects of other conditions on HRV measurement, such as running, mountaineering, head-up tilt, etc, have also been investigated. This study aimed to explore whether an inflation-and-deflation process applied to a unilateral upper arm cuff would influence the HRV measurement. Fifty healthy young volunteers aged between 21 and 30 were enrolled in this study. Electrocardiogram (ECG) signals were recorded for each subject over a five minute resting state followed by a five minute external-cuff-inflation-and-deflation state (ECID state). A one minute gap was scheduled between the two measurements. Consecutive RR intervals in the ECG were extracted automatically to form the HRV data for each of the two states. Time domain (SDNN, RMSSD and PNN50), frequency domain (LFn, HFn and LF/HF) and nonlinear (VLI, VAI and SampEn) HRV indices were analyzed and compared between the two states. In addition, the effects of mean artery pressure (MAP) and heart rate (HR) on the aforementioned HRV indices were assessed for the two states, respectively, by Pearson correlation analysis. The results showed no significant difference in all aforementioned HRV indices between the resting and the ECID states (all p  >  0.05). The corresponding HRV indices had significant positive correlation (all p  <  0.01) between the two states. None of the indices showed MAP-related change (all p  >  0.05) for either state. Besides, none of the indices showed HR-related change (all p  >  0.05) for either state except the index of VLI in the resting state. To conclude, this pilot study suggested that the applied ECID process hardly influenced those commonly used HRV indices. It would thus be applicable to simultaneously measure both blood pressure and HRV

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.

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.

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.

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.

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

Atropine unmasks bed-rest effect - A spectral analysis of cardiac interbeat intervals

NASA Technical Reports Server (NTRS)

Goldberger, Ary L.; Goldwater, Danielle; Bhargava, Valmik

1986-01-01

Heart rate spectral data obtained for 10 male subjects between 35-49 years following orthostatic tolerance testing with lower body negative pressure prebed rest and after 7-10 days of bed rest, while on placebo and after intravenous atropine are analyzed. Comparison of the spectral atropine rms for subjects prebed rest and after bed rest reveal a decrease from 63 + or - 24 ms to 40 + or - 23 ms. It is observed that heart rate interval variability for subjects after bed rest and with atropine is reduced; the heart rate at bed rest with atropine is increased from 70.4 + or - 12.4 beats/min prebed rest to 83.7 + or - 18.9 beats/min; and the exercise tolerance time for subjects in the atropine prebed-rest phase (658 + or - 352 s) is higher than the bed-rest phase (505 + or - 252 s). It is noted that bed rest impairs the cardiovascular capacity to adaptively modulate physiological responses, atropine exposes bed-rest deconditioning effects, and spectral analysis is useful for studying the effects of bed-rest deconditioning on cardiac dynamics.

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.

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.

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.

DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI.

PubMed

Chao-Gan, Yan; Yu-Feng, Zang

2010-01-01

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for "pipeline" data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for "pipeline" data analysis of resting-state fMRI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest.

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.

The importance of an ECG: back to basics.

PubMed

Haidari, Golaleh; Gray, Kirsty; Kirubakaran, Senthil

2012-11-28

A 48-year-old man presented to accident and emergency with syncope on a background history of 3 weeks of increasing shortness of breath. He collapsed at home prompting admission. He was a smoker with a 30-pack-year history. On examination, he was found to be tachypnoeic and hypoxic, with a raised JVP and quiet heard sounds. He was haemodynamically stable and a chest x-ray showed right upper-lobe collapse. His resting ECG demonstrated electrical alternans prompting urgent referral to the cardiologist for echocardiography. This revealed a large pericardial effusion with evidence of right ventricular diastolic collapse. In view of this, he underwent urgent pericardiocentesis. A subsequent CT scan showed bilateral pleural effusions and multiple lung nodules. Both pericardial and pleural fluid cytology were reported as metastatic non-small cell adenocarcinoma. The pericardial fluid continued to reaccumulate requiring a pericardial window. He was referred to the oncology team for palliative chemotherapy.

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.

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.

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

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.

Degree Of Diminution In Vagal-Cardiac Activity Predicts Sudden Death In Familial Dysautonomia When Resting Tachycardia Is Absent

NASA Technical Reports Server (NTRS)

Schlegel, T. T.; Marthol, H.; Bucchner, S.; Tutaj, M.; Berlin, D.; Axelrod, F. B.; Hilz, M. J.

2004-01-01

Patients with familial dysautonomia (FD) have an increased risk of sudden death, but sensitive and specific predictors of sudden death in FD are lacking. Methods. We recorded 10-min resting high-fidelity 12-lead ECGs in 14 FD patients and in 14 age/gender-matched healthy subjects and studied 25+ different heart rate variability (HRV) indices for their ability to predict sudden death in the FD patients. Indices studied included those from 4 "nonlinear" HRV techniques (detrended fluctuation analysis, approximate entropy, correlation dimension, and PoincarC analyses). The predictive value of PR, QRS, QTc and JTc intervals, QT dispersion (QTd), beat-to-beat QT and PR interval variability indices (QTVI and PRVI) and 12- lead high frequency QRS ECG (150-250 Hz) were also studied. FD patients and controls (C) differed (Pless than 0.0l) with respect to 20+ of the HRV indices (FD less than C) and with respect to QTVI and PRVI (FDBC) and HF QRS- related root mean squared voltages (FDBC) and reduced amplitude zone counts (FD less than C). They differed less with respect to PR intervals (FD less than C) and JTc intervals (FD greater than C) (P less than 0.05 for both) and did not differ at all with respect to QRS and QTc intervals and to QTd. Within 12 months after study, 2 of the 14 patients succumbed to sudden cardiac arrest. The best predictor of sudden death was the degree of diminution in HRV vagal-cardiac (parasympathetic) parameters such as RMSSD, the SDl of Poincare plots, and HF spectral power. Excluding the two FD patients who had resting tachycardia (HR greater than 100, which confounds traditional HRV analyses), the following criteria were independently 100% sensitive and 100% specific for predicting sudden death in the remaining 12 FD patients during spontaneous breathing: RMSSD less than 13 ms and/or PoincarC SD1 less than 9 ms. In FD patients without supine tachycardia, the degree of diminution in parasympathetic HRV parameters (by high-fidelity ECG) predicts

Frequency Band Analysis of Electrocardiogram (ECG) Signals for Human Emotional State Classification Using Discrete Wavelet Transform (DWT).

PubMed

Murugappan, Murugappan; Murugappan, Subbulakshmi; Zheng, Bong Siao

2013-07-01

[Purpose] Intelligent emotion assessment systems have been highly successful in a variety of applications, such as e-learning, psychology, and psycho-physiology. This study aimed to assess five different human emotions (happiness, disgust, fear, sadness, and neutral) using heart rate variability (HRV) signals derived from an electrocardiogram (ECG). [Subjects] Twenty healthy university students (10 males and 10 females) with a mean age of 23 years participated in this experiment. [Methods] All five emotions were induced by audio-visual stimuli (video clips). ECG signals were acquired using 3 electrodes and were preprocessed using a Butterworth 3rd order filter to remove noise and baseline wander. The Pan-Tompkins algorithm was used to derive the HRV signals from ECG. Discrete wavelet transform (DWT) was used to extract statistical features from the HRV signals using four wavelet functions: Daubechies6 (db6), Daubechies7 (db7), Symmlet8 (sym8), and Coiflet5 (coif5). The k-nearest neighbor (KNN) and linear discriminant analysis (LDA) were used to map the statistical features into corresponding emotions. [Results] KNN provided the maximum average emotion classification rate compared to LDA for five emotions (sadness - 50.28%; happiness - 79.03%; fear - 77.78%; disgust - 88.69%; and neutral - 78.34%). [Conclusion] The results of this study indicate that HRV may be a reliable indicator of changes in the emotional state of subjects and provides an approach to the development of a real-time emotion assessment system with a higher reliability than other systems.

Accurate and consistent automatic seismocardiogram annotation without concurrent ECG.

PubMed

Laurin, A; Khosrow-Khavar, F; Blaber, A P; Tavakolian, Kouhyar

2016-09-01

Seismocardiography (SCG) is the measurement of vibrations in the sternum caused by the beating of the heart. Precise cardiac mechanical timings that are easily obtained from SCG are critically dependent on accurate identification of fiducial points. So far, SCG annotation has relied on concurrent ECG measurements. An algorithm capable of annotating SCG without the use any other concurrent measurement was designed. We subjected 18 participants to graded lower body negative pressure. We collected ECG and SCG, obtained R peaks from the former, and annotated the latter by hand, using these identified peaks. We also annotated the SCG automatically. We compared the isovolumic moment timings obtained by hand to those obtained using our algorithm. Mean  ±  confidence interval of the percentage of accurately annotated cardiac cycles were [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] for levels of negative pressure 0, -20, -30, -40, and  -50 mmHg. LF/HF ratios, the relative power of low-frequency variations to high-frequency variations in heart beat intervals, obtained from isovolumic moments were also compared to those obtained from R peaks. The mean differences  ±  confidence interval were [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] for increasing levels of negative pressure. The accuracy and consistency of the algorithm enables the use of SCG as a stand-alone heart monitoring tool in healthy individuals at rest, and could serve as a basis for an eventual application in pathological cases.

Cardiorespiratory phase synchronization during normal rest and inward-attention meditation.

PubMed

Wu, Shr-Da; Lo, Pei-Chen

2010-06-11

The cardiac and respiratory systems can be viewed as two self-sustained oscillators with various interactions between them. In this study, the cardiorespiratory phase synchronization (CRPS) quantified by synchrogram was investigated to explore the phase synchronization between these two systems. The synchrogram scheme was applied to electrocardiogram (ECG) and respiration signals. Particular focus was the distinct cardiac-respiratory regulation phenomena intervened by inward-attention meditation and normal relaxation. Four synchronization parameters were measured: frequency ratio, lasting length, number of epochs, and total length. The results showed that normal rest resulted in much weaker CRPS. Statistical analysis reveals that the number of synchronous epochs and the total synchronization length significantly increase (p=0.024 and 0.034 respectively) during meditation. Furthermore, a predominance of 4:1 and 5:1 rhythm-ratio synchronizations was observed during meditation. Consequently, this study concludes that CRPS can be enhanced during meditation, compared with normal relaxation, and reveals a predominance of specific frequency ratios. Copyright (c) 2008 Elsevier Ireland Ltd. All rights reserved.

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.

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.

CAVIAR: a serial ECG processing system for the comparative analysis of VCGs and their interpretation with auto-reference to the patient.

PubMed

Fayn, J; Rubel, P

1988-01-01

The authors present a new computer program for serial ECG analysis that allows a direct comparison of any couple of three-dimensional ECGs and quantitatively assesses the degree of evolution of the spatial loops as well as of their initial, central, or terminal sectors. Loops and sectors are superposed as best as possible, with the aim of overcoming tracing variability of nonpathological origin. As a result, optimal measures of evolution are computed and a tabular summary of measurements is dynamically configured with respect to the patient's history and is then printed. A multivariate classifier assigns each couple of tracings to one of four classes of evolution. Color graphic displays corresponding to several modes of representation may also be plotted.

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

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.

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.

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.

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.

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.

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)

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.

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.

Frequency Band Analysis of Electrocardiogram (ECG) Signals for Human Emotional State Classification Using Discrete Wavelet Transform (DWT)

PubMed Central

Murugappan, Murugappan; Murugappan, Subbulakshmi; Zheng, Bong Siao

2013-01-01

[Purpose] Intelligent emotion assessment systems have been highly successful in a variety of applications, such as e-learning, psychology, and psycho-physiology. This study aimed to assess five different human emotions (happiness, disgust, fear, sadness, and neutral) using heart rate variability (HRV) signals derived from an electrocardiogram (ECG). [Subjects] Twenty healthy university students (10 males and 10 females) with a mean age of 23 years participated in this experiment. [Methods] All five emotions were induced by audio-visual stimuli (video clips). ECG signals were acquired using 3 electrodes and were preprocessed using a Butterworth 3rd order filter to remove noise and baseline wander. The Pan-Tompkins algorithm was used to derive the HRV signals from ECG. Discrete wavelet transform (DWT) was used to extract statistical features from the HRV signals using four wavelet functions: Daubechies6 (db6), Daubechies7 (db7), Symmlet8 (sym8), and Coiflet5 (coif5). The k-nearest neighbor (KNN) and linear discriminant analysis (LDA) were used to map the statistical features into corresponding emotions. [Results] KNN provided the maximum average emotion classification rate compared to LDA for five emotions (sadness − 50.28%; happiness − 79.03%; fear − 77.78%; disgust − 88.69%; and neutral − 78.34%). [Conclusion] The results of this study indicate that HRV may be a reliable indicator of changes in the emotional state of subjects and provides an approach to the development of a real-time emotion assessment system with a higher reliability than other systems. PMID:24259846

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.

Language in the brain at rest: new insights from resting state data and graph theoretical analysis

PubMed Central

Muller, Angela M.; Meyer, Martin

2014-01-01

In humans, the most obvious functional lateralization is the specialization of the left hemisphere for language. Therefore, the involvement of the right hemisphere in language is one of the most remarkable findings during the last two decades of fMRI research. However, the importance of this finding continues to be underestimated. We examined the interaction between the two hemispheres and also the role of the right hemisphere in language. From two seeds representing Broca's area, we conducted a seed correlation analysis (SCA) of resting state fMRI data and could identify a resting state network (RSN) overlapping to significant extent with a language network that was generated by an automated meta-analysis tool. To elucidate the relationship between the clusters of this RSN, we then performed graph theoretical analyses (GTA) using the same resting state dataset. We show that the right hemisphere is clearly involved in language. A modularity analysis revealed that the interaction between the two hemispheres is mediated by three partitions: A bilateral frontal partition consists of nodes representing the classical left sided language regions as well as two right-sided homologs. The second bilateral partition consists of nodes from the right frontal, the left inferior parietal cortex as well as of two nodes within the posterior cerebellum. The third partition is also bilateral and comprises five regions from the posterior midline parts of the brain to the temporal and frontal cortex, two of the nodes are prominent default mode nodes. The involvement of this last partition in a language relevant function is a novel finding. PMID:24808843

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.

ECG Rhythm Analysis with Expert and Learner-Generated Schemas in Novice Learners

ERIC Educational Resources Information Center

Blissett, Sarah; Cavalcanti, Rodrigo; Sibbald, Matthew

2015-01-01

Although instruction using expert-generated schemas is associated with higher diagnostic performance, implementation is resource intensive. Learner-generated schemas are an alternative, but may be limited by increases in cognitive load. We compared expert- and learner-generated schemas for learning ECG rhythm interpretation on diagnostic accuracy,…

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

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.

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

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.

Integration of multivariate empirical mode decomposition and independent component analysis for fetal ECG separation from abdominal signals.

PubMed

Thanaraj, Palani; Roshini, Mable; Balasubramanian, Parvathavarthini

2016-11-14

The fetal electrocardiogram (FECG) signals are essential to monitor the health condition of the baby. Fetal heart rate (FHR) is commonly used for diagnosing certain abnormalities in the formation of the heart. Usually, non-invasive abdominal electrocardiogram (AbECG) signals are obtained by placing surface electrodes in the abdomen region of the pregnant woman. AbECG signals are often not suitable for the direct analysis of fetal heart activity. Moreover, the strength and magnitude of the FECG signals are low compared to the maternal electrocardiogram (MECG) signals. The MECG signals are often superimposed with the FECG signals that make the monitoring of FECG signals a difficult task. Primary goal of the paper is to separate the fetal electrocardiogram (FECG) signals from the unwanted maternal electrocardiogram (MECG) signals. A multivariate signal processing procedure is proposed here that combines the Multivariate Empirical Mode Decomposition (MEMD) and Independent Component Analysis (ICA). The proposed method is evaluated with clinical abdominal signals taken from three pregnant women (N= 3) recorded during the 38-41 weeks of the gestation period. The number of fetal R-wave detected (NEFQRS), the number of unwanted maternal peaks (NMQRS), the number of undetected fetal R-wave (NUFQRS) and the FHR detection accuracy quantifies the performance of our method. Clinical investigation with three test subjects shows an overall detection accuracy of 92.8%. Comparative analysis with benchmark signal processing method such as ICA suggests the noteworthy performance of our method.

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.

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.

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

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.

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...

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.

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.

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.

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

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.

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.

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

Personal Verification/Identification via Analysis of the Peripheral ECG Leads: Influence of the Personal Health Status on the Accuracy

PubMed Central

Bortolan, Giovanni

2015-01-01

Traditional means for identity validation (PIN codes, passwords), and physiological and behavioral biometric characteristics (fingerprint, iris, and speech) are susceptible to hacker attacks and/or falsification. This paper presents a method for person verification/identification based on correlation of present-to-previous limb ECG leads: I (r I), II (r II), calculated from them first principal ECG component (r PCA), linear and nonlinear combinations between r I, r II, and r PCA. For the verification task, the one-to-one scenario is applied and threshold values for r I, r II, and r PCA and their combinations are derived. The identification task supposes one-to-many scenario and the tested subject is identified according to the maximal correlation with a previously recorded ECG in a database. The population based ECG-ILSA database of 540 patients (147 healthy subjects, 175 patients with cardiac diseases, and 218 with hypertension) has been considered. In addition a common reference PTB dataset (14 healthy individuals) with short time interval between the two acquisitions has been taken into account. The results on ECG-ILSA database were satisfactory with healthy people, and there was not a significant decrease in nonhealthy patients, demonstrating the robustness of the proposed method. With PTB database, the method provides an identification accuracy of 92.9% and a verification sensitivity and specificity of 100% and 89.9%. PMID:26568954

Personal Verification/Identification via Analysis of the Peripheral ECG Leads: Influence of the Personal Health Status on the Accuracy.

PubMed

Jekova, Irena; Bortolan, Giovanni

2015-01-01

Traditional means for identity validation (PIN codes, passwords), and physiological and behavioral biometric characteristics (fingerprint, iris, and speech) are susceptible to hacker attacks and/or falsification. This paper presents a method for person verification/identification based on correlation of present-to-previous limb ECG leads: I (r I), II (r II), calculated from them first principal ECG component (r PCA), linear and nonlinear combinations between r I, r II, and r PCA. For the verification task, the one-to-one scenario is applied and threshold values for r I, r II, and r PCA and their combinations are derived. The identification task supposes one-to-many scenario and the tested subject is identified according to the maximal correlation with a previously recorded ECG in a database. The population based ECG-ILSA database of 540 patients (147 healthy subjects, 175 patients with cardiac diseases, and 218 with hypertension) has been considered. In addition a common reference PTB dataset (14 healthy individuals) with short time interval between the two acquisitions has been taken into account. The results on ECG-ILSA database were satisfactory with healthy people, and there was not a significant decrease in nonhealthy patients, demonstrating the robustness of the proposed method. With PTB database, the method provides an identification accuracy of 92.9% and a verification sensitivity and specificity of 100% and 89.9%.

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).

A correlation analysis-based detection and delineation of ECG characteristic events using template waveforms extracted by ensemble averaging of clustered heart cycles.

PubMed

Homaeinezhad, M R; Erfanianmoshiri-Nejad, M; Naseri, H

2014-01-01

The goal of this study is to introduce a simple, standard and safe procedure to detect and to delineate P and T waves of the electrocardiogram (ECG) signal in real conditions. The proposed method consists of four major steps: (1) a secure QRS detection and delineation algorithm, (2) a pattern recognition algorithm designed for distinguishing various ECG clusters which take place between consecutive R-waves, (3) extracting template of the dominant events of each cluster waveform and (4) application of the correlation analysis in order to delineate automatically the P- and T-waves in noisy conditions. The performance characteristics of the proposed P and T detection-delineation algorithm are evaluated versus various ECG signals whose qualities are altered from the best to the worst cases based on the random-walk noise theory. Also, the method is applied to the MIT-BIH Arrhythmia and the QT databases for comparing some parts of its performance characteristics with a number of P and T detection-delineation algorithms. The conducted evaluations indicate that in a signal with low quality value of about 0.6, the proposed method detects the P and T events with sensitivity Se=85% and positive predictive value of P+=89%, respectively. In addition, at the same quality, the average delineation errors associated with those ECG events are 45 and 63ms, respectively. Stable delineation error, high detection accuracy and high noise tolerance were the most important aspects considered during development of the proposed method. © 2013 Elsevier Ltd. All rights reserved.

[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.

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.

Resting-state abnormalities in amnestic mild cognitive impairment: a meta-analysis.

PubMed

Lau, W K W; Leung, M-K; Lee, T M C; Law, A C K

2016-04-26

Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer's disease (AD). As no effective drug can cure AD, early diagnosis and intervention for aMCI are urgently needed. The standard diagnostic procedure for aMCI primarily relies on subjective neuropsychological examinations that require the judgment of experienced clinicians. The development of other objective and reliable aMCI markers, such as neural markers, is therefore required. Previous neuroimaging findings revealed various abnormalities in resting-state activity in MCI patients, but the findings have been inconsistent. The current study provides an updated activation likelihood estimation meta-analysis of resting-state functional magnetic resonance imaging (fMRI) data on aMCI. The authors searched on the MEDLINE/PubMed databases for whole-brain resting-state fMRI studies on aMCI published until March 2015. We included 21 whole-brain resting-state fMRI studies that reported a total of 156 distinct foci. Significant regional resting-state differences were consistently found in aMCI patients relative to controls, including the posterior cingulate cortex, right angular gyrus, right parahippocampal gyrus, left fusiform gyrus, left supramarginal gyrus and bilateral middle temporal gyri. Our findings support that abnormalities in resting-state activities of these regions may serve as neuroimaging markers for aMCI.

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.

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

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.

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.

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.

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

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

A Cardiac Early Warning System with Multi Channel SCG and ECG Monitoring for Mobile Health

PubMed Central

Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Lee, Ming-Yih

2017-01-01

Use of information and communication technology such as smart phone, smart watch, smart glass and portable health monitoring devices for healthcare services has made Mobile Health (mHealth) an emerging research area. Coronary Heart Disease (CHD) is considered as a leading cause of death world wide and an increasing number of people die prematurely due to CHD. Under such circumstances, there is a growing demand for a reliable cardiac monitoring system to catch the intermittent abnormalities and detect critical cardiac behaviors which lead to sudden death. Use of mobile devices to collect Electrocardiography (ECG), Seismocardiography (SCG) data and efficient analysis of those data can monitor a patient’s cardiac activities for early warning. This paper presents a novel cardiac data acquisition method and combined analysis of Electrocardiography (ECG) and multi channel Seismocardiography (SCG) data. An early warning system is implemented to monitor the cardiac activities of a person and accuracy assessment of the early warning system is conducted for the ECG data only. The assessment shows 88% accuracy and effectiveness of our proposed analysis, which implies the viability and applicability of the proposed early warning system. PMID:28353681

A Cardiac Early Warning System with Multi Channel SCG and ECG Monitoring for Mobile Health.

PubMed

Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Lee, Ming-Yih

2017-03-29

Use of information and communication technology such as smart phone, smart watch, smart glass and portable health monitoring devices for healthcare services has made Mobile Health (mHealth) an emerging research area. Coronary Heart Disease (CHD) is considered as a leading cause of death world wide and an increasing number of people die prematurely due to CHD. Under such circumstances, there is a growing demand for a reliable cardiac monitoring system to catch the intermittent abnormalities and detect critical cardiac behaviors which lead to sudden death. Use of mobile devices to collect Electrocardiography (ECG), Seismocardiography (SCG) data and efficient analysis of those data can monitor a patient's cardiac activities for early warning. This paper presents a novel cardiac data acquisition method and combined analysis of Electrocardiography (ECG) and multi channel Seismocardiography (SCG) data. An early warning system is implemented to monitor the cardiac activities of a person and accuracy assessment of the early warning system is conducted for the ECG data only. The assessment shows 88% accuracy and effectiveness of our proposed analysis, which implies the viability and applicability of the proposed early warning system.

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.

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.

Cardiac Repolarization Abnormalities and Potential Evidence for Loss of Cardiac Sodium Currents on ECGs of Patients with Chagas' Heart Disease

NASA Technical Reports Server (NTRS)

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

2007-01-01

Some individuals with Chagas disease develop right precordial lead ST segment elevation in response to an ajmaline challenge test, and the prevalence of right bundle branch block (RBBB) is also high in Chagas disease. Because these same electrocardiographic abnormalities occur in the Brugada syndrome, which involves genetically defective cardiac sodium channels, acquired damage to cardiac sodium channels may also occur in Chagas disease. We studied several conventional and advanced resting 12-lead/derived Frank-lead ECG parameters in 34 patients with Chagas -related heart disease (mean age 39 14 years) and in 34 age-/gender-matched healthy controls. All ECG recordings were of 5-10 min duration, obtained in the supine position using high fidelity hardware/software (CardioSoft, Houston, TX). Even after excluding those Chagas patients who had resting BBBs, tachycardia and/or pathologic arrhythmia (n=8), significant differences remained in multiple conventional and advanced ECG parameters between the Chagas and control groups (n=26/group), especially in their respective QT interval variability indices, maximal spatial QRS-T angles and low frequency HRV powers (p=0.0006, p=0.0015 and p=0.0314 respectively). In relation to the issue of potential damage to cardiac sodium channels, the Chagas patients had: 1) greater than or equal to twice the incidence of resting ST segment elevation in leads V1-V3 (n=10/26 vs. n=5/26) and of both leftward (n=5/26 versus n=0/26) and rightward (n=7/26 versus n=3/26) QRS axis deviation than controls; 2) significantly increased filtered (40-250 Hz) QRS interval durations (92.1 8.5 versus 85.3 plus or minus 9.0 ms, p=0.022) versus controls; and 3) significantly decreased QT and especially JT interval durations versus controls (QT interval: 387.5 plus or minus 26.4 versus 408.9 plus or minus 34.6 ms, p=0.013; JT interval: 290.5 plus or minus 26.3 versus 314.8 plus or minus 31.3 ms; p=0.0029). Heart rates and Bazett-corrected QTc/JTc intervals

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.

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.

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.

Effect of Head-Down Bed Rest and Artificial Gravity Countermeasure on Cardiac Autonomic and Advanced Electrocardiographic Function

NASA Technical Reports Server (NTRS)

Schlegel, T. T.; Platts, S.; Stenger, M.; Ribeiro, C.; Natapoff, A.; Howarth, M.; Evans, J.

2007-01-01

To study the effects of 21 days of head-down bed rest (HDBR), with versus without an artificial gravity (AG) countermeasure, on cardiac autonomic and advanced electrocardiographic function. Fourteen healthy men participated in the study: seven experienced 21 days of HDBR alone ("HDBR controls") and seven the same degree and duration of HDBR but with approximately 1hr daily short-arm centrifugation as an AG countermeasure ("AG-treated"). Five minute supine high-fidelity 12-lead ECGs were obtained in all subjects: 1) 4 days before HDBR; 2) on the last day of HDBR; and 3) 7 days after HDBR. Besides conventional 12-lead ECG intervals and voltages, all of the following advanced ECG parameters were studied: 1) both stochastic (time and frequency domain) and deterministic heart rate variability (HRV); 2) beat-to-beat QT interval variability (QTV); 3) T-wave morphology, including signal-averaged T-wave residua (TWR) and principal component analysis ratios; 4) other SAECG-related parameters including high frequency QRS ECG and late potentials; and 5) several advanced ECG estimates of left ventricular (LV) mass. The most important results by repeated measures ANOVA were that: 1) Heart rates, Bazett-corrected QTc intervals, TWR, LF/HF power and the alpha 1 of HRV were significantly increased in both groups (i.e., by HDBR), but with no relevant HDBR*group differences; 2) All purely "vagally-mediated" parameters of HRV (e.g., RMSSD, HF power, Poincare SD1, etc.), PR intervals, and also several parameters of LV mass (Cornell and Sokolow-Lyon voltages, spatial ventricular activation times, ventricular gradients) were all significantly decreased in both groups (i.e., by HDBR), but again with no relevant HDBR*group differences); 3) All "generalized" or "vagal plus sympathetic" parameters of stochastic HRV (i.e., SDNN, total power, LF power) were significantly more decreased in the AG-treated group than in the HDBR-only group (i.e., here there was a relevant HDBR*group difference

ABERRANT RESTING-STATE BRAIN ACTIVITY IN POSTTRAUMATIC STRESS DISORDER: A META-ANALYSIS AND SYSTEMATIC REVIEW.

PubMed

Koch, Saskia B J; van Zuiden, Mirjam; Nawijn, Laura; Frijling, Jessie L; Veltman, Dick J; Olff, Miranda

2016-07-01

About 10% of trauma-exposed individuals develop PTSD. Although a growing number of studies have investigated resting-state abnormalities in PTSD, inconsistent results suggest a need for a meta-analysis and a systematic review. We conducted a systematic literature search in four online databases using keywords for PTSD, functional neuroimaging, and resting-state. In total, 23 studies matched our eligibility criteria. For the meta-analysis, we included 14 whole-brain resting-state studies, reporting data on 663 participants (298 PTSD patients and 365 controls). We used the activation likelihood estimation approach to identify concurrence of whole-brain hypo- and hyperactivations in PTSD patients during rest. Seed-based studies could not be included in the quantitative meta-analysis. Therefore, a separate qualitative systematic review was conducted on nine seed-based functional connectivity studies. The meta-analysis showed consistent hyperactivity in the ventral anterior cingulate cortex and the parahippocampus/amygdala, but hypoactivity in the (posterior) insula, cerebellar pyramis and middle frontal gyrus in PTSD patients, compared to healthy controls. Partly concordant with these findings, the systematic review on seed-based functional connectivity studies showed enhanced salience network (SN) connectivity, but decreased default mode network (DMN) connectivity in PTSD. Combined, these altered resting-state connectivity and activity patterns could represent neurobiological correlates of increased salience processing and hypervigilance (SN), at the cost of awareness of internal thoughts and autobiographical memory (DMN) in PTSD. However, several discrepancies between findings of the meta-analysis and systematic review were observed, stressing the need for future studies on resting-state abnormalities in PTSD patients. © 2016 Wiley Periodicals, Inc.

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.

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.

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.

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.

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.

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

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.

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…

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.

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.

Predicting depressed patients with suicidal ideation from ECG recordings.

PubMed

Khandoker, A H; Luthra, V; Abouallaban, Y; Saha, S; Ahmed, K I; Mostafa, R; Chowdhury, N; Jelinek, H F

2017-05-01

Globally suicidal behavior is the third most common cause of death among patients with major depressive disorder (MDD). This study presents multi-lag tone-entropy (T-E) analysis of heart rate variability (HRV) as a screening tool for identifying MDD patients with suicidal ideation. Sixty-one ECG recordings (10 min) were acquired and analyzed from control subjects (29 CONT), 16 MDD subjects with (MDDSI+) and 16 without suicidal ideation (MDDSI-). After ECG preprocessing, tone and entropy values were calculated for multiple lags (m: 1-10). The MDDSI+ group was found to have a higher mean tone value compared to that of the MDDSI- group for lags 1-8, whereas the mean entropy value was lower in MDDSI+ than that in CONT group at all lags (1-10). Leave-one-out cross-validation tests, using a classification and regression tree (CART), obtained 94.83 % accuracy in predicting MDDSI+ subjects by using a combination of tone and entropy values at all lags and including demographic factors (age, BMI and waist circumference) compared to results with time and frequency domain HRV analysis. The results of this pilot study demonstrate the usefulness of multi-lag T-E analysis in identifying MDD patients with suicidal ideation and highlight the change in autonomic nervous system modulation of the heart rate associated with depression and suicidal ideation.

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.

Comparison of cardiogoniometry and electrocardiography with perfusion cardiac magnetic resonance imaging and late gadolinium enhancement.

PubMed

Birkemeyer, Ralf; Toelg, Ralph; Zeymer, Uwe; Wessely, Rainer; Jäckle, Sebastian; Hairedini, Bajram; Lübke, Mike; Aßfalg, Manfred; Jung, Werner

2012-12-01

Cardiogoniometry (CGM) is a spatio-temporal five-lead resting electrocardiographic method utilizing automated analysis. The purpose of this study was to determine CGM's and electrocardiography (ECG)'s accuracy for detecting myocardial ischaemia and/or lesions in comparison with perfusion cardiac magnetic resonance imaging (CMRI) and late gadolinium enhancement (LGE). Forty (n= 40) patients with suspected or known stable coronary artery disease were examined by CGM and resting ECG directly prior to CMRI including adenosine stress perfusion (ASP) and LGE. The investigators visually reading the CMRI were blinded to the CGM and ECG results. Half of the patients (n= 20) had a normal CMRI while the other half presented with either abnormal ASP and/or detectable LGE. Cardiogoniometry yielded an accuracy of 83% (sensitivity 70%) and ECG of 63% (sensitivity 35%) compared with CMRI. In this pilot study CGM compares more favourably than ECG with the detection of ischaemia and/or structural myocardial lesions on CMRI.

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

Two Dimensional Processing Of Speech And Ecg Signals Using The Wigner-Ville Distribution

NASA Astrophysics Data System (ADS)

Boashash, Boualem; Abeysekera, Saman S.

1986-12-01

The Wigner-Ville Distribution (WVD) has been shown to be a valuable tool for the analysis of non-stationary signals such as speech and Electrocardiogram (ECG) data. The one-dimensional real data are first transformed into a complex analytic signal using the Hilbert Transform and then a 2-dimensional image is formed using the Wigner-Ville Transform. For speech signals, a contour plot is determined and used as a basic feature. for a pattern recognition algorithm. This method is compared with the classical Short Time Fourier Transform (STFT) and is shown, to be able to recognize isolated words better in a noisy environment. The same method together with the concept of instantaneous frequency of the signal is applied to the analysis of ECG signals. This technique allows one to classify diseased heart-beat signals. Examples are shown.

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.

Critical analysis of a computer-assisted tutorial on ECG interpretation and its ability to determine competency.

PubMed

Burke, J F; Gnall, E; Umrudden, Z; Kyaw, M; Schick, P K

2008-01-01

We developed a computer-based tutorial and a posttest on ECG interpretation for training residents and determining competency. Forty residents, 6 cardiology fellows, and 4 experienced physicians participated. The tutorial emphasized recognition and understanding of abnormal ECG features. Active learning was promoted by asking questions prior to the discussion of ECGs. Interactivity was facilitated by providing rapid and in-depth rationale for correct answers. Responses to questions were recorded and extensively analyzed to determine the quality of questions, baseline knowledge at different levels of training and improvement of grades in posttest. Posttest grades were used to assess improvement and to determine competency. The questions were found to be challenging, fair, appropriate and discriminative. This was important since the quality of Socratic questions is critical for the success of interactive programs. The information on strengths and weakness in baseline knowledge at different levels of training were used to adapt our training program to the needs of residents. The posttest revealed that the tutorial contributed to marked improvement in feature recognition. Competency testing distinguished between residents with outstanding grades and those who needed remediation. The strategy for critical evaluation of our computer program could be applied to any computer-based educational program, regardless of topic.

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

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.

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.

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2016-10-01

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis PRINCIPAL...4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis 5b...Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad

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.

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.

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.

Localizing Circuits of Atrial Macro-Reentry Using ECG Planes of Coherent Atrial Activation

PubMed Central

Kahn, Andrew M.; Krummen, David E.; Feld, Gregory K.; Narayan, Sanjiv M.

2007-01-01

Background The complexity of ablation for atrial macro-reentry (AFL) varies significantly depending upon the circuit location. Presently, surface ECG analysis poorly separates left from right atypical AFL and from some cases of typical AFL, delaying diagnosis until invasive study. Objective To differentiate and localize the intra-atrial circuits of left atypical AFL, right atypical, and typical AFL using quantitative ECG analysis. Methods We studied 66 patients (54 M, age 59±14 years) with typical (n=35), reverse typical (n=4) and atypical (n=27) AFL. For each, we generated filtered atrial waveforms from ECG leads V5 (X-axis), aVF (Y) and V1 (Z) by correlating a 120 ms F-wave sample to successive ECG regions. Atrial spatial loops were plotted for 3 orthogonal planes (frontal, XY=V5/aVF; sagittal, YZ=aVF/V1; axial, XZ=V5/V1), then cross-correlated to measure spatial regularity (‘coherence’: range −1 to 1). Results Mean coherence was greatest in the XY plane (p<10−3 vs XZ or YZ). Atypical AFL showed lower coherence than typical AFL in XY (p<10−3), YZ (p<10−6) and XZ (p<10−5) planes. Atypical left AFL could be separated from atypical right AFL by lower XY coherence (p=0.02); for this plane coherence < 0.69 detected atypical left AFL with 84% specificity and 75% sensitivity. F-wave amplitude did not separate typical, atypical right or atypical left AFL (p=NS). Conclusions Atypical AFL shows lower spatial coherence than typical AFL, particularly in sagittal and axial planes. Coherence in the Cartesian frontal plane separated left and right atypical AFL. Such analyses may be used to plan ablation strategy from the bedside. PMID:17399632

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.

[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.

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

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.

An ECG electrode-mounted heart rate, respiratory rhythm, posture and behavior recording system.

PubMed

Yoshimura, Takahiro; Yonezawa, Yoshiharu; Maki, Hiromichi; Ogawa, Hidekuni; Ninomiya, Ishio; Morton Caldwell, W

2004-01-01

R-R interval, respiration rhythm, posture and behavior recording system has been developed for monitoring a patient's cardiovascular regulatory system in daily life. The recording system consists of three ECG chest electrodes, a variable gain instrumentation amplifier, a dual axis accelerometer, a low power 8-bit single-chip microcomputer and a 1024 KB EEPROM. The complete system is mounted on the chest electrodes. R-R interval and respiration rhythm are calculated by the R waves detected from the ECG. Posture and behavior such as walking and running are detected from the body movements recorded by the accelerometer. The detected data are stored by the EEPROM and, after recording, are downloaded to a desktop computer for analysis.

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.

Energy Analysis of Decoders for Rakeness-Based Compressed Sensing of ECG Signals.

PubMed

Pareschi, Fabio; Mangia, Mauro; Bortolotti, Daniele; Bartolini, Andrea; Benini, Luca; Rovatti, Riccardo; Setti, Gianluca

2017-12-01

In recent years, compressed sensing (CS) has proved to be effective in lowering the power consumption of sensing nodes in biomedical signal processing devices. This is due to the fact the CS is capable of reducing the amount of data to be transmitted to ensure correct reconstruction of the acquired waveforms. Rakeness-based CS has been introduced to further reduce the amount of transmitted data by exploiting the uneven distribution to the sensed signal energy. Yet, so far no thorough analysis exists on the impact of its adoption on CS decoder performance. The latter point is of great importance, since body-area sensor network architectures may include intermediate gateway nodes that receive and reconstruct signals to provide local services before relaying data to a remote server. In this paper, we fill this gap by showing that rakeness-based design also improves reconstruction performance. We quantify these findings in the case of ECG signals and when a variety of reconstruction algorithms are used either in a low-power microcontroller or a heterogeneous mobile computing platform.

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

Resting and postexercise heart rate variability in professional handball players.

PubMed

Kayacan, Yildirim; Yildiz, Sedat

2016-03-01

The aim of this study was to evaluate heart rate variability (HRV) in professional handball players during rest and following a 5 min mild jogging exercise. For that purpose, electrocardiogram (ECG) of male handball players (N.=12, mean age 25±3.95 years) and sedentary controls (N.=14, mean age 23.5±2.95 years) were recorded for 5 min at rest and just after 5 min of mild jogging. ECGs were recorded and following HRV parameters were calculated: time-domain variables such as heart rate (HR), average normal-to-normal RR intervals, standard deviation of normal-to-normal RR intervals, square root of the mean of the squares of differences between adjacent NN intervals, percentage of differences between adjacent NN intervals that are greater than 50 milliseconds (pNN50), and frequency-domain variables such as very low frequency, low (LF) and high frequency (HF) of the power and LF/HF ratio. Unpaired t-test was used to find out differences among groups while paired t-test was used for comparison of each group for pre- and postjogging HRV. Pearson correlations were carried out to find out the relationships between the parameters. Blood pressures were not different between handball players and sedentary controls but exercise increased systolic blood pressure (P<0.01). HR was increased with exercise (P<0.001) and was slower in handball players (P<0.01). QTc was increased with exercise (P<0.001) and was higher in handball players (P<0.001). Exercise decreased pNN50 values in both groups but LF/HF ratio increased only in sedentary subjects. In conclusion, results of the HRV parameters show that sympathovagal balance does not appear to change in handball players in response to a mild, short-time (5 min) jogging exercise. However, in sedentary subjects, either the sympathetic regulation of the autonomous nervous system increased or vagal withdrawal occurred.

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

Large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

2016-03-01

We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

Effects of strict prolonged bed rest on cardiorespiratory fitness: systematic review and meta-analysis.

PubMed

Ried-Larsen, Mathias; Aarts, Hugo M; Joyner, Michael J

2017-10-01

The aim of this systematic review and meta-analysis [International Prospective Register of Systematic Reviews (PROSPERO) CRD42017055619] was to assess the effects of strict prolonged bed rest (without countermeasures) on maximal oxygen uptake (V̇o 2max ) and to explore sources of variation therein. Since 1949, 80 studies with a total of 949 participants (>90% men) have been published with data on strict bed rest and V̇o 2max The studies were conducted mainly in young participants [median age (interquartile range) 24.5 (22.4-34.0) yr]. The duration of bed rest ranged from 1 to 90 days. V̇o 2max declined linearly across bed rest duration. No statistical difference in the decline among studies reporting V̇o 2max as l/min (-0.3% per day) compared with studies reporting V̇o 2max normalized to body weight (ml·kg -1 ·min -1 ; -0.43% per day) was observed. Although both total body weight and lean body mass declined in response to bed rest, we did not see any associations with the decline in V̇o 2max However, 15-26% of the variation in the decline in V̇o 2max was explained by the pre-bed-rest V̇o 2max levels, independent of the duration of bed rest (i.e., higher pre-bed-rest V̇o 2max levels were associated with larger declines in V̇o 2max ). Furthermore, the systematic review revealed a gap in the knowledge about the cardiovascular response to extreme physical inactivity, particularly in older subjects and women of any age group. In addition to its relevance to spaceflight, this lack of data has significant translational implications because younger women sometimes undergo prolonged periods of bed rest associated with the complications of pregnancy and the incidence of hospitalization including prolonged periods of bed rest increases with age. NEW & NOTEWORTHY Large interindividual responses of maximal oxygen uptake (V̇o 2max ) to aerobic exercise training exist. However, less is known about the variability in the response of V̇o 2max to prolonged bed rest

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

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.

Implementation of a data packet generator using pattern matching for wearable ECG monitoring systems.

PubMed

Noh, Yun Hong; Jeong, Do Un

2014-07-15

In this paper, a packet generator using a pattern matching algorithm for real-time abnormal heartbeat detection is proposed. The packet generator creates a very small data packet which conveys sufficient crucial information for health condition analysis. The data packet envelopes real time ECG signals and transmits them to a smartphone via Bluetooth. An Android application was developed specifically to decode the packet and extract ECG information for health condition analysis. Several graphical presentations are displayed and shown on the smartphone. We evaluate the performance of abnormal heartbeat detection accuracy using the MIT/BIH Arrhythmia Database and real time experiments. The experimental result confirm our finding that abnormal heart beat detection is practically possible. We also performed data compression ratio and signal restoration performance evaluations to establish the usefulness of the proposed packet generator and the results were excellent.

Analysis of Instantaneous Linear, Nonlinear and Complex Cardiovascular Dynamics from Videophotoplethysmography.

PubMed

Valenza, Gaetano; Iozzia, Luca; Cerina, Luca; Mainardi, Luca; Barbieri, Riccardo

2018-05-01

There is a fast growing interest in the use of non-contact devices for health and performance assessment in humans. In particular, the use of non-contact videophotoplethysmography (vPPG) has been recently demonstrated as a feasible way to extract cardiovascular information. Nevertheless, proper validation of vPPG-derived heartbeat dynamics is still missing. We aim to an in-depth validation of time-varying, linear and nonlinear/complex dynamics of the pulse rate variability extracted from vPPG. We apply inhomogeneous pointprocess nonlinear models to assess instantaneous measures defined in the time, frequency, and bispectral domains as estimated through vPPG and standard ECG. Instantaneous complexity measures, such as the instantaneous Lyapunov exponents and the recently defined inhomogeneous point-process approximate and sample entropy, were estimated as well. Video recordings were processed using our recently proposed method based on zerophase principal component analysis. Experimental data were gathered from 60 young healthy subjects (age: 24±3 years) undergoing postural changes (rest-to-stand maneuver). Group averaged results show that there is an overall agreement between linear and nonlinear/complexity indices computed from ECG and vPPG during resting state conditions. However, important differences are found, particularly in the bispectral and complexity domains, in recordings where the subjects has been instructed to stand up. Although significant differences exist between cardiovascular estimates from vPPG and ECG, it is very promising that instantaneous sympathovagal changes, as well as time-varying complex dynamics, were correctly identified, especially during resting state. In addition to a further improvement of the video signal quality, more research is advocated towards a more precise estimation of cardiovascular dynamics by a comprehensive nonlinear/complex paradigm specifically tailored to the non-contact quantification. Schattauer GmbH.

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.

Nonlinear analysis of the heartbeats in public patient ECGs using an automated PD2i algorithm for risk stratification of arrhythmic death

PubMed Central

Skinner, James E; Anchin, Jerry M; Weiss, Daniel N

2008-01-01

Heart rate variability (HRV) reflects both cardiac autonomic function and risk of arrhythmic death (AD). Reduced indices of HRV based on linear stochastic models are independent risk factors for AD in post-myocardial infarct cohorts. Indices based on nonlinear deterministic models have a significantly higher sensitivity and specificity for predicting AD in retrospective data. A need exists for nonlinear analytic software easily used by a medical technician. In the current study, an automated nonlinear algorithm, the time-dependent point correlation dimension (PD2i), was evaluated. The electrocardiogram (ECG) data were provided through an National Institutes of Health-sponsored internet archive (PhysioBank) and consisted of all 22 malignant arrhythmia ECG files (VF/VT) and 22 randomly selected arrhythmia files as the controls. The results were blindly calculated by automated software (Vicor 2.0, Vicor Technologies, Inc., Boca Raton, FL) and showed all analyzable VF/VT files had PD2i < 1.4 and all analyzable controls had PD2i > 1.4. Five VF/VT and six controls were excluded because surrogate testing showed the RR-intervals to contain noise, possibly resulting from the low digitization rate of the ECGs. The sensitivity was 100%, specificity 85%, relative risk > 100; p < 0.01, power > 90%. Thus, automated heartbeat analysis by the time-dependent nonlinear PD2i-algorithm can accurately stratify risk of AD in public data made available for competitive testing of algorithms. PMID:18728829

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.

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.

[Role of ST-analysis of fetal ECG in intrapartal fetus monitoring with presumed growth retardation].

PubMed

Hruban, L; Janků, P; Zahradnícková, J; Kurecová, B; Roztocil, A; Kachlík, P; Kucera, M; Jelenek, G

2006-07-01

Evaluation of the role of ST analysis of fetus ECG for early detection of developing acute hypoxia in the course of delivery of fetuses with presumed growth retardation. A comparison with present way of intrapartal fetus monitoring. Impact on the number of surgical births for indications of threatening fetus hypoxia. Influence of the method on perinatal results and postnatal adaptation of the newborns. A prospective study. Gynecology-Obstetrics Clinic, Masaryk University and Teaching Hospital Brno. Forty seven women with a growth retardation of the fetus diagnosed before delivery who gave birth in the Teaching Hospital in Brno during 2003-2005 and intrapartal ST analysis of fetus ECG was subsequently used, were enrolled into this prospective study (group A). The control group consisted of 87 deliveries taking place in the same period of time and concerning women with fetuses suffering from growth retardation and monitored by standard methods (group B). The standard methods included cardiotocography (CTG), supplemented with pulse oximetry (IFPO) if needed. The diagnosis of intrauterine fetus growth retardation was established on the basis of the results of repeated prepartal ultrasound fetus biometry with estimation of the mass, which corresponded to a group below 10 percentile for the given gestational age. The numbers of vaginal deliveries and surgically treated delivery due to threatening fetus hypoxia (Cesarean section, forceps delivery) were recorded. The authors evaluated postpartal pH from umbilical artery, independently for the group of values of pH < 7.00, the group of pH 7.00-0.10 and pH 7.10 or more. The values of Apgar score were evaluated for the first, fifth and tenth minute, respectively. The neonatologist followed the duration of stay of the newborn at the Newborn Intensive Care Unit, the Intermediate Care Unit, total duration of hospitalization, the occurrence of sepsis in the early newbotn period, the occurrence of hyperbilirubinemia, and the

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.

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.

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.

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.

The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition

PubMed Central

Diaz, B. Alexander; Van Der Sluis, Sophie; Moens, Sarah; Benjamins, Jeroen S.; Migliorati, Filippo; Stoffers, Diederick; Den Braber, Anouk; Poil, Simon-Shlomo; Hardstone, Richard; Van't Ent, Dennis; Boomsma, Dorret I.; De Geus, Eco; Mansvelder, Huibert D.; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

2013-01-01

Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition—and tools to quantify them—have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ). Based on ARSQ data from 813 participants assessed after 5 min eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer's disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease. PMID:23964225

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.

Resting states are resting traits--an FMRI study of sex differences and menstrual cycle effects in resting state cognitive control networks.

PubMed

Hjelmervik, Helene; Hausmann, Markus; Osnes, Berge; Westerhausen, René; Specht, Karsten

2014-01-01

To what degree resting state fMRI is stable or susceptible to internal mind states of the individual is currently an issue of debate. To address this issue, the present study focuses on sex differences and investigates whether resting state fMRI is stable in men and women or changes within relative short-term periods (i.e., across the menstrual cycle). Due to the fact that we recently reported menstrual cycle effects on cognitive control based on data collected during the same sessions, the current study is particularly interested in fronto-parietal resting state networks. Resting state fMRI was measured in sixteen women during three different cycle phases (menstrual, follicular, and luteal). Fifteen men underwent three sessions in corresponding time intervals. We used independent component analysis to identify four fronto-parietal networks. The results showed sex differences in two of these networks with women exhibiting higher functional connectivity in general, including the prefrontal cortex. Menstrual cycle effects on resting states were non-existent. It is concluded that sex differences in resting state fMRI might reflect sexual dimorphisms in the brain rather than transitory activating effects of sex hormones on the functional connectivity in the resting brain.

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.

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.

Heart rate autonomic regulation system at rest and during paced breathing among patients with CRPS as compared to age-matched healthy controls.

PubMed

Bartur, Gadi; Vatine, Jean-Jacques; Raphaely-Beer, Noa; Peleg, Sara; Katz-Leurer, Michal

2014-09-01

The objective of this study is to assess the autonomic nerve heart rate regulation system at rest and its immediate response to paced breathing among patients with complex regional pain syndrome (CRPS) as compared with age-matched healthy controls. Quasiexperimental. Outpatient clinic. Ten patients with CRPS and 10 age- and sex-matched controls. Participants underwent Holter ECG (NorthEast Monitoring, Inc., Maynard, MA, USA) recording during rest and biofeedback-paced breathing session. Heart rate variability (HRV), time, and frequency measures were assessed. HRV and time domain values were significantly lower at rest among patients with CRPS as compared with controls. A significant association was noted between pain rank and HRV frequency measures at rest and during paced breathing; although both groups reduced breathing rate significantly during paced breathing, HRV time domain parameters increased only among the control group. The increased heart rate and decreased HRV at rest in patients with CRPS suggest a general autonomic imbalance. The inability of the patients to increase HRV time domain values during paced breathing may suggest that these patients have sustained stress response with minimal changeability in response to slow-paced breathing stimuli. Wiley Periodicals, Inc.

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.

Rest

PubMed Central

2015-01-01

Rest is a health-related phenomenon. Researchers have explored the phenomenon of rest, but further concept development is recommended. The aim of my study was to develop and describe a concept of rest, from interviews with a total of 63 participants about their lived experiences of rest. I performed the developing process in two stages: first with descriptive phenomenology and second with a hermeneutic approach. The concept of rest is comprised of the essences of both rest and “non-rest,” and there is a current movement between these two conditions in peoples’ lives. The essence of rest is being in harmony in motivation, feeling, and action. The essence of non-rest is being in disharmony in motivation, feeling, and action. The essences reveal some meaning constituents. Health care professionals and researchers can use the concept as a frame of reference in health care praxis and in applied research. PMID:28462307

[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.

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.

Resting-state theta band connectivity and graph analysis in generalized social anxiety disorder.

PubMed

Xing, Mengqi; Tadayonnejad, Reza; MacNamara, Annmarie; Ajilore, Olusola; DiGangi, Julia; Phan, K Luan; Leow, Alex; Klumpp, Heide

2017-01-01

Functional magnetic resonance imaging (fMRI) resting-state studies show generalized social anxiety disorder (gSAD) is associated with disturbances in networks involved in emotion regulation, emotion processing, and perceptual functions, suggesting a network framework is integral to elucidating the pathophysiology of gSAD. However, fMRI does not measure the fast dynamic interconnections of functional networks. Therefore, we examined whole-brain functional connectomics with electroencephalogram (EEG) during resting-state. Resting-state EEG data was recorded for 32 patients with gSAD and 32 demographically-matched healthy controls (HC). Sensor-level connectivity analysis was applied on EEG data by using Weighted Phase Lag Index (WPLI) and graph analysis based on WPLI was used to determine clustering coefficient and characteristic path length to estimate local integration and global segregation of networks. WPLI results showed increased oscillatory midline coherence in the theta frequency band indicating higher connectivity in the gSAD relative to HC group during rest. Additionally, WPLI values positively correlated with state anxiety levels within the gSAD group but not the HC group. Our graph theory based connectomics analysis demonstrated increased clustering coefficient and decreased characteristic path length in theta-based whole brain functional organization in subjects with gSAD compared to HC. Theta-dependent interconnectivity was associated with state anxiety in gSAD and an increase in information processing efficiency in gSAD (compared to controls). Results may represent enhanced baseline self-focused attention, which is consistent with cognitive models of gSAD and fMRI studies implicating emotion dysregulation and disturbances in task negative networks (e.g., default mode network) in gSAD.

CyREST: Turbocharging Cytoscape Access for External Tools via a RESTful API.

PubMed

Ono, Keiichiro; Muetze, Tanja; Kolishovski, Georgi; Shannon, Paul; Demchak, Barry

2015-01-01

As bioinformatic workflows become increasingly complex and involve multiple specialized tools, so does the difficulty of reliably reproducing those workflows. Cytoscape is a critical workflow component for executing network visualization, analysis, and publishing tasks, but it can be operated only manually via a point-and-click user interface. Consequently, Cytoscape-oriented tasks are laborious and often error prone, especially with multistep protocols involving many networks. In this paper, we present the new cyREST Cytoscape app and accompanying harmonization libraries. Together, they improve workflow reproducibility and researcher productivity by enabling popular languages (e.g., Python and R, JavaScript, and C#) and tools (e.g., IPython/Jupyter Notebook and RStudio) to directly define and query networks, and perform network analysis, layouts and renderings. We describe cyREST's API and overall construction, and present Python- and R-based examples that illustrate how Cytoscape can be integrated into large scale data analysis pipelines. cyREST is available in the Cytoscape app store (http://apps.cytoscape.org) where it has been downloaded over 1900 times since its release in late 2014.

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.

Microcontroller-based underwater acoustic ECG telemetry system.

PubMed

Istepanian, R S; Woodward, B

1997-06-01

This paper presents a microcontroller-based underwater acoustic telemetry system for digital transmission of the electrocardiogram (ECG). The system is designed for the real time, through-water transmission of data representing any parameter, and it was used initially for transmitting in multiplexed format the heart rate, breathing rate and depth of a diver using self-contained underwater breathing apparatus (SCUBA). Here, it is used to monitor cardiovascular reflexes during diving and swimming. The programmable capability of the system provides an effective solution to the problem of transmitting data in the presence of multipath interference. An important feature of the paper is a comparative performance analysis of two encoding methods, Pulse Code Modulation (PCM) and Pulse Position Modulation (PPM).

Time-varying analysis of electrodermal activity during exercise

PubMed Central

Reljin, Natasa; Mills, Craig; Mills, Ian; Florian, John P.; VanHeest, Jaci L.; Chon, Ki H.

2018-01-01

The electrodermal activity (EDA) is a useful tool for assessing skin sympathetic nervous activity. Using spectral analysis of EDA data at rest, we have previously found that the spectral band which is the most sensitive to central sympathetic control is largely confined to 0.045 to 0.25 Hz. However, the frequency band associated with sympathetic control in EDA has not been studied for exercise conditions. Establishing the band limits more precisely is important to ensure the accuracy and sensitivity of the technique. As exercise intensity increases, it is intuitive that the frequencies associated with the autonomic dynamics should also increase accordingly. Hence, the aim of this study was to examine the appropriate frequency band associated with the sympathetic nervous system in the EDA signal during exercise. Eighteen healthy subjects underwent a sub-maximal exercise test, including a resting period, walking, and running, until achieving 85% of maximum heart rate. Both EDA and ECG data were measured simultaneously for all subjects. The ECG was used to monitor subjects’ instantaneous heart rate, which was used to set the experiment’s end point. We found that the upper bound of the frequency band (Fmax) containing the EDA spectral power significantly shifted to higher frequencies when subjects underwent prolonged low-intensity (Fmax ~ 0.28) and vigorous-intensity exercise (Fmax ~ 0.37 Hz) when compared to the resting condition. In summary, we have found shifting of the sympathetic dynamics to higher frequencies in the EDA signal when subjects undergo physical activity. PMID:29856815

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.

Data on association between QRS duration on prehospital ECG and mortality in patients with confirmed STEMI.

PubMed

Hansen, Rikke; Frydland, Martin; Møller-Helgestad, Ole Kristian; Lindholm, Matias Greve; Jensen, Lisette Okkels; Holmvang, Lene; Ravn, Hanne Berg; Kjærgaard, Jesper; Hassager, Christian; Møller, Jacob Eifer

2017-12-01

Data presented in this article relates to the research article entitled " Association between QRS duration on prehospital ECG and mortality in patients with suspected STEMI" (Hansen et al., in press) [1]. Data on the prognostic effect of automatically recoded QRS duration on prehospital ECG and presence of classic left and right bundle branch block in 1777 consecutive patients with confirmed ST segment elevation AMI is presented. Multivariable analysis, suggested that QRS duration >111 ms, left bundle branch block and right bundle branch block were independent predictors of 30 days all-cause mortality. For interpretation and discussion of these data, refer to the research article referenced above.

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.

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2017-10-13

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis...TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-15-2-0032 5b. GRANT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI...Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad goal is

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.

An Advanced Bio-Inspired PhotoPlethysmoGraphy (PPG) and ECG Pattern Recognition System for Medical Assessment

PubMed Central

Rundo, Francesco; Ortis, Alessandro

2018-01-01

Physiological signals are widely used to perform medical assessment for monitoring an extensive range of pathologies, usually related to cardio-vascular diseases. Among these, both PhotoPlethysmoGraphy (PPG) and Electrocardiography (ECG) signals are those more employed. PPG signals are an emerging non-invasive measurement technique used to study blood volume pulsations through the detection and analysis of the back-scattered optical radiation coming from the skin. ECG is the process of recording the electrical activity of the heart over a period of time using electrodes placed on the skin. In the present paper we propose a physiological ECG/PPG “combo” pipeline using an innovative bio-inspired nonlinear system based on a reaction-diffusion mathematical model, implemented by means of the Cellular Neural Network (CNN) methodology, to filter PPG signal by assigning a recognition score to the waveforms in the time series. The resulting “clean” PPG signal exempts from distortion and artifacts is used to validate for diagnostic purpose an EGC signal simultaneously detected for a same patient. The multisite combo PPG-ECG system proposed in this work overpasses the limitations of the state of the art in this field providing a reliable system for assessing the above-mentioned physiological parameters and their monitoring over time for robust medical assessment. The proposed system has been validated and the results confirmed the robustness of the proposed approach. PMID:29385774

An Advanced Bio-Inspired PhotoPlethysmoGraphy (PPG) and ECG Pattern Recognition System for Medical Assessment.

PubMed

Rundo, Francesco; Conoci, Sabrina; Ortis, Alessandro; Battiato, Sebastiano

2018-01-30

Physiological signals are widely used to perform medical assessment for monitoring an extensive range of pathologies, usually related to cardio-vascular diseases. Among these, both PhotoPlethysmoGraphy (PPG) and Electrocardiography (ECG) signals are those more employed. PPG signals are an emerging non-invasive measurement technique used to study blood volume pulsations through the detection and analysis of the back-scattered optical radiation coming from the skin. ECG is the process of recording the electrical activity of the heart over a period of time using electrodes placed on the skin. In the present paper we propose a physiological ECG/PPG "combo" pipeline using an innovative bio-inspired nonlinear system based on a reaction-diffusion mathematical model, implemented by means of the Cellular Neural Network (CNN) methodology, to filter PPG signal by assigning a recognition score to the waveforms in the time series. The resulting "clean" PPG signal exempts from distortion and artifacts is used to validate for diagnostic purpose an EGC signal simultaneously detected for a same patient. The multisite combo PPG-ECG system proposed in this work overpasses the limitations of the state of the art in this field providing a reliable system for assessing the above-mentioned physiological parameters and their monitoring over time for robust medical assessment. The proposed system has been validated and the results confirmed the robustness of the proposed approach.

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.

Evaluation of ECG-gated [(11)C]acetate PET for measuring left ventricular volumes, mass, and myocardial external efficiency.

PubMed

Hansson, Nils Henrik; Tolbod, Lars; Harms, Johannes; Wiggers, Henrik; Kim, Won Yong; Hansen, Esben; Zaremba, Tomas; Frøkiær, Jørgen; Jakobsen, Steen; Sørensen, Jens

2016-08-01

Noninvasive estimation of myocardial external efficiency (MEE) requires measurements of left ventricular (LV) oxygen consumption with [(11)C]acetate PET in addition to LV stroke volume and mass with cardiovascular magnetic resonance (CMR). Measuring LV geometry directly from ECG-gated [(11)C]acetate PET might enable MEE evaluation from a single PET scan. Therefore, we sought to establish the accuracy of measuring LV volumes, mass, and MEE directly from ECG-gated [(11)C]acetate PET. Thirty-five subjects with aortic valve stenosis underwent ECG-gated [(11)C]acetate PET and CMR. List mode PET data were rebinned into 16-bin ECG-gated uptake images before measuring LV volumes and mass using commercial software and compared to CMR. Dynamic datasets were used for calculation of mean LV oxygen consumption and MEE. LV mass, volumes, and ejection fraction measured by CMR and PET correlated strongly (r = 0.86-0.92, P < .001 for all), but were underestimated by PET (P < .001 for all except ESV P = .79). PET-based MEE, corrected for bias, correlated fairly with PET/CMR-based MEE (r = 0.60, P < .001, bias -3 ± 21%, P = .56). PET-based MEE bias was strongly associated with LV wall thickness. Although analysis-related improvements in accuracy are recommended, LV geometry estimated from ECG-gated [(11)C]acetate PET correlate excellently with CMR and can indeed be used to evaluate MEE.

Reduction of resting heart rate with antianginal drugs: review and meta-analysis.

PubMed

Cucherat, Michel; Borer, Jeffrey S

2012-07-01

The benefit of heart rate (HR) reduction in patients with stable coronary artery disease is well demonstrated for symptom prevention and relief, and benefits on outcomes are being actively investigated. We aimed to quantify the reduction in resting HR induced by 5 antianginal drugs frequently used for symptom prevention (diltiazem, verapamil, atenolol, metoprolol, and ivabradine) in stable angina pectoris. We identified studies published between 1966 and 2007 in PubMed, Embase, and the Cochrane database and reviewed the bibliographies to locate additional studies. Eligible studies were double-blind, randomized, placebo-controlled trials in patients with stable angina. Trials were combined using weighted mean difference and fixed-effect model meta-analysis. The main outcome measure was resting HR at the study end. For diltiazem, resting HR reduction versus placebo ranged from -0.08 beats per minute (bpm) [95% confidence interval (CI) -1.5 to +1.4] for 120 mg/d to -8.0 bpm (95% CI, -11.1 to -5.0) with 360 mg/d. For sustained-release diltiazem, there was a reduction in resting HR of -4.5 bpm (95% CI, -6.4 to -2.5), with no dose-response relationship (heterogeneity P = 0.62). Resting HR reductions for the other agents were -3.2 bpm (95% CI, -5.1 to -1.3) for verapamil (with no dose-response relationship, heterogeneity P = 0.87); -19.0 bpm (95% CI, -20.4 to -17.6) for atenolol; -13.2 bpm (95% CI, -14.7 to -11.7) for metoprolol (with greater reductions for 150 mg/d and long-acting 190 mg/d); and between -9.3 bpm (95% CI, -13.8 to -4.8) and -19.6 bpm (95% CI, -23.8 to -15.4) for ivabradine. Ivabradine, atenolol, and metoprolol give similar reductions in resting HR (-10 to -20 bpm), whereas verapamil and diltiazem produce only marginal reductions (<10 bpm).

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.

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.

5 A study analysing the diagnostic performance of ECG interpretation for 30-day major cardiac events in the emergency department.

PubMed

Morris, Niall; Body, Rick

2017-12-01

This study evaluates the diagnostic accuracy of an Emergency Medicine (EM) clinician at identifying ischaemia on an ECG using 30-day major adverse cardiac events (MACE) as the primary outcome. This is a secondary analysis of a prospective, multi-centre, observational cohort at 14 centres: the Bedside Evaluation of Sensitive Troponin study. All fourteen Emergency Departments were based in the United Kingdom. Emergency physicians' assessments of the ECG were collected using a standardised form. Clinicians were asked to judge whether the ECG demonstrated ischaemia, the presence of ST depression (STD) and if there was abnormal T wave inversion (ATWI). Patients provided written informed consent and underwent serial high sensitivity troponin testing. 30 day follow-up was performed by research nurses using a standardised form via telephone. The primary outcome was 30-day major adverse cardiac events, defined as acute myocardial infarction, any cause of death and coronary revascularisation. In total, 756 patients were included in the analysis. Clinicians' ECG diagnosis of ischaemia for 30-day MACE: ECG ischaemia produces a sensitivity (Sn) of 19.54% (95% CI:11.81% to 29.43%), specificity (Sp) of 93.27% (95% CI:91.10% to 95.05%), positive predictive value (PPV) of 27.42% (95% CI:18.47% to 38.65%) and negative predictive value (NPV) of 89.91% (95%CI 88.92% to 90.83%). ECG ST depression produces Sn of 16.09% (9.09% to 25.52%), Sp of 89.69% (87.13% to 91.89%), PPV 16.87 (10.68% to 25.62%), and NPV 89.15% (88.19% to 90.04%). ECG ATWI produces Sn of 4.60% (1.27% to 11.36%), Sp of 91.63% (89.27% to 93.62%), PPV of 6.67% (2.59% to 16.12%) and NPV of 88.07% (87.52% to 88.6). This is the first prospective, multi-centre cohort study, that assess the diagnostic performance of EM clinician's ECG interpretation, with 30-day MACE as the primary outcome. The findings are highly relevant to EM as they represent the ECG terms used by popular acute coronary syndrome clinical decision rules

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.

Detection and evaluation of ventricular repolarization alternans: an approach to combined ECG, thoracic impedance, and beat-to-beat heart rate variability analysis.

PubMed

Kriščiukaitis, Algimantas; Šimoliūnienė, Renata; Macas, Andrius; Petrolis, Robertas; Drėgūnas, Kęstutis; Bakšytė, Giedrė; Pieteris, Linas; Bertašienė, Zita; Žaliūnas, Remigijus

2014-01-01

Beat-to-beat alteration in ventricles repolarization reflected by alternans of amplitude and/or shape of ECG S-T,T segment (TWA) is known as phenomena related with risk of severe arrhythmias leading to sudden cardiac death. Technical difficulties have caused limited its usage in clinical diagnostics. Possibilities to register and analyze multimodal signals reflecting heart activity inspired search for new technical solutions. First objective of this study was to test whether thoracic impedance signal and beat-to-beat heart rate reflect repolarization alternans detected as TWA. The second objective was revelation of multimodal signal features more comprehensively representing the phenomena and increasing its prognostic usefulness. ECG, and thoracic impedance signal recordings made during 24h follow-up of the patients hospitalized in acute phase of myocardial infarction were used for investigation. Signal morphology variations reflecting estimates were obtained by the principal component analysis-based method. Clinical outcomes of patients (survival and/or rehospitalization in 6 and 12 months) were compared to repolarization alternans and heart rate variability estimates. Repolarization alternans detected as TWA was also reflected in estimates of thoracic impedance signal shape and variation in beat-to-beat heart rate. All these parameters showed correlation with clinical outcomes of patients. The strongest significant correlation showed magnitude of alternans in estimates of thoracic impedance signal shape. The features of ECG, thoracic impedance signal and beat-to-beat variability of heart rate, give comprehensive estimates of repolarization alternans, which correlate, with clinical outcomes of the patients and we recommend using them to improve diagnostic reliability. Copyright © 2014 Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Resting State Networks and Consciousness

PubMed Central

Heine, Lizette; Soddu, Andrea; Gómez, Francisco; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Demertzi, Athena

2012-01-01

In order to better understand the functional contribution of resting state activity to conscious cognition, we aimed to review increases and decreases in functional magnetic resonance imaging (fMRI) functional connectivity under physiological (sleep), pharmacological (anesthesia), and pathological altered states of consciousness, such as brain death, coma, vegetative state/unresponsive wakefulness syndrome, and minimally conscious state. The reviewed resting state networks were the DMN, left and right executive control, salience, sensorimotor, auditory, and visual networks. We highlight some methodological issues concerning resting state analyses in severely injured brains mainly in terms of hypothesis-driven seed-based correlation analysis and data-driven independent components analysis approaches. Finally, we attempt to contextualize our discussion within theoretical frameworks of conscious processes. We think that this “lesion” approach allows us to better determine the necessary conditions under which normal conscious cognition takes place. At the clinical level, we acknowledge the technical merits of the resting state paradigm. Indeed, fast and easy acquisitions are preferable to activation paradigms in clinical populations. Finally, we emphasize the need to validate the diagnostic and prognostic value of fMRI resting state measurements in non-communicating brain damaged patients. PMID:22969735

Detection of mental stress due to oral academic examination via ultra-short-term HRV analysis.

PubMed

Castaldo, R; Xu, W; Melillo, P; Pecchia, L; Santamaria, L; James, C

2016-08-01

Mental stress may cause cognitive dysfunctions, cardiovascular disorders and depression. Mental stress detection via short-term Heart Rate Variability (HRV) analysis has been widely explored in the last years, while ultra-short term (less than 5 minutes) HRV has been not. This study aims to detect mental stress using linear and non-linear HRV features extracted from 3 minutes ECG excerpts recorded from 42 university students, during oral examination (stress) and at rest after a vacation. HRV features were then extracted and analyzed according to the literature using validated software tools. Statistical and data mining analysis were then performed on the extracted HRV features. The best performing machine learning method was the C4.5 tree algorithm, which discriminated between stress and rest with sensitivity, specificity and accuracy rate of 78%, 80% and 79% respectively.

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.

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

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.

Caffeine and diuresis during rest and exercise: A meta-analysis

PubMed Central

Coca, Aitor; Casa, Douglas J.; Antonio, Jose; Green, James M.; Bishop, Phillip A.

2016-01-01

Objectives Although ergogenic, acute caffeine ingestion may increase urine volume, prompting concerns about fluid balance during exercise and sport events. This meta-analysis evaluated caffeine induced diuresis in adults during rest and exercise. Design Meta-analysis. Methods A search of three databases was completed on November 1, 2013. Only studies that involved healthy adults and provided sufficient information concerning the effect size (ES) of caffeine ingestion on urine volume were included. Sixteen studies met the inclusion criteria, providing a total of 28 ESs for the meta-analysis. Heterogeneity was assessed using a random-effects model. Results The median caffeine dosage was 300 mg. The overall ES of 0.29 (95% confidence interval (CI) = 0.11-0.48, p = 0.001) corresponds to an increase in urine volume of 109 ± 195 mL or 16.0 ± 19.2% for caffeine ingestion vs. non-caffeine conditions. Subgroup meta-analysis confirmed exercise as a strong moderator: active ES = 0.10, 95% CI = −0.07 to 0.27, p = 0.248 vs. resting ES = 0.54, 95% CI = 0.22–0.85, p = 0.001 (Cochran's Q, p = 0.019). Females (ES = 0.75,95% CI = 0.38–1.13, p< 0.001) were more susceptible to diuretic effects than males (ES = 0.13,95% CI = −0.05 to 0.31, p = 0.158) (Cochran's Q, p = 0.003). Conclusions Caffeine exerted a minor diuretic effect which was negated by exercise. Concerns regarding unwanted fluid loss associated with caffeine consumption are unwarranted particularly when ingestion precedes exercise. PMID:25154702

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