A real time ECG signal processing application for arrhythmia detection on portable devices

NASA Astrophysics Data System (ADS)

Georganis, A.; Doulgeraki, N.; Asvestas, P.

2017-11-01

Arrhythmia describes the disorders of normal heart rate, which, depending on the case, can even be fatal for a patient with severe history of heart disease. The purpose of this work is to develop an application for heart signal visualization, processing and analysis in Android portable devices e.g. Mobile phones, tablets, etc. The application is able to retrieve the signal initially from a file and at a later stage this signal is processed and analysed within the device so that it can be classified according to the features of the arrhythmia. In the processing and analysing stage, different algorithms are included among them the Moving Average and Pan Tompkins algorithm as well as the use of wavelets, in order to extract features and characteristics. At the final stage, testing is performed by simulating our application in real-time records, using the TCP network protocol for communicating the mobile with a simulated signal source. The classification of ECG beat to be processed is performed by neural networks.

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.

Cardiac Arrhythmia Classification by Multi-Layer Perceptron and Convolution Neural Networks.

PubMed

Savalia, Shalin; Emamian, Vahid

2018-05-04

The electrocardiogram (ECG) plays an imperative role in the medical field, as it records heart signal over time and is used to discover numerous cardiovascular diseases. If a documented ECG signal has a certain irregularity in its predefined features, this is called arrhythmia, the types of which include tachycardia, bradycardia, supraventricular arrhythmias, and ventricular, etc. This has encouraged us to do research that consists of distinguishing between several arrhythmias by using deep neural network algorithms such as multi-layer perceptron (MLP) and convolution neural network (CNN). The TensorFlow library that was established by Google for deep learning and machine learning is used in python to acquire the algorithms proposed here. The ECG databases accessible at PhysioBank.com and kaggle.com were used for training, testing, and validation of the MLP and CNN algorithms. The proposed algorithm consists of four hidden layers with weights, biases in MLP, and four-layer convolution neural networks which map ECG samples to the different classes of arrhythmia. The accuracy of the algorithm surpasses the performance of the current algorithms that have been developed by other cardiologists in both sensitivity and precision.

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

Detection of Life Threatening Ventricular Arrhythmia Using Digital Taylor Fourier Transform.

PubMed

Tripathy, Rajesh K; Zamora-Mendez, Alejandro; de la O Serna, José A; Paternina, Mario R Arrieta; Arrieta, Juan G; Naik, Ganesh R

2018-01-01

Accurate detection and classification of life-threatening ventricular arrhythmia episodes such as ventricular fibrillation (VF) and rapid ventricular tachycardia (VT) from electrocardiogram (ECG) is a challenging problem for patient monitoring and defibrillation therapy. This paper introduces a novel method for detection and classification of life-threatening ventricular arrhythmia episodes. The ECG signal is decomposed into various oscillatory modes using digital Taylor-Fourier transform (DTFT). The magnitude feature and a novel phase feature namely the phase difference (PD) are evaluated from the mode Taylor-Fourier coefficients of ECG signal. The least square support vector machine (LS-SVM) classifier with linear and radial basis function (RBF) kernels is employed for detection and classification of VT vs. VF, non-shock vs. shock and VF vs. non-VF arrhythmia episodes. The accuracy, sensitivity, and specificity values obtained using the proposed method are 89.81, 86.38, and 93.97%, respectively for the classification of Non-VF and VF episodes. Comparison with the performance of the state-of-the-art features demonstrate the advantages of the proposition.

Detection of Life Threatening Ventricular Arrhythmia Using Digital Taylor Fourier Transform

PubMed Central

Tripathy, Rajesh K.; Zamora-Mendez, Alejandro; de la O Serna, José A.; Paternina, Mario R. Arrieta; Arrieta, Juan G.; Naik, Ganesh R.

2018-01-01

Accurate detection and classification of life-threatening ventricular arrhythmia episodes such as ventricular fibrillation (VF) and rapid ventricular tachycardia (VT) from electrocardiogram (ECG) is a challenging problem for patient monitoring and defibrillation therapy. This paper introduces a novel method for detection and classification of life-threatening ventricular arrhythmia episodes. The ECG signal is decomposed into various oscillatory modes using digital Taylor-Fourier transform (DTFT). The magnitude feature and a novel phase feature namely the phase difference (PD) are evaluated from the mode Taylor-Fourier coefficients of ECG signal. The least square support vector machine (LS-SVM) classifier with linear and radial basis function (RBF) kernels is employed for detection and classification of VT vs. VF, non-shock vs. shock and VF vs. non-VF arrhythmia episodes. The accuracy, sensitivity, and specificity values obtained using the proposed method are 89.81, 86.38, and 93.97%, respectively for the classification of Non-VF and VF episodes. Comparison with the performance of the state-of-the-art features demonstrate the advantages of the proposition.

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.

Classification of cardiac arrhythmias using competitive networks.

PubMed

Leite, Cicilia R M; Martin, Daniel L; Sizilio, Glaucia R A; Dos Santos, Keylly E A; de Araujo, Bruno G; Valentim, Ricardo A M; Neto, Adriao D D; de Melo, Jorge D; Guerreiro, Ana M G

2010-01-01

Information generated by sensors that collect a patient's vital signals are continuous and unlimited data sequences. Traditionally, this information requires special equipment and programs to monitor them. These programs process and react to the continuous entry of data from different origins. Thus, the purpose of this study is to analyze the data produced by these biomedical devices, in this case the electrocardiogram (ECG). Processing uses a neural classifier, Kohonen competitive neural networks, detecting if the ECG shows any cardiac arrhythmia. In fact, it is possible to classify an ECG signal and thereby detect if it is exhibiting or not any alteration, according to normality.

An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects.

PubMed

Kim, Jinkwon; Min, Se Dong; Lee, Myoungho

2011-06-27

Numerous studies have been conducted regarding a heartbeat classification algorithm over the past several decades. However, many algorithms have also been studied to acquire robust performance, as biosignals have a large amount of variation among individuals. Various methods have been proposed to reduce the differences coming from personal characteristics, but these expand the differences caused by arrhythmia. In this paper, an arrhythmia classification algorithm using a dedicated wavelet adapted to individual subjects is proposed. We reduced the performance variation using dedicated wavelets, as in the ECG morphologies of the subjects. The proposed algorithm utilizes morphological filtering and a continuous wavelet transform with a dedicated wavelet. A principal component analysis and linear discriminant analysis were utilized to compress the morphological data transformed by the dedicated wavelets. An extreme learning machine was used as a classifier in the proposed algorithm. A performance evaluation was conducted with the MIT-BIH arrhythmia database. The results showed a high sensitivity of 97.51%, specificity of 85.07%, accuracy of 97.94%, and a positive predictive value of 97.26%. The proposed algorithm achieves better accuracy than other state-of-the-art algorithms with no intrasubject between the training and evaluation datasets. And it significantly reduces the amount of intervention needed by physicians.

An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects

PubMed Central

2011-01-01

Background Numerous studies have been conducted regarding a heartbeat classification algorithm over the past several decades. However, many algorithms have also been studied to acquire robust performance, as biosignals have a large amount of variation among individuals. Various methods have been proposed to reduce the differences coming from personal characteristics, but these expand the differences caused by arrhythmia. Methods In this paper, an arrhythmia classification algorithm using a dedicated wavelet adapted to individual subjects is proposed. We reduced the performance variation using dedicated wavelets, as in the ECG morphologies of the subjects. The proposed algorithm utilizes morphological filtering and a continuous wavelet transform with a dedicated wavelet. A principal component analysis and linear discriminant analysis were utilized to compress the morphological data transformed by the dedicated wavelets. An extreme learning machine was used as a classifier in the proposed algorithm. Results A performance evaluation was conducted with the MIT-BIH arrhythmia database. The results showed a high sensitivity of 97.51%, specificity of 85.07%, accuracy of 97.94%, and a positive predictive value of 97.26%. Conclusions The proposed algorithm achieves better accuracy than other state-of-the-art algorithms with no intrasubject between the training and evaluation datasets. And it significantly reduces the amount of intervention needed by physicians. PMID:21707989

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.

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.

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.

Temporal abstraction and inductive logic programming for arrhythmia recognition from electrocardiograms.

PubMed

Carrault, G; Cordier, M-O; Quiniou, R; Wang, F

2003-07-01

This paper proposes a novel approach to cardiac arrhythmia recognition from electrocardiograms (ECGs). ECGs record the electrical activity of the heart and are used to diagnose many heart disorders. The numerical ECG is first temporally abstracted into series of time-stamped events. Temporal abstraction makes use of artificial neural networks to extract interesting waves and their features from the input signals. A temporal reasoner called a chronicle recogniser processes such series in order to discover temporal patterns called chronicles which can be related to cardiac arrhythmias. Generally, it is difficult to elicit an accurate set of chronicles from a doctor. Thus, we propose to learn automatically from symbolic ECG examples the chronicles discriminating the arrhythmias belonging to some specific subset. Since temporal relationships are of major importance, inductive logic programming (ILP) is the tool of choice as it enables first-order relational learning. The approach has been evaluated on real ECGs taken from the MIT-BIH database. The performance of the different modules as well as the efficiency of the whole system is presented. The results are rather good and demonstrate that integrating numerical techniques for low level perception and symbolic techniques for high level classification is very valuable.

Arrhythmia Evaluation in Wearable ECG Devices

PubMed Central

Sadrawi, Muammar; Lin, Chien-Hung; Hsieh, Yita; Kuo, Chia-Chun; Chien, Jen Chien; Haraikawa, Koichi; Abbod, Maysam F.; Shieh, Jiann-Shing

2017-01-01

This study evaluates four databases from PhysioNet: The American Heart Association database (AHADB), Creighton University Ventricular Tachyarrhythmia database (CUDB), MIT-BIH Arrhythmia database (MITDB), and MIT-BIH Noise Stress Test database (NSTDB). The ANSI/AAMI EC57:2012 is used for the evaluation of the algorithms for the supraventricular ectopic beat (SVEB), ventricular ectopic beat (VEB), atrial fibrillation (AF), and ventricular fibrillation (VF) via the evaluation of the sensitivity, positive predictivity and false positive rate. Sample entropy, fast Fourier transform (FFT), and multilayer perceptron neural network with backpropagation training algorithm are selected for the integrated detection algorithms. For this study, the result for SVEB has some improvements compared to a previous study that also utilized ANSI/AAMI EC57. In further, VEB sensitivity and positive predictivity gross evaluations have greater than 80%, except for the positive predictivity of the NSTDB database. For AF gross evaluation of MITDB database, the results show very good classification, excluding the episode sensitivity. In advanced, for VF gross evaluation, the episode sensitivity and positive predictivity for the AHADB, MITDB, and CUDB, have greater than 80%, except for MITDB episode positive predictivity, which is 75%. The achieved results show that the proposed integrated SVEB, VEB, AF, and VF detection algorithm has an accurate classification according to ANSI/AAMI EC57:2012. In conclusion, the proposed integrated detection algorithm can achieve good accuracy in comparison with other previous studies. Furthermore, more advanced algorithms and hardware devices should be performed in future for arrhythmia detection and evaluation. PMID:29068369

ECG-based 4D-dose reconstruction of cardiac arrhythmia ablation with carbon ion beams: application in a porcine model

NASA Astrophysics Data System (ADS)

Richter, Daniel; Immo Lehmann, H.; Eichhorn, Anna; Constantinescu, Anna M.; Kaderka, Robert; Prall, Matthias; Lugenbiel, Patrick; Takami, Mitsuru; Thomas, Dierk; Bert, Christoph; Durante, Marco; Packer, Douglas L.; Graeff, Christian

2017-09-01

Noninvasive ablation of cardiac arrhythmia by scanned particle radiotherapy is highly promising, but especially challenging due to cardiac and respiratory motion. Irradiations for catheter-free ablation in intact pigs were carried out at the GSI Helmholtz Center in Darmstadt using scanned carbon ions. Here, we present real-time electrocardiogram (ECG) data to estimate time-resolved (4D) delivered dose. For 11 animals, surface ECGs and temporal structure of beam delivery were acquired during irradiation. R waves were automatically detected from surface ECGs. Pre-treatment ECG-triggered 4D-CT phases were synchronized to the R-R interval. 4D-dose calculation was performed using GSI’s in-house 4D treatment planning system. Resulting dose distributions were assessed with respect to coverage (D95 and V95), heterogeneity (HI  =  D5-D95) and normal tissue exposure. Final results shown here were performed offline, but first calculations were started shortly after irradiation The D95 for TV and PTV was above 95% for 10 and 8 out of 11 animals, respectively. HI was reduced for PTV versus TV volumes, especially for some of the animals targeted at the atrioventricular junction, indicating residual interplay effects due to cardiac motion. Risk structure exposure was comparable to static and 4D treatment planning simulations. ECG-based 4D-dose reconstruction is technically feasible in a patient treatment-like setting. Further development of the presented approach, such as real-time dose calculation, may contribute to safe, successful treatments using scanned ion beams for cardiac arrhythmia ablation.

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

PubMed

Bashir, Mohamed Ezzeldin A; Lee, Dong Gyu; Li, Meijing; Bae, Jang-Whan; Shon, Ho Sun; Cho, Myung Chan; Ryu, Keun Ho

2012-07-01

Coronary heart disease is being identified as the largest single cause of death along the world. The aim of a cardiac clinical information system is to achieve the best possible diagnosis of cardiac arrhythmias by electronic data processing. Cardiac information system that is designed to offer remote monitoring of patient who needed continues follow up is demanding. However, intra- and interpatient electrocardiogram (ECG) morphological descriptors are varying through the time as well as the computational limits pose significant challenges for practical implementations. The former requires that the classification model be adjusted continuously, and the latter requires a reduction in the number and types of ECG features, and thus, the computational burden, necessary to classify different arrhythmias. We propose the use of adaptive learning to automatically train the classifier on up-to-date ECG data, and employ adaptive feature selection to define unique feature subsets pertinent to different types of arrhythmia. Experimental results show that this hybrid technique outperforms conventional approaches and is, therefore, a promising new intelligent diagnostic tool.

Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection.

PubMed

Son, Junggab; Park, Juyoung; Oh, Heekuck; Bhuiyan, Md Zakirul Alam; Hur, Junbeom; Kang, Kyungtae

2017-06-12

Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components. The decision support server analyzes the heart activity, using the Pan-Tompkins algorithm to detect heartbeats and a decision tree to classify them. Our system protects sensing data and user privacy, which is an essential attribute of dependability, by adopting signal scrambling and anonymous identity schemes. We also employ a public key cryptosystem to enable secure communication between the entities. Simulations using data from the MIT-BIH arrhythmia database demonstrate that our system achieves a 95.74% success rate in heartbeat detection and almost a 96.63% accuracy in heartbeat classification, while successfully preserving privacy and securing communications among the involved entities.

Classification of ECG signal with Support Vector Machine Method for Arrhythmia Detection

NASA Astrophysics Data System (ADS)

Turnip, Arjon; Ilham Rizqywan, M.; Kusumandari, Dwi E.; Turnip, Mardi; Sihombing, Poltak

2018-03-01

An electrocardiogram is a potential bioelectric record that occurs as a result of cardiac activity. QRS Detection with zero crossing calculation is one method that can precisely determine peak R of QRS wave as part of arrhythmia detection. In this paper, two experimental scheme (2 minutes duration with different activities: relaxed and, typing) were conducted. From the two experiments it were obtained: accuracy, sensitivity, and positive predictivity about 100% each for the first experiment and about 79%, 93%, 83% for the second experiment, respectively. Furthermore, the feature set of MIT-BIH arrhythmia using the support vector machine (SVM) method on the WEKA software is evaluated. By combining the available attributes on the WEKA algorithm, the result is constant since all classes of SVM goes to the normal class with average 88.49% accuracy.

P wave detection in ECG signals using an extended Kalman filter: an evaluation in different arrhythmia contexts.

PubMed

Rahimpour, M; Mohammadzadeh Asl, B

2016-07-01

Monitoring atrial activity via P waves, is an important feature of the arrhythmia detection procedure. The aim of this paper is to present an algorithm for P wave detection in normal and some abnormal records by improving existing methods in the field of signal processing. In contrast to the classical approaches, which are completely blind to signal dynamics, our proposed method uses the extended Kalman filter, EKF25, to estimate the state variables of the equations modeling the dynamic of an ECG signal. This method is a modified version of the nonlinear dynamical model previously introduced for a generation of synthetic ECG signals and fiducial point extraction in normal ones. It is capable of estimating the separate types of activity of the heart with reasonable accuracy and performs well in the presence of morphological variations in the waveforms and ectopic beats. The MIT-BIH Arrhythmia and QT databases have been used to evaluate the performance of the proposed method. The results show that this method has Se  =  98.38% and Pr  =  96.74% in the overall records (considering normal and abnormal rhythms).

Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection †

PubMed Central

Son, Junggab; Park, Juyoung; Oh, Heekuck; Bhuiyan, Md Zakirul Alam; Hur, Junbeom; Kang, Kyungtae

2017-01-01

Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components. The decision support server analyzes the heart activity, using the Pan–Tompkins algorithm to detect heartbeats and a decision tree to classify them. Our system protects sensing data and user privacy, which is an essential attribute of dependability, by adopting signal scrambling and anonymous identity schemes. We also employ a public key cryptosystem to enable secure communication between the entities. Simulations using data from the MIT-BIH arrhythmia database demonstrate that our system achieves a 95.74% success rate in heartbeat detection and almost a 96.63% accuracy in heartbeat classification, while successfully preserving privacy and securing communications among the involved entities. PMID:28604628

Wireless monitoring of reconstructed 12-lead ECG in atrial fibrillation patients enables differential diagnosis of recurrent arrhythmias.

PubMed

Vukajlovic, Dejan; Gussak, Ihor; George, Samuel; Simic, Goran; Bojovic, Bosko; Hadzievski, Ljupco; Stojanovic, Bojan; Angelkov, Lazar; Panescu, Dorin

2011-01-01

Differential diagnosis of symptomatic events in post-ablation atrial fibrillation (AF) patients (pts) is important; in particular, accurate, reliable detection of AF or atrial flutter (AFL) is essential. However, existing remote monitoring devices usually require attached leads and are not suitable for prolonged monitoring; moreover, most do not provide sufficient information to assess atrial activity, since they generally monitor only 1-3 ECG leads and rely on RR interval variability for AF diagnosis. A new hand-held, wireless, symptom-activated event monitor (CardioBip; CB) does not require attached leads and hence can be conveniently used for extended periods. Moreover, CB provides data that enables remote reconstruction of full 12-lead ECG data including atrial signal information. We hypothesized that these CB features would enable accurate remote differential diagnosis of symptomatic arrhythmias in post-ablation AF pts. 21 pts who underwent catheter ablation for AF were instructed to make a CB transmission (TX) whenever palpitations, lightheadedness, or similar symptoms occurred, and at multiple times daily when asymptomatic, during a 60 day post-ablation time period. CB transmissions (TXs) were analyzed blindly by 2 expert readers, with differences adjudicated by consensus. 7 pts had no symptomatic episodes during the monitoring period. 14 of 21 pts had symptomatic events and made a total of 1699 TX, 164 of which were during symptoms. TX quality was acceptable for rhythm diagnosis and atrial activity in 96%. 118 TX from 10 symptomatic pts showed AF (96 TX from 10 pts) or AFL (22 TX from 3 pts), and 46 TX from 9 pts showed frequent PACs or PVCs. No other arrhythmias were detected. Five pts made symptomatic TX during AF/AFL and also during PACs/PVCs. Use of CB during symptomatic episodes enabled detection and differential diagnosis of symptomatic arrhythmias. The ability of CB to provide accurate reconstruction of 12 L ECGs including atrial activity, combined

Long-Term Continuous Ambulatory ECG Monitors and External Cardiac Loop Recorders for Cardiac Arrhythmia: A Health Technology Assessment

PubMed Central

Kabali, Conrad; Xie, Xuanqian; Higgins, Caroline

2017-01-01

Background Ambulatory electrocardiography (ECG) monitors are often used to detect cardiac arrhythmia. For patients with symptoms, an external cardiac loop recorder will often be recommended. The improved recording capacity of newer Holter monitors and similar devices, collectively known as longterm continuous ambulatory ECG monitors, suggests that they will perform just as well as, or better than, external loop recorders. This health technology assessment aimed to evaluate the effectiveness, cost-effectiveness, and budget impact of longterm continuous ECG monitors compared with external loop recorders in detecting symptoms of cardiac arrhythmia. Methods Based on our systematic search for studies published up to January 15, 2016, we did not identify any studies directly comparing the clinical effectiveness of longterm continuous ECG monitors and external loop recorders. Therefore, we conducted an indirect comparison, using a 24-hour Holter monitor as a common comparator. We used a meta-regression model to control for bias due to variation in device-wearing time and baseline syncope rate across studies. We conducted a similar systematic search for cost-utility and cost-effectiveness studies comparing the two types of devices; none were found. Finally, we used historical claims data (2006–2014) to estimate the future 5-year budget impact in Ontario, Canada, of continued public funding for both types of longterm ambulatory ECG monitors. Results Our clinical literature search yielded 7,815 non-duplicate citations, of which 12 cohort studies were eligible for indirect comparison. Seven studies assessed the effectiveness of longterm continuous monitors and five assessed external loop recorders. Both types of devices were more effective than a 24-hour Holter monitor, and we found no substantial difference between them in their ability to detect symptoms (risk difference 0.01; 95% confidence interval −0.18, 0.20). Using GRADE for network meta-analysis, we evaluated the

Perspective: A Dynamics-Based Classification of Ventricular Arrhythmias

PubMed Central

Weiss, James N.; Garfinkel, Alan; Karagueuzian, Hrayr S.; Nguyen, Thao P.; Olcese, Riccardo; Chen, Peng-Sheng; Qu, Zhilin

2015-01-01

Despite key advances in the clinical management of life-threatening ventricular arrhythmias, culminating with the development of implantable cardioverter-defibrillators and catheter ablation techniques, pharmacologic/biologic therapeutics have lagged behind. The fundamental issue is that biological targets are molecular factors. Diseases, however, represent emergent properties at the scale of the organism that result from dynamic interactions between multiple constantly changing molecular factors. For a pharmacologic/biologic therapy to be effective, it must target the dynamic processes that underlie the disease. Here we propose a classification of ventricular arrhythmias that is based on our current understanding of the dynamics occurring at the subcellular, cellular, tissue and organism scales, which cause arrhythmias by simultaneously generating arrhythmia triggers and exacerbating tissue vulnerability. The goal is to create a framework that systematically links these key dynamic factors together with fixed factors (structural and electrophysiological heterogeneity) synergistically promoting electrical dispersion and increased arrhythmia risk to molecular factors that can serve as biological targets. We classify ventricular arrhythmias into three primary dynamic categories related generally to unstable Ca cycling, reduced repolarization, and excess repolarization, respectively. The clinical syndromes, arrhythmia mechanisms, dynamic factors and what is known about their molecular counterparts are discussed. Based on this framework, we propose a computational-experimental strategy for exploring the links between molecular factors, fixed factors and dynamic factors that underlie life-threatening ventricular arrhythmias. The ultimate objective is to facilitate drug development by creating an in silico platform to evaluate and predict comprehensively how molecular interventions affect not only a single targeted arrhythmia, but all primary arrhythmia dynamics

Design of a hybrid model for cardiac arrhythmia classification based on Daubechies wavelet transform.

PubMed

Rajagopal, Rekha; Ranganathan, Vidhyapriya

2018-06-05

Automation in cardiac arrhythmia classification helps medical professionals make accurate decisions about the patient's health. The aim of this work was to design a hybrid classification model to classify cardiac arrhythmias. The design phase of the classification model comprises the following stages: preprocessing of the cardiac signal by eliminating detail coefficients that contain noise, feature extraction through Daubechies wavelet transform, and arrhythmia classification using a collaborative decision from the K nearest neighbor classifier (KNN) and a support vector machine (SVM). The proposed model is able to classify 5 arrhythmia classes as per the ANSI/AAMI EC57: 1998 classification standard. Level 1 of the proposed model involves classification using the KNN and the classifier is trained with examples from all classes. Level 2 involves classification using an SVM and is trained specifically to classify overlapped classes. The final classification of a test heartbeat pertaining to a particular class is done using the proposed KNN/SVM hybrid model. The experimental results demonstrated that the average sensitivity of the proposed model was 92.56%, the average specificity 99.35%, the average positive predictive value 98.13%, the average F-score 94.5%, and the average accuracy 99.78%. The results obtained using the proposed model were compared with the results of discriminant, tree, and KNN classifiers. The proposed model is able to achieve a high classification accuracy.

[Analysis of pacemaker ECGs].

PubMed

Israel, Carsten W; Ekosso-Ejangue, Lucy; Sheta, Mohamed-Karim

2015-09-01

The key to a successful analysis of a pacemaker electrocardiogram (ECG) is the application of the systematic approach used for any other ECG without a pacemaker: analysis of (1) basic rhythm and rate, (2) QRS axis, (3) PQ, QRS and QT intervals, (4) morphology of P waves, QRS, ST segments and T(U) waves and (5) the presence of arrhythmias. If only the most obvious abnormality of a pacemaker ECG is considered, wrong conclusions can easily be drawn. If a systematic approach is skipped it may be overlooked that e.g. atrial pacing is ineffective, the left ventricle is paced instead of the right ventricle, pacing competes with intrinsic conduction or that the atrioventricular (AV) conduction time is programmed too long. Apart from this analysis, a pacemaker ECG which is not clear should be checked for the presence of arrhythmias (e.g. atrial fibrillation, atrial flutter, junctional escape rhythm and endless loop tachycardia), pacemaker malfunction (e.g. atrial or ventricular undersensing or oversensing, atrial or ventricular loss of capture) and activity of specific pacing algorithms, such as automatic mode switching, rate adaptation, AV delay modifying algorithms, reaction to premature ventricular contractions (PVC), safety window pacing, hysteresis and noise mode. A systematic analysis of the pacemaker ECG almost always allows a probable diagnosis of arrhythmias and malfunctions to be made, which can be confirmed by pacemaker control and can often be corrected at the touch of the right button to the patient's benefit.

A 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

Computer-assisted education system for arrhythmia (CAESAR).

PubMed

Fukushima, M; Inoue, M; Fukunami, M; Ishikawa, K; Inada, H; Abe, H

1984-08-01

A computer-assisted education system for arrhythmia (CAESAR) was developed for students to acquire the ability to logically diagnose complicated arrhythmias. This system has a logical simulator of cardiac rhythm using a mathematical model of the impulse formation and conduction system of the heart. A simulated arrhythmia (ECG pattern) is given on a graphic display unit with simulated series of the action potential of five pacemaker centers and the "ladder diagram" of impulse formation and conduction, which show the mechanism of that arrhythmia. For the purpose of the evaluation of this system, 13 medical students were given two types of tests concerning arrhythmias before and after 2-hr learning with this system. The scores they obtained after learning increased significantly from 73.3 +/- 11.9 to 93.2 +/- 3.0 (P less than 0.001) in one test and from 47.2 +/- 17.9 to 64.9 +/- 19.6 (P less than 0.001) in another one. These results proved that this CAI system is useful and effective for training ECG interpretation of arrhythmias.

[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.

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

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.

Quantitative Assessment of Arrhythmia Using Non-linear Approach: A Non-invasive Prognostic Tool

NASA Astrophysics Data System (ADS)

Chakraborty, Monisha; Ghosh, Dipak

2017-12-01

Accurate prognostic tool to identify severity of Arrhythmia is yet to be investigated, owing to the complexity of the ECG signal. In this paper, we have shown that quantitative assessment of Arrhythmia is possible using non-linear technique based on "Hurst Rescaled Range Analysis". Although the concept of applying "non-linearity" for studying various cardiac dysfunctions is not entirely new, the novel objective of this paper is to identify the severity of the disease, monitoring of different medicine and their dose, and also to assess the efficiency of different medicine. The approach presented in this work is simple which in turn will help doctors in efficient disease management. In this work, Arrhythmia ECG time series are collected from MIT-BIH database. Normal ECG time series are acquired using POLYPARA system. Both time series are analyzed in thelight of non-linear approach following the method "Rescaled Range Analysis". The quantitative parameter, "Fractal Dimension" (D) is obtained from both types of time series. The major finding is that Arrhythmia ECG poses lower values of D as compared to normal. Further, this information can be used to access the severity of Arrhythmia quantitatively, which is a new direction of prognosis as well as adequate software may be developed for the use of medical practice.

Quantitative Assessment of Arrhythmia Using Non-linear Approach: A Non-invasive Prognostic Tool

NASA Astrophysics Data System (ADS)

Chakraborty, Monisha; Ghosh, Dipak

2018-04-01

Accurate prognostic tool to identify severity of Arrhythmia is yet to be investigated, owing to the complexity of the ECG signal. In this paper, we have shown that quantitative assessment of Arrhythmia is possible using non-linear technique based on "Hurst Rescaled Range Analysis". Although the concept of applying "non-linearity" for studying various cardiac dysfunctions is not entirely new, the novel objective of this paper is to identify the severity of the disease, monitoring of different medicine and their dose, and also to assess the efficiency of different medicine. The approach presented in this work is simple which in turn will help doctors in efficient disease management. In this work, Arrhythmia ECG time series are collected from MIT-BIH database. Normal ECG time series are acquired using POLYPARA system. Both time series are analyzed in thelight of non-linear approach following the method "Rescaled Range Analysis". The quantitative parameter, "Fractal Dimension" (D) is obtained from both types of time series. The major finding is that Arrhythmia ECG poses lower values of D as compared to normal. Further, this information can be used to access the severity of Arrhythmia quantitatively, which is a new direction of prognosis as well as adequate software may be developed for the use of medical practice.

Arrhythmia during extracorporeal shock wave lithotripsy.

PubMed

Zeng, Z R; Lindstedt, E; Roijer, A; Olsson, S B

1993-01-01

A prospective study of arrhythmia during extracorporeal shock wave lithotripsy (ESWL) was performed in 50 patients, using an EDAP LT01 piezoelectric lithotriptor. The 12-lead standard ECG was recorded continuously for 10 min before and during treatment. One or more atrial and/or ventricular ectopic beats occurred during ESWL in 15 cases (30%). The occurrence of arrhythmia was similar during right-sided and left-sided treatment. One patient developed multifocal ventricular premature beats and ventricular bigeminy; another had cardiac arrest for 13.5 s. It was found that various irregularities of the heart rhythm can be caused even by treatment with a lithotriptor using piezoelectric energy to create the shock wave. No evidence was found, however, that the shock wave itself rather than vagal activation and the action of sedo-analgesia was the cause of the arrhythmia. For patients with severe underlying heart disease and a history of complex arrhythmia, we suggest that the ECG be monitored during treatment. In other cases, we have found continuous monitoring of oxygen saturation and pulse rate with a pulse oximeter to be perfectly reliable for raising the alarm when depression of respiration and vaso-vagal reactions occur.

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.

Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records.

PubMed

Van Driest, Sara L; Wells, Quinn S; Stallings, Sarah; Bush, William S; Gordon, Adam; Nickerson, Deborah A; Kim, Jerry H; Crosslin, David R; Jarvik, Gail P; Carrell, David S; Ralston, James D; Larson, Eric B; Bielinski, Suzette J; Olson, Janet E; Ye, Zi; Kullo, Iftikhar J; Abul-Husn, Noura S; Scott, Stuart A; Bottinger, Erwin; Almoguera, Berta; Connolly, John; Chiavacci, Rosetta; Hakonarson, Hakon; Rasmussen-Torvik, Laura J; Pan, Vivian; Persell, Stephen D; Smith, Maureen; Chisholm, Rex L; Kitchner, Terrie E; He, Max M; Brilliant, Murray H; Wallace, John R; Doheny, Kimberly F; Shoemaker, M Benjamin; Li, Rongling; Manolio, Teri A; Callis, Thomas E; Macaya, Daniela; Williams, Marc S; Carey, David; Kapplinger, Jamie D; Ackerman, Michael J; Ritchie, Marylyn D; Denny, Joshua C; Roden, Dan M

2016-01-05

Large-scale DNA sequencing identifies incidental rare variants in established Mendelian disease genes, but the frequency of related clinical phenotypes in unselected patient populations is not well established. Phenotype data from electronic medical records (EMRs) may provide a resource to assess the clinical relevance of rare variants. To determine the clinical phenotypes from EMRs for individuals with variants designated as pathogenic by expert review in arrhythmia susceptibility genes. This prospective cohort study included 2022 individuals recruited for nonantiarrhythmic drug exposure phenotypes from October 5, 2012, to September 30, 2013, for the Electronic Medical Records and Genomics Network Pharmacogenomics project from 7 US academic medical centers. Variants in SCN5A and KCNH2, disease genes for long QT and Brugada syndromes, were assessed for potential pathogenicity by 3 laboratories with ion channel expertise and by comparison with the ClinVar database. Relevant phenotypes were determined from EMRs, with data available from 2002 (or earlier for some sites) through September 10, 2014. One or more variants designated as pathogenic in SCN5A or KCNH2. Arrhythmia or electrocardiographic (ECG) phenotypes defined by International Classification of Diseases, Ninth Revision (ICD-9) codes, ECG data, and manual EMR review. Among 2022 study participants (median age, 61 years [interquartile range, 56-65 years]; 1118 [55%] female; 1491 [74%] white), a total of 122 rare (minor allele frequency <0.5%) nonsynonymous and splice-site variants in 2 arrhythmia susceptibility genes were identified in 223 individuals (11% of the study cohort). Forty-two variants in 63 participants were designated potentially pathogenic by at least 1 laboratory or ClinVar, with low concordance across laboratories (Cohen κ = 0.26). An ICD-9 code for arrhythmia was found in 11 of 63 (17%) variant carriers vs 264 of 1959 (13%) of those without variants (difference, +4%; 95% CI, -5% to +13

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.

[Arrhythmias and heart blocks in flying personnel with mitral valve prolapses].

PubMed

Zakharov, V P; Karlov, V N; Bondareva, S V; Vlasov, V D

1999-01-01

Investigated were 76 pilots with ECG-verified mitral valve prolapses (MVP) of the 1st and 2nd degree (w/o profound regurgitation). There were various heart blocks and ECG repolarization changes in 35 cases. Comparison of results of the cardiovascular functional investigations of flyers with MVP displayed non-specific cardiac rhythm and conductance disturbances that were registered more often during ECG-monitoring or test loading. According to the data of this study, bicycle and treadmill ergometry revealed "pseudoischemic" shifts in ECG. Literary indications of a significant loss in human endurance of physical loads due to MVP combined with the strain-induced arrhythmia received the experimental confirmation. Probably, arrhythmias in flyers with diagnosed MVP are predominantly associated with electric instability of the myocardium against the autonomous dysfunction with prevailing adrenergic effects.

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

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.

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.

Improving ECG Classification Accuracy Using an Ensemble of Neural Network Modules

PubMed Central

Javadi, Mehrdad; Ebrahimpour, Reza; Sajedin, Atena; Faridi, Soheil; Zakernejad, Shokoufeh

2011-01-01

This paper illustrates the use of a combined neural network model based on Stacked Generalization method for classification of electrocardiogram (ECG) beats. In conventional Stacked Generalization method, the combiner learns to map the base classifiers' outputs to the target data. We claim adding the input pattern to the base classifiers' outputs helps the combiner to obtain knowledge about the input space and as the result, performs better on the same task. Experimental results support our claim that the additional knowledge according to the input space, improves the performance of the proposed method which is called Modified Stacked Generalization. In particular, for classification of 14966 ECG beats that were not previously seen during training phase, the Modified Stacked Generalization method reduced the error rate for 12.41% in comparison with the best of ten popular classifier fusion methods including Max, Min, Average, Product, Majority Voting, Borda Count, Decision Templates, Weighted Averaging based on Particle Swarm Optimization and Stacked Generalization. PMID:22046232

Low-power wireless ECG acquisition and classification system for body sensor networks.

PubMed

Lee, Shuenn-Yuh; Hong, Jia-Hua; Hsieh, Cheng-Han; Liang, Ming-Chun; Chang Chien, Shih-Yu; Lin, Kuang-Hao

2015-01-01

A low-power biosignal acquisition and classification system for body sensor networks is proposed. The proposed system consists of three main parts: 1) a high-pass sigma delta modulator-based biosignal processor (BSP) for signal acquisition and digitization, 2) a low-power, super-regenerative on-off keying transceiver for short-range wireless transmission, and 3) a digital signal processor (DSP) for electrocardiogram (ECG) classification. The BSP and transmitter circuits, which are the body-end circuits, can be operated for over 80 days using two 605 mAH zinc-air batteries as the power supply; the power consumption is 586.5 μW. As for the radio frequency receiver and DSP, which are the receiving-end circuits that can be integrated in smartphones or personal computers, power consumption is less than 1 mW. With a wavelet transform-based digital signal processing circuit and a diagnosis control by cardiologists, the accuracy of beat detection and ECG classification are close to 99.44% and 97.25%, respectively. All chips are fabricated in TSMC 0.18-μm standard CMOS process.

Emotional behavior and arrhythmias induced in cats by hypothalamic stimulation.

PubMed

Tashiro, N; Tanaka, T; Fukumoto, T; Hirata, K; Nakao, H

1985-03-18

As the relationship between emotional behavior and electrocardiographic (ECG) change induced by hypothalamic stimulation is poorly understood, eighty-four points in various areas within the hypothalamus in conscious cats were stimulated electrically through chronically implanted electrodes, the objective being to clarify the behavior accompanying ECG changes, in particular poststimulus arrhythmias. Forty-one of 84 points elicited behavioral patterns such as defense reaction, pseudo-rage and restlessness (classified as group A), and in twenty-one (51%) of these 41 points arrhythmias occurred after cessation of stimulation. Forty-three of 84 points elicited behavioral patterns including predatory, exploratory and other behavioral responses (classified as group B), and in three (7%) of 43 points, poststimulus arrhythmias followed. Under light anesthesia, stimulations of twofold current intensity were applied at these points, and the incidences of the arrhythmias did not change in either group. The arrhythmia-inducing area in the cases of group A was found to lie dorsal and caudal to the optic chiasma and to extend caudally in the fornix. Three points in the cases of group B were located in the outer area of the aforementioned area. These studies showed that arrhythmias and group A behavior were observed mainly from stimulation of the anterior hypothalamus, whereas stimulation of other areas of the hypothalamus, including the lateral and the posterolateral hypothalamus, produced group B behavior and no arrhythmias.

Reasons for failed ablation for idiopathic right ventricular outflow tract-like ventricular arrhythmias.

PubMed

Yokokawa, Miki; Good, Eric; Crawford, Thomas; Chugh, Aman; Pelosi, Frank; Latchamsetty, Rakesh; Jongnarangsin, Krit; Ghanbari, Hamid; Oral, Hakan; Morady, Fred; Bogun, Frank

2013-08-01

The right ventricular outflow tract (RVOT) is the most common site of origin of ventricular arrhythmias (VAs) in patients with idiopathic VAs. A left bundle branch block, inferior axis morphology arrhythmia is the hallmark of RVOT arrhythmias. VAs from other sites of origin can mimic RVOT VAs, and ablation in the RVOT typically fails for these VAs. To analyze reasons for failed ablations of RVOT-like VAs. Among a consecutive series of 197 patients with an RVOT-like electrocardiographic (ECG) morphology who were referred for ablation, 38 patients (13 men; age 46 ± 14 years; left ventricular ejection fraction 47% ± 14%) in whom a prior procedure failed within the RVOT underwent a second ablation procedure. ECG characteristics of the VA were compared to a consecutive series of 50 patients with RVOT VAs. The origin of the VA was identified in 95% of the patients. In 28 of 38 (74%) patients, the arrhythmia origin was not in the RVOT. The VA originated from intramural sites (n = 8, 21%), the pulmonary arteries (n = 7, 18%), the aortic cusps (n = 6, 16%), and the epicardium (n = 5, 13%). The origin was within the RVOT in 10 (26%) patients. In 2 (5%) patients, the origin could not be identified despite biventricular, aortic, and epicardial mapping. The VA was eliminated in 34 of 38 (89%) patients with repeat procedures. The ECG features of patients with failed RVOT-like arrhythmias were different from the characteristics of RVOT arrhythmias. In patients in whom ablation of a VA with an RVOT-like appearance fails, mapping of the pulmonary artery, the aortic cusps, the epicardium, the left ventricular outflow tract, and the aortic cusps will help identify the correct site of origin. The 12-lead ECG is helpful in differentiating these VAs from RVOT VAs. Copyright © 2013 Heart Rhythm Society. All rights reserved.

Electrocardiogram changes and atrial arrhythmias in individuals carrying sodium channel SCN5A D1275N mutation.

PubMed

Vanninen, Sari U M; Nikus, Kjell; Aalto-Setälä, Katriina

2017-09-01

The cardiac sodium channel SCN5A regulates atrioventricular and ventricular depolarization as well as cardiac conduction. Patients with cardiac electrical abnormalities have an increased risk of sudden cardiac death (SCD) and cardio-embolic stroke. Optimal management of cardiac disease includes the understanding of association between the causative mutations and the clinical phenotype. A 12-lead electrocardiogram (ECG) is an easy and inexpensive tool for finding risk patients. A blood sample for DNA extraction was obtained in a Finnish family with 43 members; systematic 12-lead ECG analysis was performed in 13 of the family members carrying an SCN5A D1275N mutation. Conduction defects and supraventricular arrhythmias, including atrial fibrillation/flutter, atrioventricular nodal re-entry tachycardia (AVNRT) and junctional rhythm were searched for. Five (38%) mutation carriers had fascicular or bundle branch block, 10 had atrial arrhythmias; no ventricular arrhythmias were found. Notching of the R- and S waves - including initial QRS fragmentation - and prolonged S-wave upstroke were present in all the affected family members. Notably, four (31%) affected family members had a stroke before the age of 31 and two experienced premature death. A 12-lead ECG can be used to predict arrhythmias in SCN5A D1275N mutation carriers. Key messages The 12-lead ECG may reveal cardiac abnormalities even before clinical symptoms occur. Specific ECG findings - initial QRS fragmentation, prolonged S-wave upstroke as well as supraventricular arrhythmias - were frequently encountered in all SCN5A D1257N mutation carriers. ECG follow-up is recommended for all SCN5A D1275N mutation carriers.

Remote Arrhythmia Monitoring System Developed

NASA Technical Reports Server (NTRS)

York, David W.; Mackin, Michael A.; Liszka, Kathy J.; Lichter, Michael J.

2004-01-01

Telemedicine is taking a step forward with the efforts of team members from the NASA Glenn Research Center, the MetroHealth campus of Case Western University, and the University of Akron. The Arrhythmia Monitoring System is a completed, working test bed developed at Glenn that collects real-time electrocardiogram (ECG) signals from a mobile or homebound patient, combines these signals with global positioning system (GPS) location data, and transmits them to a remote station for display and monitoring. Approximately 300,000 Americans die every year from sudden heart attacks, which are arrhythmia cases. However, not all patients identified at risk for arrhythmias can be monitored continuously because of technological and economical limitations. Such patients, who are at moderate risk of arrhythmias, would benefit from technology that would permit long-term continuous monitoring of electrical cardiac rhythms outside the hospital environment. Embedded Web Technology developed at Glenn to remotely command and collect data from embedded systems using Web technology is the catalyst for this new telemetry system (ref. 1). In the end-to-end system architecture, ECG signals are collected from a patient using an event recorder and are transmitted to a handheld personal digital assistant (PDA) using Bluetooth, a short-range wireless technology. The PDA concurrently tracks the patient's location via a connection to a GPS receiver. A long distance link is established via a standard Internet connection over a 2.5-generation Global System for Mobile Communications/General Packet Radio Service (GSM/GPRS)1 cellular, wireless infrastructure. Then, the digital signal is transmitted to a call center for monitoring by medical professionals.

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.

[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.

Research and development of the device for diagnostics of arrhythmia

NASA Astrophysics Data System (ADS)

Lezhnina, I. A.; Boyakhchyan, A. A.; Overchuk, K. V.; Uvarov, A. A.

2017-08-01

The article describes the results of the research for sensors optimal arrangement during one limb ECG detection. The found placement provides the registration of the enough quality signal sufficient for the diagnosis of arrhythmia, the QRS complex is clearly recognized. Authors also show the test results of the device developed for the diagnosis of arrhythmia and sudden cardiac death.

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

PubMed

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

1985-01-01

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

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.

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.

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.

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.

Multiclass Classification of Cardiac Arrhythmia Using Improved Feature Selection and SVM Invariants.

PubMed

Mustaqeem, Anam; Anwar, Syed Muhammad; Majid, Muahammad

2018-01-01

Arrhythmia is considered a life-threatening disease causing serious health issues in patients, when left untreated. An early diagnosis of arrhythmias would be helpful in saving lives. This study is conducted to classify patients into one of the sixteen subclasses, among which one class represents absence of disease and the other fifteen classes represent electrocardiogram records of various subtypes of arrhythmias. The research is carried out on the dataset taken from the University of California at Irvine Machine Learning Data Repository. The dataset contains a large volume of feature dimensions which are reduced using wrapper based feature selection technique. For multiclass classification, support vector machine (SVM) based approaches including one-against-one (OAO), one-against-all (OAA), and error-correction code (ECC) are employed to detect the presence and absence of arrhythmias. The SVM method results are compared with other standard machine learning classifiers using varying parameters and the performance of the classifiers is evaluated using accuracy, kappa statistics, and root mean square error. The results show that OAO method of SVM outperforms all other classifiers by achieving an accuracy rate of 81.11% when used with 80/20 data split and 92.07% using 90/10 data split option.

Pit-a-Pat: A Smart Electrocardiogram System for Detecting Arrhythmia.

PubMed

Park, Juyoung; Lee, Kuyeon; Kang, Kyungtae

2015-10-01

Electrocardiogram (ECG) telemonitoring is one of the most promising applications of medical telemetry. However, previous approaches to ECG telemonitoring have largely relied on public databases of ECG results. In this article we propose a smart ECG system called Pit-a-Pat, which extracts features from ECG signals and detects arrhythmia. It is designed to run on an Android™ (Google, Mountain View, CA) device, without requiring modifications to other software. We implemented the Pit-a-Pat system using a commercial ECG device, and the experimental results demonstrate the effectiveness and accuracy of Pit-a-Pat for monitoring the ECG signal and analyzing the cardiac activity of a mobile patient. The proposed system allows monitoring of cardiac activity with automatic analysis, thereby providing a convenient, inexpensive, and ubiquitous adjunct to personal healthcare.

Neural network and wavelet average framing percentage energy for atrial fibrillation classification.

PubMed

Daqrouq, K; Alkhateeb, A; Ajour, M N; Morfeq, A

2014-03-01

ECG signals are an important source of information in the diagnosis of atrial conduction pathology. Nevertheless, diagnosis by visual inspection is a difficult task. This work introduces a novel wavelet feature extraction method for atrial fibrillation derived from the average framing percentage energy (AFE) of terminal wavelet packet transform (WPT) sub signals. Probabilistic neural network (PNN) is used for classification. The presented method is shown to be a potentially effective discriminator in an automated diagnostic process. The ECG signals taken from the MIT-BIH database are used to classify different arrhythmias together with normal ECG. Several published methods were investigated for comparison. The best recognition rate selection was obtained for AFE. The classification performance achieved accuracy 97.92%. It was also suggested to analyze the presented system in an additive white Gaussian noise (AWGN) environment; 55.14% for 0dB and 92.53% for 5dB. It was concluded that the proposed approach of automating classification is worth pursuing with larger samples to validate and extend the present study. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Simulation of Cardiac Arrhythmias Using a 2D Heterogeneous Whole Heart Model

PubMed Central

Balakrishnan, Minimol; Chakravarthy, V. Srinivasa; Guhathakurta, Soma

2015-01-01

Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) gives an understanding of how the underlying cell and tissue level changes manifest as rhythm disturbances in the ECG. We present a 2D whole heart model (WHM2D) which can accommodate variations at the cellular level and can generate the ECG waveform. It is shown that, by varying cellular-level parameters like the gap junction conductance (GJC), excitability, action potential duration (APD) and frequency of oscillations of the auto-rhythmic cell in WHM2D a large variety of cardiac arrhythmias can be generated including sinus tachycardia, sinus bradycardia, sinus arrhythmia, sinus pause, junctional rhythm, Wolf Parkinson White syndrome and all types of AV conduction blocks. WHM2D includes key components of the electrical conduction system of the heart like the SA (Sino atrial) node cells, fast conducting intranodal pathways, slow conducting atriovenctricular (AV) node, bundle of His cells, Purkinje network, atrial, and ventricular myocardial cells. SA nodal cells, AV nodal cells, bundle of His cells, and Purkinje cells are represented by the Fitzhugh-Nagumo (FN) model which is a reduced model of the Hodgkin-Huxley neuron model. The atrial and ventricular myocardial cells are modeled by the Aliev-Panfilov (AP) two-variable model proposed for cardiac excitation. WHM2D can prove to be a valuable clinical tool for understanding cardiac arrhythmias. PMID:26733873

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.

Use of the Surface Electrocardiogram to Define the Nature of Challenging Arrhythmias.

PubMed

Singh, David K; Peter, C Thomas

2016-03-01

Despite unprecedented advances in technology, the electrocardiogram (ECG) remains essential to the practice of modern electrophysiology. Since its emergence at the turn of the nineteenth century, the form of the ECG has changed little. What has changed is our ability to understand the complex mechanisms that underlie various arrhythmias. In this article, the authors review several important principles of ECG interpretation by providing illustrative tracings. The authors also highlight several important concepts that be can used in ECG analysis. There are several fundamental principles that should be considered in ECG interpretation. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

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).

A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

PubMed

Yildirim, Özal

2018-05-01

Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was proposed for classifying electrocardiogram (ECG) signals. For this purpose, a new wavelet-based layer is implemented to generate ECG signal sequences. The ECG signals were decomposed into frequency sub-bands at different scales in this layer. These sub-bands are used as sequences for the input of LSTM networks. New network models that include unidirectional (ULSTM) and bidirectional (BLSTM) structures are designed for performance comparisons. Experimental studies have been performed for five different types of heartbeats obtained from the MIT-BIH arrhythmia database. These five types are Normal Sinus Rhythm (NSR), Ventricular Premature Contraction (VPC), Paced Beat (PB), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB). The results show that the DBLSTM-WS model gives a high recognition performance of 99.39%. It has been observed that the wavelet-based layer proposed in the study significantly improves the recognition performance of conventional networks. This proposed network structure is an important approach that can be applied to similar signal processing problems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Resting ECG findings in elite football players.

PubMed

Bohm, Philipp; Ditzel, Roman; Ditzel, Heribert; Urhausen, Axel; Meyer, Tim

2013-01-01

The purpose of the study was to evaluate ECG abnormalities in a large sample of elite football players. Data from 566 elite male football players (57 of them of African origin) above 16 years of age were screened retrospectively (age: 20.9 ± 5.3 years; BMI: 22.9 ± 1.7 kg · m(-2), training history: 13.8 ± 4.7 years). The resting ECGs were analysed and classified according to the most current ECG categorisation of the European Society of Cardiology (ESC) (2010) and a classification of Pelliccia et al. (2000) in order to assess the impact of the new ESC-approach. According to the classification of Pelliccia, 52.5% showed mildly abnormal ECG patterns and 12% were classified as distinctly abnormal ECG patterns. According to the classification of the ESC, 33.7% showed 'uncommon ECG patterns'. Short-QT interval was the most frequent ECG pattern in this group (41.9%), followed by a shortened PR-interval (19.9%). When assessed with a QTc cut-off-point of 340 ms (instead of 360 ms), only 22.2% would have had 'uncommon ECG patterns'. Resting ECG changes amongst elite football players are common. Adjustment of the ESC criteria by adapting proposed time limits for the ECG (e.g. QTc, PR) should further reduce the rate of false-positive results.

Ubiquitous health monitoring and real-time cardiac arrhythmias detection: a case study.

PubMed

Li, Jian; Zhou, Haiying; Zuo, Decheng; Hou, Kun-Mean; De Vaulx, Christophe

2014-01-01

As the symptoms and signs of heart diseases that cause sudden cardiac death, cardiac arrhythmia has attracted great attention. Due to limitations in time and space, traditional approaches to cardiac arrhythmias detection fail to provide a real-time continuous monitoring and testing service applicable in different environmental conditions. Integrated with the latest technologies in ECG (electrocardiograph) analysis and medical care, the pervasive computing technology makes possible the ubiquitous cardiac care services, and thus brings about new technical challenges, especially in the formation of cardiac care architecture and realization of the real-time automatic ECG detection algorithm dedicated to care devices. In this paper, a ubiquitous cardiac care prototype system is presented with its architecture framework well elaborated. This prototype system has been tested and evaluated in all the clinical-/home-/outdoor-care modes with a satisfactory performance in providing real-time continuous cardiac arrhythmias monitoring service unlimitedly adaptable in time and space.

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.

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

PubMed

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

2015-01-01

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

Comparison of two teaching methods for cardiac arrhythmia interpretation among nursing students.

PubMed

Varvaroussis, Dimitrios P; Kalafati, Maria; Pliatsika, Paraskevi; Castrén, Maaret; Lott, Carsten; Xanthos, Theodoros

2014-02-01

The aim of this study was to compare the six-stage method (SSM) for instructing primary cardiac arrhythmias interpretation to students without basic electrocardiogram (ECG) knowledge with a descriptive teaching method in a single educational intervention. This is a randomized trial. Following a brief instructional session, undergraduate nursing students, assigned to group A (SSM) and group B (descriptive teaching method), undertook a written test in cardiac rhythm recognition, immediately after the educational intervention (initial exam). Participants were also examined with an unannounced retention test (final exam), one month after instruction. Altogether 134 students completed the study. Interpretation accuracy for each cardiac arrhythmia was assessed. Mean score at the initial exam was 8.71±1.285 for group A and 8.74±1.303 for group B. Mean score at the final exam was 8.25±1.46 for group A vs 7.84±1.44 for group B. Overall results showed that the SSM was equally effective with the descriptive teaching method. The study showed that in each group bradyarrhythmias were identified correctly by more students than tachyarrhythmias. No significant difference between the two teaching methods was seen for any specific cardiac arrhythmia. The SSM effectively develops staff competency for interpreting common cardiac arrhythmias in students without ECG knowledge. More research is needed to support this conclusion and the method's effectiveness must be evaluated if being implemented to trainee groups with preexisting basic ECG interpretation knowledge. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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.

Electrocardiogram interpretation and arrhythmia management: a primary and secondary care survey.

PubMed

Begg, Gordon; Willan, Kathryn; Tyndall, Keith; Pepper, Chris; Tayebjee, Muzahir

2016-05-01

There is increasing desire among service commissioners to treat arrhythmia in primary care. Accurate interpretation of the electrocardiogram (ECG) is fundamental to this. ECG interpretation has previously been shown to vary widely but there is little recent data. To examine the interpretation of ECGs in primary and secondary care. A cross-sectional survey of participants' interpretation of six ECGs and hypothetical management of patients based on those ECGs, at primary care educational events, and a cardiology department in Leeds. A total of 262 primary care clinicians and 20 cardiology clinicians were surveyed via questionnaire. Answers were compared with expert electrophysiologist opinion. In primary care, abnormal ECGs were interpreted as normal by 23% of responders. ST elevation and prolonged QT were incorrectly interpreted as normal by 1% and 22%, respectively. In cardiology, abnormal ECGs were interpreted as normal by 3%. ECG provision and interpretation remains inconsistent in both primary and secondary care. Primary care practitioners are less experienced and less confident with ECG interpretation than cardiologists, and require support in this area. © British Journal of General Practice 2016.

Electrocardiographic left ventricular hypertrophy predicts recurrence of atrial arrhythmias after catheter ablation of paroxysmal atrial fibrillation.

PubMed

Li, Song-Nan; Wang, Lu; Dong, Jian-Zeng; Yu, Rong-Hui; Long, De-Yong; Tang, Ri-Bo; Sang, Cai-Hua; Jiang, Chen-Xi; Liu, Nian; Bai, Rong; Du, Xin; Ma, Chang-Sheng

2018-06-01

Left ventricular hypertrophy (LVH) is an independent predictor of new-onset atrial fibrillation. Whether LVH can predict the recurrence of arrhythmia after radiofrequency catheter ablation (RFCA) in patients with paroxysmal atrial fibrillation (PAF) remains unclear. PAF patients with baseline-electrocardiographic LVH has a higher recurrence rate after RFCA procedure compared with those without LVH. A total of 436 patients with PAF undergoing first RFCA were consecutively enrolled and clustered into 2 groups based on electrocardiogram (ECG) findings: non-ECG LVH (218 patients) and ECG LVH (218 patients). LVH was characterized by the Romhilt-Estes point score system; the score ≥5points were defined as LVH. At 42 months' (interquartile range, 18.0-60.0 months) follow-up after RFCA, 151 (69.3%) patients in the non-ECG LVH group and 108 (49.5%) patients in the ECG LVH group maintained sinus rhythm without using antiarrhythmic drugs (P < 0.001). Patients with ECG LVH tended to experience a much higher prevalence of stroke and recurrence of atrial arrhythmia episodes compared with those without ECG LVH (log-rank P < 0.001). Multivariate analysis found the presence of ECG LVH and left atrial diameter to be independent risk factors for recurrence after adjusting for confounding factors. The presence of ECG LVH was a strong and independent predictor of recurrence in patients with PAF following RFCA. © 2018 Wiley Periodicals, Inc.

Simulation system of arrhythmia using ActiveX control.

PubMed

Takeuchi, Akihiro; Hirose, Minoru; Hamada, Atsushi; Ikeda, Noriaki

2005-07-01

A simulation system for arrhythmias has been developed using Windows-based software technology, ActiveX control. The cardiac module consists of six cells, the sinus, atrium, AV node, ventricle, and ectopic foci. The physiological properties of the cells, the automaticity and conduction delay, were modelled, respectively, by the phase response curve and the excitability recovery curve. Cell functions were implemented in the ActiveX control and incorporated into the cardiac module. The system draws the ECG sequence as a ladder diagram in real time. The system interactively shows diverse arrhythmias for various user settings of the cell function and bidirectional conduction between the cells. Users are able to experiment virtually by setting up a so-called electrophysiological stimulation. This system is useful for learning and for teaching the interaction between the cells and arrhythmias.

An Energy Efficient ECG Signal Processor Detecting Cardiovascular Diseases on Smartphone.

PubMed

Jain, Sanjeev Kumar; Bhaumik, Basabi

2017-04-01

A novel disease diagnostic algorithm for ECG signal processing based on forward search is implemented in Application Specific Integrated Circuit (ASIC) for cardiovascular disease diagnosis on smartphone. An ASIC is fabricated using 130-nm CMOS low leakage process technology. The area of our PQRST ASIC is 1.21 mm 2 . The energy dissipation of PQRST ASIC is 96 pJ with a supply voltage of 0.9 V. The outputs from the ASIC are fed to an Android application that generates diagnostic report and can be sent to a cardiologist via email. The ASIC and Android application are verified for the detection of bundle branch block, hypertrophy, arrhythmia and myocardial infarction using Physionet PTB diagnostic ECG database. The failed detection rate is 0.69%, 0.69%, 0.34% and 1.72% for bundle branch block, hypertrophy, arrhythmia and myocardial infarction respectively. The AV block is detected in all the three patients in the Physionet St. Petersburg arrhythmia database. Our proposed ASIC together with our Android application is the most suitable for an energy efficient wearable cardiovascular disease detection system.

Patient characteristics associated with false arrhythmia alarms in intensive care

PubMed Central

Harris, Patricia R; Zègre-Hemsey, Jessica K; Schindler, Daniel; Bai, Yong; Pelter, Michele M; Hu, Xiao

2017-01-01

characteristics were compared in relation to 1) the number and 2) the duration of false arrhythmia alarms per 24-hour period, using nonparametric statistics to minimize the influence of outliers. Among the significant associations were the following: age ≥60 years (P=0.013; P=0.034), confused mental status (P<0.001 for both comparisons), cardiovascular diagnoses (P<0.001 for both comparisons), electrocardiographic (ECG) features, such as wide ECG waveforms that correspond to ventricular depolarization known as QRS complex due to bundle branch block (BBB) (P=0.003; P=0.004) or ventricular paced rhythm (P=0.002 for both comparisons), respiratory diagnoses (P=0.004 for both comparisons), and support with mechanical ventilation, including those with primary diagnoses other than respiratory ones (P<0.001 for both comparisons). Conclusion Patients likely to trigger a higher number of false arrhythmia alarms may be those with older age, confusion, cardiovascular diagnoses, and ECG features that indicate BBB or ventricular pacing, respiratory diagnoses, and mechanical ventilatory support. Algorithm improvements could focus on better noise reduction (eg, motion artifact with confused state) and distinguishing BBB and paced rhythms from ventricular arrhythmias. Increasing awareness of patient conditions that apparently trigger a higher rate of false arrhythmia alarms may be useful for reducing unnecessary noise and improving alarm management. PMID:28458554

Patient characteristics associated with false arrhythmia alarms in intensive care.

PubMed

Harris, Patricia R; Zègre-Hemsey, Jessica K; Schindler, Daniel; Bai, Yong; Pelter, Michele M; Hu, Xiao

2017-01-01

number and 2) the duration of false arrhythmia alarms per 24-hour period, using nonparametric statistics to minimize the influence of outliers. Among the significant associations were the following: age ≥60 years ( P =0.013; P =0.034), confused mental status ( P <0.001 for both comparisons), cardiovascular diagnoses ( P <0.001 for both comparisons), electrocardiographic (ECG) features, such as wide ECG waveforms that correspond to ventricular depolarization known as QRS complex due to bundle branch block (BBB) ( P =0.003; P =0.004) or ventricular paced rhythm ( P =0.002 for both comparisons), respiratory diagnoses ( P =0.004 for both comparisons), and support with mechanical ventilation, including those with primary diagnoses other than respiratory ones ( P <0.001 for both comparisons). Patients likely to trigger a higher number of false arrhythmia alarms may be those with older age, confusion, cardiovascular diagnoses, and ECG features that indicate BBB or ventricular pacing, respiratory diagnoses, and mechanical ventilatory support. Algorithm improvements could focus on better noise reduction (eg, motion artifact with confused state) and distinguishing BBB and paced rhythms from ventricular arrhythmias. Increasing awareness of patient conditions that apparently trigger a higher rate of false arrhythmia alarms may be useful for reducing unnecessary noise and improving alarm management.

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 QRS Detection and R Point Recognition Method for Wearable Single-Lead ECG Devices.

PubMed

Chen, Chieh-Li; Chuang, Chun-Te

2017-08-26

In the new-generation wearable Electrocardiogram (ECG) system, signal processing with low power consumption is required to transmit data when detecting dangerous rhythms and to record signals when detecting abnormal rhythms. The QRS complex is a combination of three of the graphic deflection seen on a typical ECG. This study proposes a real-time QRS detection and R point recognition method with low computational complexity while maintaining a high accuracy. The enhancement of QRS segments and restraining of P and T waves are carried out by the proposed ECG signal transformation, which also leads to the elimination of baseline wandering. In this study, the QRS fiducial point is determined based on the detected crests and troughs of the transformed signal. Subsequently, the R point can be recognized based on four QRS waveform templates and preliminary heart rhythm classification can be also achieved at the same time. The performance of the proposed approach is demonstrated using the benchmark of the MIT-BIH Arrhythmia Database, where the QRS detected sensitivity (Se) and positive prediction (+P) are 99.82% and 99.81%, respectively. The result reveals the approach's advantage of low computational complexity, as well as the feasibility of the real-time application on a mobile phone and an embedded system.

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

PubMed

Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

2017-07-01

Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

A 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.

ECG during helicopter underwater escape training.

PubMed

Tipton, Michael J; Gibbs, Peter; Brooks, Chris; Roiz de Sa, Dan; Reilly, Tara J

2010-04-01

Coincidental stimulation of the sympathetic and parasympathetic nervous system can cause "autonomic conflict" and consequent cardiac arrhythmias. The present study tested the hypotheses that: 1) cardiac arrhythmias would be seen in those undertaking helicopter underwater escape training (HUET); 2) the occurrence of arrhythmias in individuals could be predicted; and 3) the heart rate response to HUET would habituate with repeated runs. There were 26 male volunteers who each undertook 5 HUET submersions into water at 29.5 degrees C, with each run separated by 10 min. Each submersion included a 3-min, 40-s pre-submersion period, a 10-s submersion, and 40-s post-submersion period. Participants wore a three-lead telemetric ECG system beneath an immersion suit and underclothing. Skin temperature was measured in one participant. Each participant undertook tests to establish their autonomic function, including heart rate variability, face immersion, cold pressor test, and aerobic capacity assessment. The heart rate response to HUET was reduced by the fourth run when compared to the first run. Across all runs, 32 cardiac arrhythmias were identified (25%) in 22 different participants; all but 6 of the arrhythmias occurred just after submersion. Only aerobic fitness appeared inversely associated with the occurrence of arrhythmias. The heart rate response to HUET habituates. HUET produces cardiac arrhythmias; these are asymptomatic and probably of little clinical significance in young, fit individuals. It remains to be seen if this is the case with either an older, less fit cohort of people or in those undertaking longer breath holds in colder water.

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).

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.

A time-frequency approach for the analysis of normal and arrhythmia cardiac signals.

PubMed

Mahmoud, Seedahmed S; Fang, Qiang; Davidović, Dragomir M; Cosic, Irena

2006-01-01

Previously, electrocardiogram (ECG) signals have been analyzed in either a time-indexed or spectral form. The reality, is that the ECG and all other biological signals belong to the family of multicomponent nonstationary signals. Due to this reason, the use of time-frequency analysis can be unavoidable for these signals. The Husimi and Wigner distributions are normally used in quantum mechanics for phase space representations of the wavefunction. In this paper, we introduce the Husimi distribution (HD) to analyze the normal and abnormal ECG signals in time-frequency domain. The abnormal cardiac signal was taken from a patient with supraventricular arrhythmia. Simulation results show that the HD has a good performance in the analysis of the ECG signals comparing with the Wigner-Ville distribution (WVD).

Facilitating arrhythmia simulation: the method of quantitative cellular automata modeling and parallel running

PubMed Central

Zhu, Hao; Sun, Yan; Rajagopal, Gunaretnam; Mondry, Adrian; Dhar, Pawan

2004-01-01

Background Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. Methods We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. Results We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. Conclusions Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described. PMID:15339335

Computers and clinical arrhythmias.

PubMed

Knoebel, S B; Lovelace, D E

1983-02-01

Cardiac arrhythmias are ubiquitous in normal and abnormal hearts. These disorders may be life-threatening or benign, symptomatic or unrecognized. Arrhythmias may be the precursor of sudden death, a cause or effect of cardiac failure, a clinical reflection of acute or chronic disorders, or a manifestation of extracardiac conditions. Progress is being made toward unraveling the diagnostic and therapeutic problems involved in arrhythmogenesis. Many of the advances would not be possible, however, without the availability of computer technology. To preserve the proper balance and purposeful progression of computer usage, engineers and physicians have been exhorted not to work independently in this field. Both should learn some of the other's trade. The two disciplines need to come together to solve important problems with computers in cardiology. The intent of this article was to acquaint the practicing cardiologist with some of the extant and envisioned computer applications and some of the problems with both. We conclude that computer-based database management systems are necessary for sorting out the clinical factors of relevance for arrhythmogenesis, but computer database management systems are beset with problems that will require sophisticated solutions. The technology for detecting arrhythmias on routine electrocardiograms is quite good but human over-reading is still required, and the rationale for computer application in this setting is questionable. Systems for qualitative, continuous monitoring and review of extended time ECG recordings are adequate with proper noise rejection algorithms and editing capabilities. The systems are limited presently for clinical application to the recognition of ectopic rhythms and significant pauses. Attention should now be turned to the clinical goals for detection and quantification of arrhythmias. We should be asking the following questions: How quantitative do systems need to be? Are computers required for the detection of

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

PubMed

Bote, Jose Manuel; Recas, Joaquin; Rincon, Francisco; Atienza, David; Hermida, Roman

2018-03-01

This work presents a new modular and low-complexity algorithm for the delineation of the different ECG waves (QRS, P and T peaks, onsets, and end). Involving a reduced number of operations per second and having a small memory footprint, this algorithm is intended to perform real-time delineation on resource-constrained embedded systems. The modular design allows the algorithm to automatically adjust the delineation quality in runtime to a wide range of modes and sampling rates, from a ultralow-power mode when no arrhythmia is detected, in which the ECG is sampled at low frequency, to a complete high-accuracy delineation mode, in which the ECG is sampled at high frequency and all the ECG fiducial points are detected, in the case of arrhythmia. The delineation algorithm has been adjusted using the QT database, providing very high sensitivity and positive predictivity, and validated with the MIT database. The errors in the delineation of all the fiducial points are below the tolerances given by the Common Standards for Electrocardiography Committee in the high-accuracy mode, except for the P wave onset, for which the algorithm is above the agreed tolerances by only a fraction of the sample duration. The computational load for the ultralow-power 8-MHz TI MSP430 series microcontroller ranges from 0.2% to 8.5% according to the mode used.

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

PubMed

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

2007-12-01

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

Real-Time Analytics for the Healthcare Industry: Arrhythmia Detection.

PubMed

Agneeswaran, Vijay Srinivas; Mukherjee, Joydeb; Gupta, Ashutosh; Tonpay, Pranay; Tiwari, Jayati; Agarwal, Nitin

2013-09-01

It is time for the healthcare industry to move from the era of "analyzing our health history" to the age of "managing the future of our health." In this article, we illustrate the importance of real-time analytics across the healthcare industry by providing a generic mechanism to reengineer traditional analytics expressed in the R programming language into Storm-based real-time analytics code. This is a powerful abstraction, since most data scientists use R to write the analytics and are not clear on how to make the data work in real-time and on high-velocity data. Our paper focuses on the applications necessary to a healthcare analytics scenario, specifically focusing on the importance of electrocardiogram (ECG) monitoring. A physician can use our framework to compare ECG reports by categorization and consequently detect Arrhythmia. The framework can read the ECG signals and uses a machine learning-based categorizer that runs within a Storm environment to compare different ECG signals. The paper also presents some performance studies of the framework to illustrate the throughput and accuracy trade-off in real-time analytics.

[Silent myocardial ischemia and exercise-induced arrhythmia detected by the exercise test in the total health promotion plan (THP)].

PubMed

Iwane, M; Shibe, Y; Itoh, K; Kinoshita, F; Kanagawa, Y; Kobayashi, M; Mugitani, K; Ohta, M; Ohata, H; Yoshikawa, A; Ikuta, Z; Nakamura, Y; Mohara, O

2001-03-01

We investigated the prevalence and characteristics of ischemic heart disease especially silent myocardial ischemia (SMI) and arrhythmia in need of careful observation in the exercise stress tests in the Total Health Promotion Plan (THP), which was conducted between 1994-96 for the purpose of measuring cardiopulmonary function. All workers (n = 4,918, 4,426 males) aged 18-60 yr old in an occupational field were studied. Exercise tests with an ergometer were performed by the LOPS protocol, in which the maximal workload was set up as a presumed 70-80% maximal oxygen intake, or STEP (original multistage protocol). ECG changes were evaluated with a CC5 lead. Two hundred and fifteen people refused the study because of a common cold, lumbago and so on. Of 4,703 subjects, 17 with abnormal rest ECG and 19 with probable anginal pain were excluded from the exercise tests. Of 4,667 who underwent the exercise test, 37 (0.79%) had ischemic ECG change, and 155 (3.32%) had striking arrhythmia. These 228 subjects then did a treadmill exercise test with Bruce protocol. Twenty-two (0.47% of 4,703) showed positive ECG change, 9 (0.19%) of 22 had abnormal findings on a 201Tl scan. 8 (0.17%) were diagnosed as SMI (Cohn I), in which the prevalence of hypertension, hyperlipidemia, diabetes mellitus, smoker and positive familial history of ischemic heart disease was greater than that of all subjects. In a 15-30 month follow up, none has developed cardiac accidents. Exercise-induced arrhythmia was detected in 11 (0.23%) subjects. Four were non-sustained ventricular tachycardia without any organic disease, 4 were ventricular arrhythmia based on cardiomyopathy detected by echocardiography, 2 were atrial fibrillation and another was WPW syndrome. It is therefore likely that the ergometer exercise test in THP was effective in preventing sudden death caused by ischemic heart disease or striking arrhythmia.

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.

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

Low-complexity R-peak detection in ECG signals: a preliminary step towards ambulatory fetal monitoring.

PubMed

Rooijakkers, Michiel; Rabotti, Chiara; Bennebroek, Martijn; van Meerbergen, Jef; Mischi, Massimo

2011-01-01

Non-invasive fetal health monitoring during pregnancy has become increasingly important. Recent advances in signal processing technology have enabled fetal monitoring during pregnancy, using abdominal ECG recordings. Ubiquitous ambulatory monitoring for continuous fetal health measurement is however still unfeasible due to the computational complexity of noise robust solutions. In this paper an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, while increasing the R-peak detection quality compared to existing R-peak detection schemes. Validation of the algorithm is performed on two manually annotated datasets, the MIT/BIH Arrhythmia database and an in-house abdominal database. Both R-peak detection quality and computational complexity are compared to state-of-the-art algorithms as described in the literature. With a detection error rate of 0.22% and 0.12% on the MIT/BIH Arrhythmia and in-house databases, respectively, the quality of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

[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.

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

PubMed

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

2014-07-01

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

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

PubMed Central

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

2014-01-01

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

[Idiopathic ventricular arrhythmia in children. Apropos of 24 cases].

PubMed

Coeurderoy, A; Almange, C; Laurent, M; Biron, Y; Leborgne, P

1985-12-01

The severity and prognosis of idiopathic ventricular arrhythmias in childhood were studied in 24 patients (12 boys, 12 girls) with an average age of 8 years at the time of diagnosis of the arrhythmia. Investigations included clinical assessment and analysis of basal ECG (morphology of the arrhythmias) and dynamic recordings (Holter and exercise stress testing). The clinical course was followed for an average of 3.8 years. The patients were classified in two groups: monomorphic arrhythmias (Group I) and polymorphic arrhythmias (Group II). Group I was divided into 4 subgroups: isolated ventricular extrasystoles (IA), 11 patients; ventricular extrasystoles with bursts of ventricular tachycardia (IB), 6 patients; sustained ventricular tachycardia without intercritical extrasystoles (IC), 1 patient; accelerated idioventricular rhythm (ID), 2 patients. Subgroups IA, IB and ID were characterised by the absence of symptoms, the disappearance of the arrhythmia on exercise, the decreased efficacy of antiarrhythmic drugs and an excellent prognosis. Therapeutic abstention was the rule in these patients. Patients in Group IC were characterised by the variability of their symptoms, the absence of exercise induced arrhythmias, the need for treatment in most cases and a good long-term prognosis. Group II was divided into 2 subgroups: adrenergic polymorphic ventricular tachycardia (IIA), 2 patients, and non-adrenergic polymorphic ventricular tachycardia (IIB), 2 patients. Patients in Subgroup IIA were characterised by syncope on exercise or emotion, the need for betablocker therapy which considerably improved the patients symptoms but which did not usually prevent sudden death.(ABSTRACT TRUNCATED AT 250 WORDS)

The Role of NT-proBNP in the Diagnosis of Ventricular Arrhythmias in Patients with Systemic Sclerosis

PubMed Central

MURESAN, Lucian; PETCU, Ana; MURESAN, Crina; RINZIS, Mirela; GUSETU, Gabriel; POP, Dana; ZDRENGHEA, Dumitru; REDNIC, Simona

2017-01-01

Background: In patients with systemic sclerosis, NT-proBNP is a useful diagnostic marker for pulmonary hypertension and ventricular dysfunction, with important prognostic significance. The aim of this study was to assess the relationship between the NT-proBNP levels and the presence and severity of ventricular arrhythmias in patients with scleroderma. Methods: Forty consecutive patients with a diagnostic of systemic sclerosis according to the EULAR criteria admitted at the Rheumatology Clinic of Cluj-Napoca, Romania, from Jan 2014 to Apr 2014 were enrolled. Patients underwent a 12-lead ECG and a 24-hour Holter ECG monitoring for ventricular arrhythmias evaluation. Blood sample testing (including NT-proBNP level measurements), echocardiography, spirometry, chest X-ray and, when considered appropriate, high-resolution chest CT were performed. Results: Sixty percent of patients (n=24) had abnormal NT-proBNP serum levels (>125 pg/ml) and 10 patients had >100 PVC/24 h. There was a statistically significant correlation between the NT-proBNP levels and the total number of premature ventricular contractions (PVC) (r=0.445, P=0.006), total number of isolated PVC (r=0,493, P=0.002), total number of ventricular couplets (r=0.379, P=0.021) and the number of PVC morphologies (r=0.501, P=0.002). The presence of an NT-proBNP serum level >287 pg/ml had a sensitivity of 55% and a specificity of 93% in predicting the presence of complex ventricular arrhythmias on 24-hour Holter ECG monitoring. Conclusion: NT-proBNP levels could become a useful ventricular arrhythmia marker for assessing the arrhythmic risk in patients with systemic sclerosis. PMID:28845401

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.

Arrhythmia Secondary to Cold Water Submersion during Helicopter Underwater Escape Training.

PubMed

Kaur, Paven P; Drummond, Sarah E; Furyk, Jeremy

2016-02-01

A 32-year-old, fit and healthy, Caucasian male presented with a less than 24-hour history of palpitations with the onset following participation in helicopter underwater escape training (HUET). He reported no chest pain, shortness of breath, syncope, or pre-syncope symptoms. On examination, an irregularly irregular pulse was noted at a rate of 120 beats per minute with a blood pressure of 132/84. There was no evidence of congestive cardiac failure. The electrocardiogram (ECG) demonstrated atrial fibrillation at 97 beats per minute with a normal axis, normal QRS complexes, and a QTc of 399 ms. Bloods were all within normal limits and a chest x-ray showed no abnormality. The patient was loaded with amiodarone and reverted to sinus rhythm with a normal post-reversion ECG. Five years on, following further HUET, the patient presented with an identical presentation. His ECG showed fast atrial fibrillation at a rate of 115 beats per minute. On this occasion, he was sedated and Direct Current cardioverted with reversal to sinus rhythm after one shock. It was felt that the precipitating factor for this patient's atrial fibrillation, in both cases, was HUET. The case discussed describes a previously fit and well subject who developed a sustained arrhythmia secondary to cold water submersion. Evidence suggests water submersion can provoke cardiac arrhythmias via the suggested theory of "autonomic conflict." It has been proposed that a number of unexplained deaths related to water submersion may be secondary to arrhythmogenic syncope.

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.

Cardiac arrhythmia mechanisms in rats with heart failure induced by pulmonary hypertension

PubMed Central

Benoist, David; Stones, Rachel; Drinkhill, Mark J.; Benson, Alan P.; Yang, Zhaokang; Cassan, Cecile; Gilbert, Stephen H.; Saint, David A.; Cazorla, Olivier; Steele, Derek S.; Bernus, Olivier

2012-01-01

Pulmonary hypertension provokes right heart failure and arrhythmias. Better understanding of the mechanisms underlying these arrhythmias is needed to facilitate new therapeutic approaches for the hypertensive, failing right ventricle (RV). The aim of our study was to identify the mechanisms generating arrhythmias in a model of RV failure induced by pulmonary hypertension. Rats were injected with monocrotaline to induce either RV hypertrophy or failure or with saline (control). ECGs were measured in conscious, unrestrained animals by telemetry. In isolated hearts, electrical activity was measured by optical mapping and myofiber orientation by diffusion tensor-MRI. Sarcoplasmic reticular Ca2+ handling was studied in single myocytes. Compared with control animals, the T-wave of the ECG was prolonged and in three of seven heart failure animals, prominent T-wave alternans occurred. Discordant action potential (AP) alternans occurred in isolated failing hearts and Ca2+ transient alternans in failing myocytes. In failing hearts, AP duration and dispersion were increased; conduction velocity and AP restitution were steeper. The latter was intrinsic to failing single myocytes. Failing hearts had greater fiber angle disarray; this correlated with AP duration. Failing myocytes had reduced sarco(endo)plasmic reticular Ca2+-ATPase activity, increased sarcoplasmic reticular Ca2+-release fraction, and increased Ca2+ spark leak. In hypertrophied hearts and myocytes, dysfunctional adaptation had begun, but alternans did not develop. We conclude that increased electrical and structural heterogeneity and dysfunctional sarcoplasmic reticular Ca2+ handling increased the probability of alternans, a proarrhythmic predictor of sudden cardiac death. These mechanisms are potential therapeutic targets for the correction of arrhythmias in hypertensive, failing RVs. PMID:22427523

Respiratory sinus arrhythmia in Chagas disease.

PubMed

Neves, Victor Ribeiro; Peltola, Mirja; Huikuri, Heikki; Rocha, Manoel Otávio da Costa; Ribeiro, Antonio Luiz

2014-10-01

We applied the respiratory sinus arrhythmia (RSA) quantification algorithm to 24-hour ECG recordings of Chagas disease (ChD) patients with (G1, n=148) and without left ventricular dysfunction (LVD) (G2, n=33), and in control subjects (G0, n=28). Both ChD groups displayed a reduced RSA index; G1=299 (144-812); G2=335 (162-667), p=0.011, which was correlated with vagal indexes of heart rate variability analysis. RSA index is a marker of vagal modulation in ChD patients. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

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.

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

PubMed

Ze Wang; Chi Man Wong; Feng Wan

2017-07-01

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

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…

Malignant arrhythmia as the first manifestation of Wolff-Parkinson-White syndrome: a case with minimal preexcitation on electrocardiography.

PubMed

Gungor, B; Alper, A T

2013-09-01

Wolff-Parkinson-White (WPW) syndrome is defined as the presence of an accessory atrioventricular pathway which is manifested as delta waves and short PR interval on electrocardiography (ECG). However, some WPW cases do not have typical findings on ECG and may remain undiagnosed unless palpitations occur. Sudden cardiac death may be the first manifestation of WPW and develops mostly secondary to degeneration of atrial fibrillation into ventricular fibrillation. In this report, we present a case of undiagnosed WPW with minimal preexcitation on ECG and who suffered an episode of malignant arrhythmia as the first manifestation of the disease.

[The Key Technology Study on Cloud Computing Platform for ECG Monitoring Based on Regional Internet of Things].

PubMed

Yang, Shu; Qiu, Yuyan; Shi, Bo

2016-09-01

This paper explores the methods of building the internet of things of a regional ECG monitoring, focused on the implementation of ECG monitoring center based on cloud computing platform. It analyzes implementation principles of automatic identifi cation in the types of arrhythmia. It also studies the system architecture and key techniques of cloud computing platform, including server load balancing technology, reliable storage of massive smalfi les and the implications of quick search function.

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.

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.

α-Adrenoceptor blockade modifies neurally induced atrial arrhythmias

PubMed Central

Richer, Louis-Philippe; Vinet, Alain; Kus, Teresa; Cardinal, René; Ardell, Jeffrey L.; Armour, John Andrew

2008-01-01

Our objective was to determine whether neuronally induced atrial arrhythmias can be modified by α-adrenergic receptor blockade. In 30 anesthetized dogs, trains of five electrical stimuli (1 mA; 1 ms) were delivered immediately after the P wave of the ECG to mediastinal nerves associated with the superior vena cava. Regional atrial electrical events were monitored with 191 atrial unipolar electrodes. Mediastinal nerve sites were identified that reproducibly initiated atrial arrhythmias. These sites were then restimulated following 1 h (time control, n = 6), or the intravenous administration of naftopidil (α1-adrenergic blocker: 0.2 mg/kg, n = 6), yohimbine (α2-adrenergic blocker: 1 mg/kg, n = 6) or both (n = 8). A ganglionic blocker (hexamethonium: 1 mg/kg) was tested in four dogs. Stimulation of mediastinal nerves sites consistently elicited atrial tachyarrhythmias. Repeat stimulation after 1 h in the time-control group exerted a 19% decrease of the sites still able to induce atrial tachyarrhythmias. Hexamethonium inactivated 78% of the previously active sites. Combined α-adrenoceptor blockade inactivated 72% of the previously active sites. Bradycardia responses induced by mediastinal nerve stimulation were blunted by hexamethonium, but not by α1,2-adrenergic blockade. Naftopidil or yohimbine alone eliminated atrial arrhythmia induction from 31% and 34% of the sites (similar to time control). We conclude that heterogeneous activation of the intrinsic cardiac nervous system results in atrial arrhythmias that involve intrinsic cardiac neuronal α-adrenoceptors. In contrast to the global suppression exerted by hexamethonium, we conclude that α-adrenoceptor blockade targets intrinsic cardiac local circuit neurons involved in arrhythmia formation and not the flow-through efferent projections of the cardiac nervous system. PMID:18716036

Alpha-adrenoceptor blockade modifies neurally induced atrial arrhythmias.

PubMed

Richer, Louis-Philippe; Vinet, Alain; Kus, Teresa; Cardinal, René; Ardell, Jeffrey L; Armour, John Andrew

2008-10-01

Our objective was to determine whether neuronally induced atrial arrhythmias can be modified by alpha-adrenergic receptor blockade. In 30 anesthetized dogs, trains of five electrical stimuli (1 mA; 1 ms) were delivered immediately after the P wave of the ECG to mediastinal nerves associated with the superior vena cava. Regional atrial electrical events were monitored with 191 atrial unipolar electrodes. Mediastinal nerve sites were identified that reproducibly initiated atrial arrhythmias. These sites were then restimulated following 1 h (time control, n = 6), or the intravenous administration of naftopidil (alpha(1)-adrenergic blocker: 0.2 mg/kg, n = 6), yohimbine (alpha(2)-adrenergic blocker: 1 mg/kg, n = 6) or both (n = 8). A ganglionic blocker (hexamethonium: 1 mg/kg) was tested in four dogs. Stimulation of mediastinal nerves sites consistently elicited atrial tachyarrhythmias. Repeat stimulation after 1 h in the time-control group exerted a 19% decrease of the sites still able to induce atrial tachyarrhythmias. Hexamethonium inactivated 78% of the previously active sites. Combined alpha-adrenoceptor blockade inactivated 72% of the previously active sites. Bradycardia responses induced by mediastinal nerve stimulation were blunted by hexamethonium, but not by alpha(1,2)-adrenergic blockade. Naftopidil or yohimbine alone eliminated atrial arrhythmia induction from 31% and 34% of the sites (similar to time control). We conclude that heterogeneous activation of the intrinsic cardiac nervous system results in atrial arrhythmias that involve intrinsic cardiac neuronal alpha-adrenoceptors. In contrast to the global suppression exerted by hexamethonium, we conclude that alpha-adrenoceptor blockade targets intrinsic cardiac local circuit neurons involved in arrhythmia formation and not the flow-through efferent projections of the cardiac nervous system.

Design and implementation of an electrocardiographical signal acquisition and digital processing system orientated to the detection of paroxysmal arrhythmias

NASA Astrophysics Data System (ADS)

Iriart Braceli, Agustín; Exequiel Morani, Jorge

2011-12-01

This article describes the design, technical aspects and implementation of a device capable of acquiring electrocardiograph signals; visualize them in real time over a graphic liquid crystal display (GLCD), and the storage of these ECG registers on a SD memory card. It also details a noise suppression algorithm using the Wavelet Transform. This system was specially developed to cover some bankruptcy that presents actual Holters or ECG regarding the detection of paroxysmal arrhythmias. The contribution of this work is settled on its portability and low production cost. The filtering method used provides an ECG signal without any significant noise and appropriate to the diagnosis of cardiac pathologies.

ECG authentication in post-exercise situation.

PubMed

Dongsuk Sung; Jeehoon Kim; Myungjun Koh; Kwangsuk Park

2017-07-01

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

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

Mitral valve prolapse and electrolyte abnormality: a dangerous combination for ventricular arrhythmias

PubMed Central

Rajani, Ali Raza; Murugesan, Vagishwari; Baslaib, Fahad Omar; Rafiq, Muhammad Anwer

2014-01-01

A 27-year-old woman with a history of bileaflet mitral valve prolapse and moderate mitral regurgitation presented to our emergency with untractable polymorphic wide complex tachycardia and unstable haemodynamics. After cardiopulmonary resuscitation, return of spontaneous circulation was achieved 30 min later. Her post-resuscitation ECG showed a prolonged QT interval which progressively normalised over the same day. Her laboratory investigations revealed hypocalcaemia while other electrolytes were within normal limits. A diagnosis of ventricular arrhythmia secondary to structural heart disease further precipitated by hypocalcaemia was made. Further hospital stay did not reveal a recurrence of prolonged QT interval or other arrhythmias except for an episode of non-sustained ventricular tachycardia. However, the patient suffered diffuse hypoxic brain encephalopathy secondary to prolonged cardiopulmonary resuscitation. PMID:24827670

Inhibition of Angiotensin-II Production Increases Susceptibility to Acute Ischemia/Reperfusion Arrhythmia

PubMed Central

Taskin, Eylem; Tuncer, Kadir Ali; Guven, Celal; Kaya, Salih Tunc; Dursun, Nurcan

2016-01-01

Background Myocardial ischemia and reperfusion lead to impairment of electrolyte balance and, eventually, lethal arrhythmias. The aim of this study was to investigate the effects of pharmacological inhibition of angiotensin-II (Ang-II) production on heart tissue with ischemia-reperfusion damage, arrhythmia, and oxidative stress. Material/Methods Rats were divided into 4 groups: only ischemia/reperfusion (MI/R), captopril (CAP), aliskiren (AL), and CAP+AL. The drugs were given by gavage 30 min before anesthesia. Blood pressure and electrocardiography (ECG) were recorded during MI/R procedures. The heart tissue and plasma was kept so as to evaluate the total oxidant (TOS), antioxidant status (TAS), and creatine kinase-MB (CK-MB). Results Creatine kinase-MB was not different among the groups. Although TAS was not affected by inhibition of Ang-II production, TOS was significantly lower in the CAP and/or AL groups than in the MI/R group. Furthermore, oxidative stress index was significantly attenuated in the CAP and/or AL groups. Captopril significantly increased the duration of VT during ischemia; however, it did not have any effect on the incidence of arrhythmias. During reperfusion periods, aliskiren and its combinations with captopril significantly reduced the incidence of other types of arrhythmias. Captopril alone had no effect on the incidence of arrhythmias, but significantly increased arrhythmias score and durations of arrhythmias during reperfusion. MAP and heart rate did not show changes in any groups during ischemic and reperfusion periods. Conclusions Angiotensin-II production appears to be associated with elevated levels of reactive oxygen species, but Ang-II inhibitions increases arrhythmia, mainly by initiating ventricular ectopic beats. PMID:27889788

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

NASA Astrophysics Data System (ADS)

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

2013-09-01

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

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

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.

A wearable smartphone-based platform for real-time cardiovascular disease detection via electrocardiogram processing.

PubMed

Oresko, Joseph J; Duschl, Heather; Cheng, Allen C

2010-05-01

Cardiovascular disease (CVD) is the single leading cause of global mortality and is projected to remain so. Cardiac arrhythmia is a very common type of CVD and may indicate an increased risk of stroke or sudden cardiac death. The ECG is the most widely adopted clinical tool to diagnose and assess the risk of arrhythmia. ECGs measure and display the electrical activity of the heart from the body surface. During patients' hospital visits, however, arrhythmias may not be detected on standard resting ECG machines, since the condition may not be present at that moment in time. While Holter-based portable monitoring solutions offer 24-48 h ECG recording, they lack the capability of providing any real-time feedback for the thousands of heart beats they record, which must be tediously analyzed offline. In this paper, we seek to unite the portability of Holter monitors and the real-time processing capability of state-of-the-art resting ECG machines to provide an assistive diagnosis solution using smartphones. Specifically, we developed two smartphone-based wearable CVD-detection platforms capable of performing real-time ECG acquisition and display, feature extraction, and beat classification. Furthermore, the same statistical summaries available on resting ECG machines are provided.

Early classification of pathological heartbeats on wireless body sensor nodes.

PubMed

Braojos, Rubén; Beretta, Ivan; Ansaloni, Giovanni; Atienza, David

2014-11-27

Smart Wireless Body Sensor Nodes (WBSNs) are a novel class of unobtrusive, battery-powered devices allowing the continuous monitoring and real-time interpretation of a subject's bio-signals, such as the electrocardiogram (ECG). These low-power platforms, while able to perform advanced signal processing to extract information on heart conditions, are usually constrained in terms of computational power and transmission bandwidth. It is therefore essential to identify in the early stages which parts of an ECG are critical for the diagnosis and, only in these cases, activate on demand more detailed and computationally intensive analysis algorithms. In this work, we present a comprehensive framework for real-time automatic classification of normal and abnormal heartbeats, targeting embedded and resource-constrained WBSNs. In particular, we provide a comparative analysis of different strategies to reduce the heartbeat representation dimensionality, and therefore the required computational effort. We then combine these techniques with a neuro-fuzzy classification strategy, which effectively discerns normal and pathological heartbeats with a minimal run time and memory overhead. We prove that, by performing a detailed analysis only on the heartbeats that our classifier identifies as abnormal, a WBSN system can drastically reduce its overall energy consumption. Finally, we assess the choice of neuro-fuzzy classification by comparing its performance and workload with respect to other state-of-the-art strategies. Experimental results using the MIT-BIH Arrhythmia database show energy savings of as much as 60% in the signal processing stage, and 63% in the subsequent wireless transmission, when a neuro-fuzzy classification structure is employed, coupled with a dimensionality reduction technique based on random projections.

Early Classification of Pathological Heartbeats on Wireless Body Sensor Nodes

PubMed Central

Braojos, Rubén; Beretta, Ivan; Ansaloni, Giovanni; Atienza, David

2014-01-01

Smart Wireless Body Sensor Nodes (WBSNs) are a novel class of unobtrusive, battery-powered devices allowing the continuous monitoring and real-time interpretation of a subject's bio-signals, such as the electrocardiogram (ECG). These low-power platforms, while able to perform advanced signal processing to extract information on heart conditions, are usually constrained in terms of computational power and transmission bandwidth. It is therefore essential to identify in the early stages which parts of an ECG are critical for the diagnosis and, only in these cases, activate on demand more detailed and computationally intensive analysis algorithms. In this work, we present a comprehensive framework for real-time automatic classification of normal and abnormal heartbeats, targeting embedded and resource-constrained WBSNs. In particular, we provide a comparative analysis of different strategies to reduce the heartbeat representation dimensionality, and therefore the required computational effort. We then combine these techniques with a neuro-fuzzy classification strategy, which effectively discerns normal and pathological heartbeats with a minimal run time and memory overhead. We prove that, by performing a detailed analysis only on the heartbeats that our classifier identifies as abnormal, a WBSN system can drastically reduce its overall energy consumption. Finally, we assess the choice of neuro-fuzzy classification by comparing its performance and workload with respect to other state-of-the-art strategies. Experimental results using the MIT-BIH Arrhythmia database show energy savings of as much as 60% in the signal processing stage, and 63% in the subsequent wireless transmission, when a neuro-fuzzy classification structure is employed, coupled with a dimensionality reduction technique based on random projections. PMID:25436654

ECG changes in factory workers exposed to 27.2  MHz radiofrequency radiation.

PubMed

Chen, Qingsong; Xu, Guoyong; Lang, Li; Yang, Aichu; Li, Shilin; Yang, Liwen; Li, Chaolin; Huang, Hanlin; Li, Tao

2013-05-01

To research the effect of 27.2 MHz radiofrequency radiation on electrocardiograms (ECG), 225 female workers operating radiofrequency machines at a shoe factory were chosen as the exposure group and 100 female workers without exposure from the same factory were selected as the control group. The 6 min electric field strength that the female workers were exposed to was 64.0 ± 25.2 V/m (mean ± SD), which exceeded 61 V/m, the International Commission on Non-Ionizing Radiation Protection reference root mean square levels for occupational exposure. A statistical difference was observed between the exposed group and the control group in terms of the rate of sinus bradycardia (χ(2)  = 11.48, P = 0.003). When several known risk factors for cardiovascular disease were considered, including smoking, age, alcohol ingestion habit, and so on, the exposure duration was not an effective factor for ECG changes, sinus arrhythmia, or sinus bradycardia according to α = 0.05, while P = 0.052 for sinus arrhythmia was very close to 0.05. We did not find any statistical difference in heart rate, duration of the QRS wave (ventricular depolarization), or corrected QT intervals (between the start of the Q wave and end of the T wave) between the exposed and control groups. Occupational exposure to radiofrequency radiation was not found to be a cause of ECG changes after consideration of the confounding factors. Copyright © 2012 Wiley Periodicals, Inc.

Development of a triage engine enabling behavior recognition and lethal arrhythmia detection for remote health care system.

PubMed

Sugano, Hiroto; Hara, Shinsuke; Tsujioka, Tetsuo; Inoue, Tadayuki; Nakajima, Shigeyoshi; Kozaki, Takaaki; Namkamura, Hajime; Takeuchi, Kazuhide

2011-01-01

For ubiquitous health care systems which continuously monitor a person's vital signs such as electrocardiogram (ECG), body surface temperature and three-dimensional (3D) acceleration by wireless, it is important to accurately detect the occurrence of an abnormal event in the data and immediately inform a medical doctor of its detail. In this paper, we introduce a remote health care system, which is composed of a wireless vital sensor, multiple receivers and a triage engine installed in a desktop personal computer (PC). The middleware installed in the receiver, which was developed in C++, supports reliable data handling of vital data to the ethernet port. On the other hand, the human interface of the triage engine, which was developed in JAVA, shows graphics on his/her ECG data, 3D acceleration data, body surface temperature data and behavior status in the display of the desktop PC and sends an urgent e-mail containing the display data to a pre-registered medical doctor when it detects the occurrence of an abnormal event. In the triage engine, the lethal arrhythmia detection algorithm based on short time Fourier transform (STFT) analysis can achieve 100 % sensitivity and 99.99 % specificity, and the behavior recognition algorithm based on the combination of the nearest neighbor method and the Naive Bayes method can achieve more than 71 % classification accuracy.

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

PubMed

Sharifahmadian, Ershad

2006-01-01

The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

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

PubMed

Tripathy, R K; Dandapat, S

2016-06-01

The cardiac activities such as the depolarization and the relaxation of atria and ventricles are observed in electrocardiogram (ECG). The changes in the morphological features of ECG are the symptoms of particular heart pathology. It is a cumbersome task for medical experts to visually identify any subtle changes in the morphological features during 24 hours of ECG recording. Therefore, the automated analysis of ECG signal is a need for accurate detection of cardiac abnormalities. In this paper, a novel method for automated detection of cardiac abnormalities from multilead ECG is proposed. The method uses multiscale phase alternation (PA) features of multilead ECG and two classifiers, k-nearest neighbor (KNN) and fuzzy KNN for classification of bundle branch block (BBB), myocardial infarction (MI), heart muscle defect (HMD) and healthy control (HC). The dual tree complex wavelet transform (DTCWT) is used to decompose the ECG signal of each lead into complex wavelet coefficients at different scales. The phase of the complex wavelet coefficients is computed and the PA values at each wavelet scale are used as features for detection and classification of cardiac abnormalities. A publicly available multilead ECG database (PTB database) is used for testing of the proposed method. The experimental results show that, the proposed multiscale PA features and the fuzzy KNN classifier have better performance for detection of cardiac abnormalities with sensitivity values of 78.12 %, 80.90 % and 94.31 % for BBB, HMD and MI classes. The sensitivity value of proposed method for MI class is compared with the state-of-art techniques from multilead ECG.

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

PubMed

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

2017-07-01

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

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

PubMed Central

Alday, Erick A. Perez; Colman, Michael A.; Langley, Philip; Butters, Timothy D.; Higham, Jonathan; Workman, Antony J.; Hancox, Jules C.; Zhang, Henggui

2015-01-01

Rapid atrial arrhythmias such as atrial fibrillation (AF) predispose to ventricular arrhythmias, sudden cardiac death and stroke. Identifying the origin of atrial ectopic activity from the electrocardiogram (ECG) can help to diagnose the early onset of AF in a cost-effective manner. The complex and rapid atrial electrical activity during AF makes it difficult to obtain detailed information on atrial activation using the standard 12-lead ECG alone. Compared to conventional 12-lead ECG, more detailed ECG lead configurations may provide further information about spatio-temporal dynamics of the body surface potential (BSP) during atrial excitation. We apply a recently developed 3D human atrial model to simulate electrical activity during normal sinus rhythm and ectopic pacing. The atrial model is placed into a newly developed torso model which considers the presence of the lungs, liver and spinal cord. A boundary element method is used to compute the BSP resulting from atrial excitation. Elements of the torso mesh corresponding to the locations of the placement of the electrodes in the standard 12-lead and a more detailed 64-lead ECG configuration were selected. The ectopic focal activity was simulated at various origins across all the different regions of the atria. Simulated BSP maps during normal atrial excitation (i.e. sinoatrial node excitation) were compared to those observed experimentally (obtained from the 64-lead ECG system), showing a strong agreement between the evolution in time of the simulated and experimental data in the P-wave morphology of the ECG and dipole evolution. An algorithm to obtain the location of the stimulus from a 64-lead ECG system was developed. The algorithm presented had a success rate of 93%, meaning that it correctly identified the origin of atrial focus in 75/80 simulations, and involved a general approach relevant to any multi-lead ECG system. This represents a significant improvement over previously developed algorithms. PMID

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

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.

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.

A Novel ECG Data Compression Method Using Adaptive Fourier Decomposition With Security Guarantee in e-Health Applications.

PubMed

Ma, JiaLi; Zhang, TanTan; Dong, MingChui

2015-05-01

This paper presents a novel electrocardiogram (ECG) compression method for e-health applications by adapting an adaptive Fourier decomposition (AFD) algorithm hybridized with a symbol substitution (SS) technique. The compression consists of two stages: first stage AFD executes efficient lossy compression with high fidelity; second stage SS performs lossless compression enhancement and built-in data encryption, which is pivotal for e-health. Validated with 48 ECG records from MIT-BIH arrhythmia benchmark database, the proposed method achieves averaged compression ratio (CR) of 17.6-44.5 and percentage root mean square difference (PRD) of 0.8-2.0% with a highly linear and robust PRD-CR relationship, pushing forward the compression performance to an unexploited region. As such, this paper provides an attractive candidate of ECG compression method for pervasive e-health applications.

Cardiac arrhythmias during aerobatic flight and its simulation on a centrifuge.

PubMed

Zawadzka-Bartczak, Ewelina K; Kopka, Lech H

2011-06-01

It is well known that accelerations during centrifuge training and during flight can provoke cardiac arrhythmias. Our study was designed to investigate both the similarities and differences between heart rhythm disturbances during flights and centrifuge tests. There were 40 asymptomatic, healthy pilots who performed two training flights and were also tested in a human centrifuge according to a program of rapid onset rate acceleration (ROR) and of centrifuge simulation of the actual acceleration experienced in flight (Simulation). During the flight and centrifuge tests ECG was monitored with the Holter method. ECG was examined for heart rhythm changes and disturbances. During flights, premature ventricular contractions (PVCs) were found in 25% of the subjects, premature supraventricular contractions (PSVCs) and PVCs with bigeminy in 5%, and pairs of PVCs in 2.5% of subjects. During the centrifuge tests, PVCs were experienced by 45% of the subjects, PSVCs and pairs of PVCs by 7.5%, and PVCs with bigeminy by 2.5%. Sinus bradycardia was observed during flights and centrifuge tests in 7.5% of subjects. Comparative evaluation of electrocardiographic records in military pilots during flights and centrifuge tests demonstrated that: 1) there were no clinically significant arrhythmias recorded; and 2) the frequency and kind of heart rhythm disturbances during aerobatic flight and its simulation on a centrifuge were not identical and did not occur repetitively in the same persons during equal phases of the tests.

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.

Real time reconstruction of quasiperiodic multi parameter physiological signals

NASA Astrophysics Data System (ADS)

Ganeshapillai, Gartheeban; Guttag, John

2012-12-01

A modern intensive care unit (ICU) has automated analysis systems that depend on continuous uninterrupted real time monitoring of physiological signals such as electrocardiogram (ECG), arterial blood pressure (ABP), and photo-plethysmogram (PPG). These signals are often corrupted by noise, artifacts, and missing data. We present an automated learning framework for real time reconstruction of corrupted multi-parameter nonstationary quasiperiodic physiological signals. The key idea is to learn a patient-specific model of the relationships between signals, and then reconstruct corrupted segments using the information available in correlated signals. We evaluated our method on MIT-BIH arrhythmia data, a two-channel ECG dataset with many clinically significant arrhythmias, and on the CinC challenge 2010 data, a multi-parameter dataset containing ECG, ABP, and PPG. For each, we evaluated both the residual distance between the original signals and the reconstructed signals, and the performance of a heartbeat classifier on a reconstructed ECG signal. At an SNR of 0 dB, the average residual distance on the CinC data was roughly 3% of the energy in the signal, and on the arrhythmia database it was roughly 16%. The difference is attributable to the large amount of diversity in the arrhythmia database. Remarkably, despite the relatively high residual difference, the classification accuracy on the arrhythmia database was still 98%, indicating that our method restored the physiologically important aspects of the signal.

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

PubMed

Fan, Xiaomao; Yao, Qihang; Li, Ye; Chen, Runge; Cai, Yunpeng

2018-05-03

Long-term electrocardiogram (ECG) is one of the important diagnostic assistant approaches in capturing intermittent cardiac arrhythmias. Combination of miniaturized wearable holters and healthcare platforms enable people to have their cardiac condition monitored at home. The high computational burden created by concurrent processing of numerous holter data poses a serious challenge to the healthcare platform. An alternative solution is to shift the analysis tasks from healthcare platforms to the mobile computing devices. However, long-term ECG data processing is quite time consuming due to the limited computation power of the mobile central unit processor (CPU). This paper aimed to propose a novel parallel automatic ECG analysis algorithm which exploited the mobile graphics processing unit (GPU) to reduce the response time for processing long-term ECG data. By studying the architecture of the sequential automatic ECG analysis algorithm, we parallelized the time-consuming parts and reorganized the entire pipeline in the parallel algorithm to fully utilize the heterogeneous computing resources of CPU and GPU. The experimental results showed that the average executing time of the proposed algorithm on a clinical long-term ECG dataset (duration 23.0 ± 1.0 h per signal) is 1.215 ± 0.140 s, which achieved an average speedup of 5.81 ± 0.39× without compromising analysis accuracy, comparing with the sequential algorithm. Meanwhile, the battery energy consumption of the automatic ECG analysis algorithm was reduced by 64.16%. Excluding energy consumption from data loading, 79.44% of the energy consumption could be saved, which alleviated the problem of limited battery working hours for mobile devices. The reduction of response time and battery energy consumption in ECG analysis not only bring better quality of experience to holter users, but also make it possible to use mobile devices as ECG terminals for healthcare professions such as physicians and health

GPU based cloud system for high-performance arrhythmia detection with parallel k-NN algorithm.

PubMed

Tae Joon Jun; Hyun Ji Park; Hyuk Yoo; Young-Hak Kim; Daeyoung Kim

2016-08-01

In this paper, we propose an GPU based Cloud system for high-performance arrhythmia detection. Pan-Tompkins algorithm is used for QRS detection and we optimized beat classification algorithm with K-Nearest Neighbor (K-NN). To support high performance beat classification on the system, we parallelized beat classification algorithm with CUDA to execute the algorithm on virtualized GPU devices on the Cloud system. MIT-BIH Arrhythmia database is used for validation of the algorithm. The system achieved about 93.5% of detection rate which is comparable to previous researches while our algorithm shows 2.5 times faster execution time compared to CPU only detection algorithm.

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

PubMed

Di Marco, Luigi Y; Chiari, Lorenzo

2011-04-03

Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra.

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

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

Why Arrhythmia Matters

MedlinePlus

... Disease Venous Thromboembolism Aortic Aneurysm More Why Arrhythmia Matters Updated:Dec 21,2016 When the heart's ability ... September 2016. Arrhythmia • Home • About Arrhythmia • Why Arrhythmia Matters • Understand Your Risk for Arrhythmia • Symptoms, Diagnosis & Monitoring ...

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.

A novel algorithm for reducing false arrhythmia alarms in intensive care units.

PubMed

Srivastava, Chandan; Sharma, Sonal; Jalali, Ali

2016-08-01

Alarm fatigue in intensive care units (ICU) is one of the top healthcare issues in the US. False alarms in ICU will decrease the quality of care and staff response time over the alarms. Normally, false alarm will cause desensitization of the clinical staff which leads to warnings and misleading, if the triggered alarm is true. In this study, we have proposed a multi-model ensemble approach to reduce the false alarm rate in monitoring systems. We have used 750 patient records from PhysioNet database. At First arrhythmia based features from electrocardiogram (ECG), arterial blood pressure (ABP) and photoplethysmogram (PPG) features were extracted from the records. Next, the dataset has been separated into two subsets on the basis of available features information. The first dataset (DS1) is the combination of ECG physiological, ABP and PPG features. Their correlation coefficient and p-values criteria have been applied for relevant alarm-wise feature-set selection, and random forest classifier was used for model development and validation. The threshold based approach was used on second dataset (DS2) which is the combination of arrhythmia, ABP and PPG features. The developed ensemble model is able to achieve sensitivity 83.33-100 % (average 95.56 %) being true alarms and suppress false alarms rate 66.67-89% (average 77.25%). The predictability of classifier shows the advantage to deal with unbalanced set of information, therefore overall model performance has reached to 83.96% accuracy.

A deep convolutional neural network model to classify heartbeats.

PubMed

Acharya, U Rajendra; Oh, Shu Lih; Hagiwara, Yuki; Tan, Jen Hong; Adam, Muhammad; Gertych, Arkadiusz; Tan, Ru San

2017-10-01

The electrocardiogram (ECG) is a standard test used to monitor the activity of the heart. Many cardiac abnormalities will be manifested in the ECG including arrhythmia which is a general term that refers to an abnormal heart rhythm. The basis of arrhythmia diagnosis is the identification of normal versus abnormal individual heart beats, and their correct classification into different diagnoses, based on ECG morphology. Heartbeats can be sub-divided into five categories namely non-ectopic, supraventricular ectopic, ventricular ectopic, fusion, and unknown beats. It is challenging and time-consuming to distinguish these heartbeats on ECG as these signals are typically corrupted by noise. We developed a 9-layer deep convolutional neural network (CNN) to automatically identify 5 different categories of heartbeats in ECG signals. Our experiment was conducted in original and noise attenuated sets of ECG signals derived from a publicly available database. This set was artificially augmented to even out the number of instances the 5 classes of heartbeats and filtered to remove high-frequency noise. The CNN was trained using the augmented data and achieved an accuracy of 94.03% and 93.47% in the diagnostic classification of heartbeats in original and noise free ECGs, respectively. When the CNN was trained with highly imbalanced data (original dataset), the accuracy of the CNN reduced to 89.07%% and 89.3% in noisy and noise-free ECGs. When properly trained, the proposed CNN model can serve as a tool for screening of ECG to quickly identify different types and frequency of arrhythmic heartbeats. Copyright © 2017 Elsevier Ltd. All rights reserved.

False alarm reduction in BSN-based cardiac monitoring using signal quality and activity type information.

PubMed

Tanantong, Tanatorn; Nantajeewarawat, Ekawit; Thiemjarus, Surapa

2015-02-09

False alarms in cardiac monitoring affect the quality of medical care, impacting on both patients and healthcare providers. In continuous cardiac monitoring using wireless Body Sensor Networks (BSNs), the quality of ECG signals can be deteriorated owing to several factors, e.g., noises, low battery power, and network transmission problems, often resulting in high false alarm rates. In addition, body movements occurring from activities of daily living (ADLs) can also create false alarms. This paper presents a two-phase framework for false arrhythmia alarm reduction in continuous cardiac monitoring, using signals from an ECG sensor and a 3D accelerometer. In the first phase, classification models constructed using machine learning algorithms are used for labeling input signals. ECG signals are labeled with heartbeat types and signal quality levels, while 3D acceleration signals are labeled with ADL types. In the second phase, a rule-based expert system is used for combining classification results in order to determine whether arrhythmia alarms should be accepted or suppressed. The proposed framework was validated on datasets acquired using BSNs and the MIT-BIH arrhythmia database. For the BSN dataset, acceleration and ECG signals were collected from 10 young and 10 elderly subjects while they were performing ADLs. The framework reduced the false alarm rate from 9.58% to 1.43% in our experimental study, showing that it can potentially assist physicians in diagnosing a vast amount of data acquired from wireless sensors and enhance the performance of continuous cardiac monitoring.

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.

Metabolic Syndrome Remodels Electrical Activity of the Sinoatrial Node and Produces Arrhythmias in Rats

PubMed Central

Albarado-Ibañez, Alondra; Avelino-Cruz, José Everardo; Velasco, Myrian; Torres-Jácome, Julián; Hiriart, Marcia

2013-01-01

In the last ten years, the incidences of metabolic syndrome and supraventricular arrhythmias have greatly increased. The metabolic syndrome is a cluster of alterations, which include obesity, hypertension, hypertriglyceridemia, glucose intolerance and insulin resistance, that increase the risk of developing, among others, atrial and nodal arrhythmias. The aim of this study is to demonstrate that metabolic syndrome induces electrical remodeling of the sinus node and produces arrhythmias. We induced metabolic syndrome in 2-month-old male Wistar rats by administering 20% sucrose in the drinking water. Eight weeks later, the rats were anesthetized and the electrocardiogram was recorded, revealing the presence of arrhythmias only in treated rats. Using conventional microelectrode and voltage clamp techniques, we analyzed the electrical activity of the sinoatrial node. We observed that in the sinoatrial node of “metabolic syndrome rats”, compared to controls, the spontaneous firing of all cells decreased, while the slope of the diastolic depolarization increased only in latent pacemaker cells. Accordingly, the pacemaker currents If and Ist increased. Furthermore, histological analysis showed a large amount of fat surrounding nodal cardiomyocytes and a rise in the sympathetic innervation. Finally, Poincaré plot denoted irregularity in the R-R and P-P ECG intervals, in agreement with the variability of nodal firing potential recorded in metabolic syndrome rats. We conclude that metabolic syndrome produces a dysfunction SA node by disrupting normal architecture and the electrical activity, which could explain the onset of arrhythmias in rats. PMID:24250786

Metabolic syndrome remodels electrical activity of the sinoatrial node and produces arrhythmias in rats.

PubMed

Albarado-Ibañez, Alondra; Avelino-Cruz, José Everardo; Velasco, Myrian; Torres-Jácome, Julián; Hiriart, Marcia

2013-01-01

In the last ten years, the incidences of metabolic syndrome and supraventricular arrhythmias have greatly increased. The metabolic syndrome is a cluster of alterations, which include obesity, hypertension, hypertriglyceridemia, glucose intolerance and insulin resistance, that increase the risk of developing, among others, atrial and nodal arrhythmias. The aim of this study is to demonstrate that metabolic syndrome induces electrical remodeling of the sinus node and produces arrhythmias. We induced metabolic syndrome in 2-month-old male Wistar rats by administering 20% sucrose in the drinking water. Eight weeks later, the rats were anesthetized and the electrocardiogram was recorded, revealing the presence of arrhythmias only in treated rats. Using conventional microelectrode and voltage clamp techniques, we analyzed the electrical activity of the sinoatrial node. We observed that in the sinoatrial node of "metabolic syndrome rats", compared to controls, the spontaneous firing of all cells decreased, while the slope of the diastolic depolarization increased only in latent pacemaker cells. Accordingly, the pacemaker currents If and Ist increased. Furthermore, histological analysis showed a large amount of fat surrounding nodal cardiomyocytes and a rise in the sympathetic innervation. Finally, Poincaré plot denoted irregularity in the R-R and P-P ECG intervals, in agreement with the variability of nodal firing potential recorded in metabolic syndrome rats. We conclude that metabolic syndrome produces a dysfunction SA node by disrupting normal architecture and the electrical activity, which could explain the onset of arrhythmias in rats.

Arrhythmias and hemodialysis: role of potassium and new diagnostic tools.

PubMed

Buemi, Michele; Coppolino, Giuseppe; Bolignano, Davide; Sturiale, Alessio; Campo, Susanna; Buemi, Antoine; Crascì, Eleonora; Romeo, Adolfo

2009-01-01

Cardiovascular diseases represent the main causes of death in patients affected by renal failure, and arrhythmias are frequently observed in patients undergoing hemodialysis. Dialytic treatment per se can be considered as an arrhythmogenic stimulus; moreover, uraemic patients are characterized by a "pro-arrhythmic substrate" because of the high prevalence of ischaemic heart disease, left ventricular hypertrophy and autonomic neuropathy. One of the most important pathogenetic element involved in the onset of intra-dialytic arrhythmias is the alteration in electrolytes concentration, particularly calcium and potassium. It may be very useful to monitor the patient's cardiac activity during the whole hemodilaytic session. Nevertheless, the application of an extended intradialytic electrocardiographic monitoring is not simple because of several technical and structural impairments. We tried to overcome these difficulties using Whealthy, a wearable system consisting in a t-shirt composed of conductors and piezoresistive materials, integrated to form fibers and threads connected to tissutal sensors, electrodes, and connectors. ECG and pneumographic impedance signals are acquired by the electrodes in the tissue, and the data are registered by a small computer and transmitted via GPRS or Bluetooth.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed Central

2011-01-01

Background Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. Methods This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. Results The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. Conclusions The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra. PMID:21457580

Arrhythmia

MedlinePlus

... cardiologists who specialize in arrhythmias. Medical and Family Histories To diagnose an arrhythmia, your doctor may ask ... your doctor will use a procedure called cardiac catheterization (KATH-e-ter-ih-ZA-shun). A thin, ...

Detection and Prevention of Cardiac Arrhythmias During Space Flight

NASA Technical Reports Server (NTRS)

Pillai, Dilip; Rosenbaum, David S.; Liszka, Kathy J.; York, David W.; Mackin, Michael A.; Lichter, Michael J.

2004-01-01

There have been reports suggesting that long-duration space flight might lead to an increased risk of potentially serious heart rhythm disturbances. If space flight does, in fact, significantly decrease cardiac electrical stability, the effects could be catastrophic, potentially leading to sudden cardiac death. It will be important to determine the mechanisms underlying this phenomenon in order to prepare for long-term manned lunar and interplanetary missions and to develop appropriate countermeasures. Electrical alternans affecting the ST segment and T-wave have been demonstrated to be common among patients at increased risk for ventricular arrhythmias. Subtle electrical alternans on the ECG may serve as a noninvasive marker of vulnerability to ventricular arrhythmias. We are studying indices of electrical instability in the heart for long term space missions by non-invasively measuring microvolt level T-wave alternans in a reduced gravity environment. In this investigation we are using volunteer subjects on the KC-135 aircraft as an initial study of the effect of electrical adaptation of the heart to microgravity. T-wave alternans will be analyzed for heart rate variability and QT restitution curve plotting will be compared for statistical significance.

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).

Random forests ensemble classifier trained with data resampling strategy to improve cardiac arrhythmia diagnosis.

PubMed

Ozçift, Akin

2011-05-01

Supervised classification algorithms are commonly used in the designing of computer-aided diagnosis systems. In this study, we present a resampling strategy based Random Forests (RF) ensemble classifier to improve diagnosis of cardiac arrhythmia. Random forests is an ensemble classifier that consists of many decision trees and outputs the class that is the mode of the class's output by individual trees. In this way, an RF ensemble classifier performs better than a single tree from classification performance point of view. In general, multiclass datasets having unbalanced distribution of sample sizes are difficult to analyze in terms of class discrimination. Cardiac arrhythmia is such a dataset that has multiple classes with small sample sizes and it is therefore adequate to test our resampling based training strategy. The dataset contains 452 samples in fourteen types of arrhythmias and eleven of these classes have sample sizes less than 15. Our diagnosis strategy consists of two parts: (i) a correlation based feature selection algorithm is used to select relevant features from cardiac arrhythmia dataset. (ii) RF machine learning algorithm is used to evaluate the performance of selected features with and without simple random sampling to evaluate the efficiency of proposed training strategy. The resultant accuracy of the classifier is found to be 90.0% and this is a quite high diagnosis performance for cardiac arrhythmia. Furthermore, three case studies, i.e., thyroid, cardiotocography and audiology, are used to benchmark the effectiveness of the proposed method. The results of experiments demonstrated the efficiency of random sampling strategy in training RF ensemble classification algorithm. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

Symmetrical compression distance for arrhythmia discrimination in cloud-based big-data services.

PubMed

Lillo-Castellano, J M; Mora-Jiménez, I; Santiago-Mozos, R; Chavarría-Asso, F; Cano-González, A; García-Alberola, A; Rojo-Álvarez, J L

2015-07-01

The current development of cloud computing is completely changing the paradigm of data knowledge extraction in huge databases. An example of this technology in the cardiac arrhythmia field is the SCOOP platform, a national-level scientific cloud-based big data service for implantable cardioverter defibrillators. In this scenario, we here propose a new methodology for automatic classification of intracardiac electrograms (EGMs) in a cloud computing system, designed for minimal signal preprocessing. A new compression-based similarity measure (CSM) is created for low computational burden, so-called weighted fast compression distance, which provides better performance when compared with other CSMs in the literature. Using simple machine learning techniques, a set of 6848 EGMs extracted from SCOOP platform were classified into seven cardiac arrhythmia classes and one noise class, reaching near to 90% accuracy when previous patient arrhythmia information was available and 63% otherwise, hence overcoming in all cases the classification provided by the majority class. Results show that this methodology can be used as a high-quality service of cloud computing, providing support to physicians for improving the knowledge on patient diagnosis.

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.

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.

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.

Early repolarization, localization of J point elevation on ECG and arrhythmias.

PubMed

Matoshvili, Z; Petriashvili, Sh; Archvadze, A; Azaladze, I

2015-04-01

Final aim of this observational study was to determine correlation between localization of J point elevation and number of premature ventricular beats. The 52 patients (19-68 years old; 31 men and 21 women) were divided in two groups based on localization of J point elevation. First Group - 9 patients (5 men and 4 women) with J-point elevation ≥1 mm in ≥2 contiguous inferior and/or lateral leads on a standard 12-lead ECG reading, Second Group - other 43 (26 men and 17 women) patients with another localization of J point elevation. Total summarized number of premature ventricular contractions for each group was compared and analyzed. The results of the study shows that the number of premature ventricular beats in first group was 61% higher. Thus, in our opinion J-point elevation ≥1 mm in ≥2 contiguous inferior and/or lateral leads, is more arrhythmogenic. Data shows that this difference is statistically significant.

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.

Novel electrogram device with web-based service centre for ambulatory ECG monitoring.

PubMed

Tan, B Y; Ho, K L; Ching, C K; Teo, W S

2010-07-01

Arrhythmias are often intermittent, and a normal electrocardiogram (ECG) may not be diagnostic. The purpose of this study was to evaluate the usefulness of HeartWave500 (HW), a novel web-based ambulatory ECG monitoring device. A total of 120 patients from the National Heart Centre, Singapore were prospectively randomised in a three to one ratio to either HW or a standard transtelephonic (TT) event recorder. HW records five leads and transmits to an internet server, while TT transmits audio data to a central station. Monitoring was conducted for two weeks. The diagnostic yield was calculated in two ways: the percentage of patients successfully diagnosed as a function of time, and the absolute number of new diagnoses per patient per week. 33 patients (14 male, 19 female; mean age 49.6 + or - 11.1 years) were randomised to TT. 87 patients (32 male, 55 female; mean age 43.7 + or - 12.2 years) were randomised to HW. At the end of two weeks, the percentage of patients diagnosed with any arrhythmia was similar for both groups (66.7 percent for TT versus 67.8 percent for HW). There was a trend toward significance for the number of diagnoses per patient per week for Week 2 between TT and HW (0.58 + or - 0.75 versus 0.34 + or - 0.55, p is 0.06). Transmitted ECGs were read earlier for HW (18 minutes versus 1107 minutes, Mann-Whitney non-parametric test, p is less than 0.05). Transmitted recordings that were unreadable were also significantly lower for HW (8.0 percent versus 17.6 percent, chi-square test, p is less than 0.05). HW and TT have similar diagnostic yields. There is a trend toward a shorter monitoring time for HW. The ability of HW to record and transmit via the web, the earlier review of data and low unreadable data make HW an attractive alternative to TT.

LiteNet: Lightweight Neural Network for Detecting Arrhythmias at Resource-Constrained Mobile Devices.

PubMed

He, Ziyang; Zhang, Xiaoqing; Cao, Yangjie; Liu, Zhi; Zhang, Bo; Wang, Xiaoyan

2018-04-17

By running applications and services closer to the user, edge processing provides many advantages, such as short response time and reduced network traffic. Deep-learning based algorithms provide significantly better performances than traditional algorithms in many fields but demand more resources, such as higher computational power and more memory. Hence, designing deep learning algorithms that are more suitable for resource-constrained mobile devices is vital. In this paper, we build a lightweight neural network, termed LiteNet which uses a deep learning algorithm design to diagnose arrhythmias, as an example to show how we design deep learning schemes for resource-constrained mobile devices. Compare to other deep learning models with an equivalent accuracy, LiteNet has several advantages. It requires less memory, incurs lower computational cost, and is more feasible for deployment on resource-constrained mobile devices. It can be trained faster than other neural network algorithms and requires less communication across different processing units during distributed training. It uses filters of heterogeneous size in a convolutional layer, which contributes to the generation of various feature maps. The algorithm was tested using the MIT-BIH electrocardiogram (ECG) arrhythmia database; the results showed that LiteNet outperforms comparable schemes in diagnosing arrhythmias, and in its feasibility for use at the mobile devices.

LiteNet: Lightweight Neural Network for Detecting Arrhythmias at Resource-Constrained Mobile Devices

PubMed Central

Zhang, Xiaoqing; Cao, Yangjie; Liu, Zhi; Zhang, Bo; Wang, Xiaoyan

2018-01-01

By running applications and services closer to the user, edge processing provides many advantages, such as short response time and reduced network traffic. Deep-learning based algorithms provide significantly better performances than traditional algorithms in many fields but demand more resources, such as higher computational power and more memory. Hence, designing deep learning algorithms that are more suitable for resource-constrained mobile devices is vital. In this paper, we build a lightweight neural network, termed LiteNet which uses a deep learning algorithm design to diagnose arrhythmias, as an example to show how we design deep learning schemes for resource-constrained mobile devices. Compare to other deep learning models with an equivalent accuracy, LiteNet has several advantages. It requires less memory, incurs lower computational cost, and is more feasible for deployment on resource-constrained mobile devices. It can be trained faster than other neural network algorithms and requires less communication across different processing units during distributed training. It uses filters of heterogeneous size in a convolutional layer, which contributes to the generation of various feature maps. The algorithm was tested using the MIT-BIH electrocardiogram (ECG) arrhythmia database; the results showed that LiteNet outperforms comparable schemes in diagnosing arrhythmias, and in its feasibility for use at the mobile devices. PMID:29673171

Classification of cardiac patient states using artificial neural networks

PubMed Central

Kannathal, N; Acharya, U Rajendra; Lim, Choo Min; Sadasivan, PK; Krishnan, SM

2003-01-01

Electrocardiogram (ECG) is a nonstationary signal; therefore, the disease indicators may occur at random in the time scale. This may require the patient be kept under observation for long intervals in the intensive care unit of hospitals for accurate diagnosis. The present study examined the classification of the states of patients with certain diseases in the intensive care unit using their ECG and an Artificial Neural Networks (ANN) classification system. The states were classified into normal, abnormal and life threatening. Seven significant features extracted from the ECG were fed as input parameters to the ANN for classification. Three neural network techniques, namely, back propagation, self-organizing maps and radial basis functions, were used for classification of the patient states. The ANN classifier in this case was observed to be correct in approximately 99% of the test cases. This result was further improved by taking 13 features of the ECG as input for the ANN classifier. PMID:19649222

Use of whole exome sequencing for the identification of Ito-based arrhythmia mechanism and therapy.

PubMed

Sturm, Amy C; Kline, Crystal F; Glynn, Patric; Johnson, Benjamin L; Curran, Jerry; Kilic, Ahmet; Higgins, Robert S D; Binkley, Philip F; Janssen, Paul M L; Weiss, Raul; Raman, Subha V; Fowler, Steven J; Priori, Silvia G; Hund, Thomas J; Carnes, Cynthia A; Mohler, Peter J

2015-05-26

Identified genetic variants are insufficient to explain all cases of inherited arrhythmia. We tested whether the integration of whole exome sequencing with well-established clinical, translational, and basic science platforms could provide rapid and novel insight into human arrhythmia pathophysiology and disease treatment. We report a proband with recurrent ventricular fibrillation, resistant to standard therapeutic interventions. Using whole-exome sequencing, we identified a variant in a previously unidentified exon of the dipeptidyl aminopeptidase-like protein-6 (DPP6) gene. This variant is the first identified coding mutation in DPP6 and augments cardiac repolarizing current (Ito) causing pathological changes in Ito and action potential morphology. We designed a therapeutic regimen incorporating dalfampridine to target Ito. Dalfampridine, approved for multiple sclerosis, normalized the ECG and reduced arrhythmia burden in the proband by >90-fold. This was combined with cilostazol to accelerate the heart rate to minimize the reverse-rate dependence of augmented Ito. We describe a novel arrhythmia mechanism and therapeutic approach to ameliorate the disease. Specifically, we identify the first coding variant of DPP6 in human ventricular fibrillation. These findings illustrate the power of genetic approaches for the elucidation and treatment of disease when carefully integrated with clinical and basic/translational research teams. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

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

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

Correlation-based pattern recognition for implantable defibrillators.

PubMed Central

Wilkins, J.

1996-01-01

An estimated 300,000 Americans die each year from cardiac arrhythmias. Historically, drug therapy or surgery were the only treatment options available for patients suffering from arrhythmias. Recently, implantable arrhythmia management devices have been developed. These devices allow abnormal cardiac rhythms to be sensed and corrected in vivo. Proper arrhythmia classification is critical to selecting the appropriate therapeutic intervention. The classification problem is made more challenging by the power/computation constraints imposed by the short battery life of implantable devices. Current devices utilize heart rate-based classification algorithms. Although easy to implement, rate-based approaches have unacceptably high error rates in distinguishing supraventricular tachycardia (SVT) from ventricular tachycardia (VT). Conventional morphology assessment techniques used in ECG analysis often require too much computation to be practical for implantable devices. In this paper, a computationally-efficient, arrhythmia classification architecture using correlation-based morphology assessment is presented. The architecture classifies individuals heart beats by assessing similarity between an incoming cardiac signal vector and a series of prestored class templates. A series of these beat classifications are used to make an overall rhythm assessment. The system makes use of several new results in the field of pattern recognition. The resulting system achieved excellent accuracy in discriminating SVT and VT. PMID:8947674

Exploiting periodicity to extract the atrial activity in atrial arrhythmias

NASA Astrophysics Data System (ADS)

Llinares, Raul; Igual, Jorge

2011-12-01

Atrial fibrillation disorders are one of the main arrhythmias of the elderly. The atrial and ventricular activities are decoupled during an atrial fibrillation episode, and very rapid and irregular waves replace the usual atrial P-wave in a normal sinus rhythm electrocardiogram (ECG). The estimation of these wavelets is a must for clinical analysis. We propose a new approach to this problem focused on the quasiperiodicity of these wavelets. Atrial activity is characterized by a main atrial rhythm in the interval 3-12 Hz. It enables us to establish the problem as the separation of the original sources from the instantaneous linear combination of them recorded in the ECG or the extraction of only the atrial component exploiting the quasiperiodic feature of the atrial signal. This methodology implies the previous estimation of such main atrial period. We present two algorithms that separate and extract the atrial rhythm starting from a prior estimation of the main atrial frequency. The first one is an algebraic method based on the maximization of a cost function that measures the periodicity. The other one is an adaptive algorithm that exploits the decorrelation of the atrial and other signals diagonalizing the correlation matrices at multiple lags of the period of atrial activity. The algorithms are applied successfully to synthetic and real data. In simulated ECGs, the average correlation index obtained was 0.811 and 0.847, respectively. In real ECGs, the accuracy of the results was validated using spectral and temporal parameters. The average peak frequency and spectral concentration obtained were 5.550 and 5.554 Hz and 56.3 and 54.4%, respectively, and the kurtosis was 0.266 and 0.695. For validation purposes, we compared the proposed algorithms with established methods, obtaining better results for simulated and real registers.

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

PubMed

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

2013-01-01

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

Appropriate threshold levels of cardiac beat-to-beat variation in semi-automatic analysis of equine ECG recordings.

PubMed

Flethøj, Mette; Kanters, Jørgen K; Pedersen, Philip J; Haugaard, Maria M; Carstensen, Helena; Olsen, Lisbeth H; Buhl, Rikke

2016-11-28

Although premature beats are a matter of concern in horses, the interpretation of equine ECG recordings is complicated by a lack of standardized analysis criteria and a limited knowledge of the normal beat-to-beat variation of equine cardiac rhythm. The purpose of this study was to determine the appropriate threshold levels of maximum acceptable deviation of RR intervals in equine ECG analysis, and to evaluate a novel two-step timing algorithm by quantifying the frequency of arrhythmias in a cohort of healthy adult endurance horses. Beat-to-beat variation differed considerably with heart rate (HR), and an adaptable model consisting of three different HR ranges with separate threshold levels of maximum acceptable RR deviation was consequently defined. For resting HRs <60 beats/min (bpm) the threshold level of RR deviation was set at 20%, for HRs in the intermediate range between 60 and 100 bpm the threshold was 10%, and for exercising HRs >100 bpm, the threshold level was 4%. Supraventricular premature beats represented the most prevalent arrhythmia category with varying frequencies in seven horses at rest (median 7, range 2-86) and six horses during exercise (median 2, range 1-24). Beat-to-beat variation of equine cardiac rhythm varies according to HR, and threshold levels in equine ECG analysis should be adjusted accordingly. Standardization of the analysis criteria will enable comparisons of studies and follow-up examinations of patients. A small number of supraventricular premature beats appears to be a normal finding in endurance horses. Further studies are required to validate the findings and determine the clinical significance of premature beats in horses.

21 CFR 870.1025 - Arrhythmia detector and alarm (including ST-segment measurement and alarm).

Code of Federal Regulations, 2011 CFR

2011-04-01

... a visible or audible signal or alarm when atrial or ventricular arrhythmia, such as premature contraction or ventricular fibrillation, occurs. (b) Classification. Class II (special controls). The guidance...

21 CFR 870.1025 - Arrhythmia detector and alarm (including ST-segment measurement and alarm).

Code of Federal Regulations, 2010 CFR

2010-04-01

... a visible or audible signal or alarm when atrial or ventricular arrhythmia, such as premature contraction or ventricular fibrillation, occurs. (b) Classification. Class II (special controls). The guidance...

Total Beta-Adrenoceptor Knockout Slows Conduction and Reduces Inducible Arrhythmias in the Mouse Heart

PubMed Central

Stöckigt, Florian; Brixius, Klara; Lickfett, Lars; Andrié, René; Linhart, Markus; Nickenig, Georg; Schrickel, Jan Wilko

2012-01-01

Introduction Beta-adrenoceptors (β-AR) play an important role in the neurohumoral regulation of cardiac function. Three β-AR subtypes (β1, β2, β3) have been described so far. Total deficiency of these adrenoceptors (TKO) results in cardiac hypotrophy and negative inotropy. TKO represents a unique mouse model mimicking total unselective medical β-blocker therapy in men. Electrophysiological characteristics of TKO have not yet been investigated in an animal model. Methods In vivo electrophysiological studies using right heart catheterisation were performed in 10 TKO mice and 10 129SV wild type control mice (WT) at the age of 15 weeks. Standard surface ECG, intracardiac and electrophysiological parameters, and arrhythmia inducibility were analyzed. Results The surface ECG of TKO mice revealed a reduced heart rate (359.2±20.9 bpm vs. 461.1±33.3 bpm; p<0.001), prolonged P wave (17.5±3.0 ms vs. 15.1±1.2 ms; p = 0.019) and PQ time (40.8±2.4 ms vs. 37.3±3.0 ms; p = 0.013) compared to WT. Intracardiac ECG showed a significantly prolonged infra-Hisian conductance (HV-interval: 12.9±1.4 ms vs. 6.8±1.0 ms; p<0.001). Functional testing showed prolonged atrial and ventricular refractory periods in TKO (40.5±15.5 ms vs. 21.3±5.8 ms; p = 0.004; and 41.0±9.7 ms vs. 28.3±6.6 ms; p = 0.004, respectively). In TKO both the probability of induction of atrial fibrillation (12% vs. 24%; p<0.001) and of ventricular tachycardias (0% vs. 26%; p<0.001) were significantly reduced. Conclusion TKO results in significant prolongations of cardiac conduction times and refractory periods. This was accompanied by a highly significant reduction of atrial and ventricular arrhythmias. Our finding confirms the importance of β-AR in arrhythmogenesis and the potential role of unspecific beta-receptor-blockade as therapeutic target. PMID:23133676

Increased Short-Term Variability of the QT Interval in Professional Soccer Players: Possible Implications for Arrhythmia Prediction

PubMed Central

Lengyel, Csaba; Orosz, Andrea; Hegyi, Péter; Komka, Zsolt; Udvardy, Anna; Bosnyák, Edit; Trájer, Emese; Pavlik, Gábor; Tóth, Miklós; Wittmann, Tibor; Papp, Julius Gy.; Varró, András; Baczkó, István

2011-01-01

Background Sudden cardiac death in competitive athletes is rare but it is significantly more frequent than in the normal population. The exact cause is seldom established and is mostly attributed to ventricular fibrillation. Myocardial hypertrophy and slow heart rate, both characteristic changes in top athletes in response to physical conditioning, could be associated with increased propensity for ventricular arrhythmias. We investigated conventional ECG parameters and temporal short-term beat-to-beat variability of repolarization (STVQT), a presumptive novel parameter for arrhythmia prediction, in professional soccer players. Methods Five-minute 12-lead electrocardiograms were recorded from professional soccer players (n = 76, all males, age 22.0±0.61 years) and age-matched healthy volunteers who do not participate in competitive sports (n = 76, all males, age 22.0±0.54 years). The ECGs were digitized and evaluated off-line. The temporal instability of beat-to-beat heart rate and repolarization were characterized by the calculation of short-term variability of the RR and QT intervals. Results Heart rate was significantly lower in professional soccer players at rest (61±1.2 vs. 72±1.5/min in controls). The QT interval was prolonged in players at rest (419±3.1 vs. 390±3.6 in controls, p<0.001). QTc was significantly longer in players compared to controls calculated with Fridericia and Hodges correction formulas. Importantly, STVQT was significantly higher in players both at rest and immediately after the game compared to controls (4.8±0.14 and 4.3±0.14 vs. 3.5±0.10 ms, both p<0.001, respectively). Conclusions STVQT is significantly higher in professional soccer players compared to age-matched controls, however, further studies are needed to relate this finding to increased arrhythmia propensity in this population. PMID:21526208

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 �

Screening for sleep-related breathing disorders by transthoracic impedance recording integrated into a Holter ECG system.

PubMed

Mueller, Andreas; Fietze, Ingo; Voelker, Richard; Eddicks, Stephan; Glos, Martin; Baumann, Gert; Theres, Heinz

2006-12-01

In patients with arrhythmias, coincidence with sleep-related breathing disorders (SRBD) is high and of clinical relevance. Electrocardiogram-derived (ECG) parameters have been developed for SRBD screening, but it has proved necessary to exclude patients with frequent arrhythmias. Holter-based screening tools, easy to use, are therefore warranted. The goal of our study was to evaluate the diagnostic accuracy, with respect to SRBD detection, of transthoracic impedance recording (TTIR) integrated into a Holter System. Our investigation consisted of 2 phases. In phase 1 we compared the performance of TTIR to that of in-hospital polysomnography (PSG) in 56 patients (46 male, mean age 57). In phase 2 we compared TTIR to results from an ambulatory polygraphy (PG) system in 180 patients (143 male, mean age 56). We scored apnea and hypopnea from P(S)G, and derived a respiratory-disturbance index (P(S)G-RDI). TTIR was analyzed semi-automatically. Reduction of the impedance amplitude by more than 50% over 10 s was scored as apnea/hypopnea, with consequent calculation of TTIR-RDI. In phase 1, 20 out of 56 patients revealed a PSG-RDI > 10 h(-1). TTIR-RDI in 19 patients from this group was >10 h(-1) (sensitivity 95%, specificity 97.2%, positive predictive value 95%, negative predictive value 97.2%, interclass correlation coefficient 0.98). In phase 2, 46 of 180 patients revealed a PSG-RDI > 10 h(-1). TTIR-RDI in 37 out of this group was >10 h(-1) (sensitivity 80.4%, specificity 92.5%, positive predictive value 78.7%, negative predictive value 93.2%, interclass correlation coefficient 0.92). TTIR integrated into a Holter ECG system and tested in a large patient cohort demonstrates acceptable high accuracy in detection of SRBD. Arrhythmia analysis and screening for SRBD can be performed in a single-step approch.

Idiopathic accelerated idioventricular rhythm or ventricular tachycardia originating from the right bundle branch: unusual type of ventricular arrhythmia.

PubMed

Chen, Minglong; Gu, Kai; Yang, Bing; Chen, Hongwu; Ju, Weizhu; Zhang, Fengxiang; Yang, Gang; Li, Mingfang; Lu, Xinzheng; Cao, Kejiang; Ouyang, Feifan

2014-12-01

Accelerated idioventricular rhythm (AIVR) or ventricular tachycardia (VT) originating from the right bundle branch (RBB) is rare and published clinical data on such arrhythmia are scarce. In this study, we will describe the clinical manifestations, diagnosis, and management of a cohort of patients with this novel arrhythmia. Eight patients (5 men; median age, 25 years) with RBB-AIVR/VT were consecutively enrolled in the study. Pharmacological testing, exercise treadmill testing, electrophysiological study, and catheter ablation were performed in the study patients, and ECG features were characterized. All RBB-AIVR/VTs were of typical left bundle-branch block morphology with atrioventricular dissociation. The arrhythmias, which demonstrated chronotropic variability, were often isorhythmic with sinus rhythm and were accelerated by physical exercise, stress, and intravenous isoprenaline infusion. The rate of RBB-AIVR/VT varied from 45 to 200 beats per minute. Two patients experienced syncope, and 3 had impaired left ventricular function. Metoprolol was proven to be the most effective drug to decelerate the arrhythmia rate and relieve symptoms. Electrophysiology study was performed in 5 patients and the earliest activation with a sharp RBB potential was localized in the mid or distal RBB area. Catheter ablation terminated the arrhythmia with subsequent RBB block morphology during sinus rhythm. During follow-up, patients' symptoms were controlled with normalization of left ventricular function either on metoprolol or by catheter ablation. RBB-AIVR/VT is an unusual type of ventricular arrhythmia. It can result in significant symptoms and depressed ventricular function and can be successfully treated with catheter ablation. © 2014 American Heart Association, Inc.

About Arrhythmia

MedlinePlus

... may shut down or be damaged. View an animation of arrhythmia . Types of Arrhythmias Atrial Fibrillation = upper ... learn about: S tructure of the heart Watch an animation of heart valve anatomy The heart: four chambers, ...

Atrial arrhythmias after lung transplant: underlying mechanisms, risk factors, and prognosis.

PubMed

Orrego, Carlos M; Cordero-Reyes, Andrea M; Estep, Jerry D; Seethamraju, Harish; Scheinin, Scott; Loebe, Matthias; Torre-Amione, Guillermo

2014-07-01

Atrial arrhythmias (AAs) early after lung transplant are frequent and have a significant impact on morbidity and mortality. However, the pathogenesis of AAs after lung transplant remains incompletely understood. In this study we aimed to determine the prevalence of atrial fibrillation (AF) and other AAs, as well as risk factors, clinical outcomes and possible underlying mechanisms associated with AAs after lung transplant. A retrospective analysis was performed on 382 patients who underwent lung transplantation from 2000 to 2010. A 12-lead electrocardiogram (ECG) was obtained and AAs classified as AF and other AAs (atrial flutter [AFL] and supraventricular tachycardia [SVT]). Multivariate logistic regression analysis was performed to determine predictors, and Kaplan-Meier survival curves were constructed. The incidence of AAs was 25%; 17.8% developed AF and 7.6% other AAs (AFL/SVT). The major indication for transplant was idiopathic pulmonary fibrosis (IPF, 35%). Significant predictors of AF were as follows: age; IPF; left atrial enlargement; diastolic dysfunction; and history of coronary artery disease (CAD). Risk factors for other AAs (AFL/SVT) were: age; right ventricle dysfunction; right ventricular enlargement; and elevated right atrial pressure (RAP). One-year mortality was higher in the arrhythmia group (21.5% arrhythmia vs 15.7% no-arrhythmia group; p < 0.05). In addition, patients treated with anti-arrhythmic medications had higher mortality (p < 0.05). AAs are common after lung transplantation. Risk factors for developing either AF or other AAs (AFL/SVT) are different. The development of early AAs post-transplant is associated with prolonged post-operative stay and increased mortality. A rate-control strategy should be used as first-line therapy and anti-arrhythmic agents reserved for those patients who do not respond to the initial treatment. Copyright © 2014 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights

Energy-efficient ECG compression on wireless biosensors via minimal coherence sensing and weighted ℓ₁ minimization reconstruction.

PubMed

Zhang, Jun; Gu, Zhenghui; Yu, Zhu Liang; Li, Yuanqing

2015-03-01

Low energy consumption is crucial for body area networks (BANs). In BAN-enabled ECG monitoring, the continuous monitoring entails the need of the sensor nodes to transmit a huge data to the sink node, which leads to excessive energy consumption. To reduce airtime over energy-hungry wireless links, this paper presents an energy-efficient compressed sensing (CS)-based approach for on-node ECG compression. At first, an algorithm called minimal mutual coherence pursuit is proposed to construct sparse binary measurement matrices, which can be used to encode the ECG signals with superior performance and extremely low complexity. Second, in order to minimize the data rate required for faithful reconstruction, a weighted ℓ1 minimization model is derived by exploring the multisource prior knowledge in wavelet domain. Experimental results on MIT-BIH arrhythmia database reveals that the proposed approach can obtain higher compression ratio than the state-of-the-art CS-based methods. Together with its low encoding complexity, our approach can achieve significant energy saving in both encoding process and wireless transmission.

ECG compression using non-recursive wavelet transform with quality control

NASA Astrophysics Data System (ADS)

Liu, Je-Hung; Hung, King-Chu; Wu, Tsung-Ching

2016-09-01

While wavelet-based electrocardiogram (ECG) data compression using scalar quantisation (SQ) yields excellent compression performance, a wavelet's SQ scheme, however, must select a set of multilevel quantisers for each quantisation process. As a result of the properties of multiple-to-one mapping, however, this scheme is not conducive for reconstruction error control. In order to address this problem, this paper presents a single-variable control SQ scheme able to guarantee the reconstruction quality of wavelet-based ECG data compression. Based on the reversible round-off non-recursive discrete periodised wavelet transform (RRO-NRDPWT), the SQ scheme is derived with a three-stage design process that first uses genetic algorithm (GA) for high compression ratio (CR), followed by a quadratic curve fitting for linear distortion control, and the third uses a fuzzy decision-making for minimising data dependency effect and selecting the optimal SQ. The two databases, Physikalisch-Technische Bundesanstalt (PTB) and Massachusetts Institute of Technology (MIT) arrhythmia, are used to evaluate quality control performance. Experimental results show that the design method guarantees a high compression performance SQ scheme with statistically linear distortion. This property can be independent of training data and can facilitate rapid error control.

Effect of long-term application of Crataegus oxyacantha on ischemia and reperfusion induced arrhythmias in rats.

PubMed

Rothfuss, M A; Pascht, U; Kissling, G

2001-01-01

The effect of long-term application of Crataegus oxyacantha on ischemia and reperfusion induced arrhythmias was investigated in Wistar rats on the heart in situ and on Langendorff preparations. Seventeen rats were fed for 8 weeks with 0.5 g/kg b.w. Crataegus extract per day, standardised to 2.2% flavonoids. Twenty age-matched untreated rats served as controls. In the hearts in situ as well as in the Langendorff preparations the left anterior descending coronary artery (LAD) was ligated for 20 min and subsequently reperfused for 30 min. ECG was continuously recorded and the time spent between start of ischemia and onset of arrhythmias was measured. In addition, during ischemia and reperfusion the number of ventricular premature beats and bigemini and the duration of salvos and ventricular flutter and fibrillation were determined. The ischemic area was evaluated in all experiments and coronary flow was measured in Langendorff preparations. In the present experiments, no cardioprotective effects of Crataegus oxyacantha could be detected, neither in the heart in situ nor in the Langendorff preparations. Although the ischemic areas were identical, arrhythmias occurred even earlier in the Crataegus collectives than in the controls. Also the number and duration of ischemia and reperfusion induced arrhythmias tended to occur longer and more frequently in the Crataegus collectives, whilst coronary flow remained unchanged. The phenomenon that Crataegus rather aggravates than prevents arrhythmias may be reduced to a Crataegus induced increase in intracellular Ca(2+)-concentration proven true for the positive inotropic effects of Crataegus.

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

WaveformECG: A Platform for Visualizing, Annotating, and Analyzing ECG Data

PubMed Central

Winslow, Raimond L.; Granite, Stephen; Jurado, Christian

2017-01-01

The electrocardiogram (ECG) is the most commonly collected data in cardiovascular research because of the ease with which it can be measured and because changes in ECG waveforms reflect underlying aspects of heart disease. Accessed through a browser, WaveformECG is an open source platform supporting interactive analysis, visualization, and annotation of ECGs. PMID:28642673

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.

The cardiomyocyte molecular clock, regulation of Scn5a, and arrhythmia susceptibility

PubMed Central

Lefta, Mellani; Zhang, Xiping; Bartos, Daniel; Feng, Han-Zhong; Zhao, Yihua; Patwardhan, Abhijit; Jin, Jian-Ping; Esser, Karyn A.; Delisle, Brian P.

2013-01-01

The molecular clock mechanism underlies circadian rhythms and is defined by a transcription-translation feedback loop. Bmal1 encodes a core molecular clock transcription factor. Germline Bmal1 knockout mice show a loss of circadian variation in heart rate and blood pressure, and they develop dilated cardiomyopathy. We tested the role of the molecular clock in adult cardiomyocytes by generating mice that allow for the inducible cardiomyocyte-specific deletion of Bmal1 (iCSΔBmal1). ECG telemetry showed that cardiomyocyte-specific deletion of Bmal1 (iCSΔBmal1−/−) in adult mice slowed heart rate, prolonged RR and QRS intervals, and increased episodes of arrhythmia. Moreover, isolated iCSΔBmal1−/− hearts were more susceptible to arrhythmia during electromechanical stimulation. Examination of candidate cardiac ion channel genes showed that Scn5a, which encodes the principle cardiac voltage-gated Na+ channel (NaV1.5), was circadianly expressed in control mouse and rat hearts but not in iCSΔBmal1−/− hearts. In vitro studies confirmed circadian expression of a human Scn5a promoter-luciferase reporter construct and determined that overexpression of clock factors transactivated the Scn5a promoter. Loss of Scn5a circadian expression in iCSΔBmal1−/− hearts was associated with decreased levels of NaV1.5 and Na+ current in ventricular myocytes. We conclude that disruption of the molecular clock in the adult heart slows heart rate, increases arrhythmias, and decreases the functional expression of Scn5a. These findings suggest a potential link between environmental factors that alter the cardiomyocyte molecular clock and factors that influence arrhythmia susceptibility in humans. PMID:23364267

Fast clustering algorithm for large ECG data sets based on CS theory in combination with PCA and K-NN methods.

PubMed

Balouchestani, Mohammadreza; Krishnan, Sridhar

2014-01-01

Long-term recording of Electrocardiogram (ECG) signals plays an important role in health care systems for diagnostic and treatment purposes of heart diseases. Clustering and classification of collecting data are essential parts for detecting concealed information of P-QRS-T waves in the long-term ECG recording. Currently used algorithms do have their share of drawbacks: 1) clustering and classification cannot be done in real time; 2) they suffer from huge energy consumption and load of sampling. These drawbacks motivated us in developing novel optimized clustering algorithm which could easily scan large ECG datasets for establishing low power long-term ECG recording. In this paper, we present an advanced K-means clustering algorithm based on Compressed Sensing (CS) theory as a random sampling procedure. Then, two dimensionality reduction methods: Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) followed by sorting the data using the K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers are applied to the proposed algorithm. We show our algorithm based on PCA features in combination with K-NN classifier shows better performance than other methods. The proposed algorithm outperforms existing algorithms by increasing 11% classification accuracy. In addition, the proposed algorithm illustrates classification accuracy for K-NN and PNN classifiers, and a Receiver Operating Characteristics (ROC) area of 99.98%, 99.83%, and 99.75% respectively.

Cloud-ECG for real time ECG monitoring and analysis.

PubMed

Xia, Henian; Asif, Irfan; Zhao, Xiaopeng

2013-06-01

Recent advances in mobile technology and cloud computing have inspired numerous designs of cloud-based health care services and devices. Within the cloud system, medical data can be collected and transmitted automatically to medical professionals from anywhere and feedback can be returned to patients through the network. In this article, we developed a cloud-based system for clients with mobile devices or web browsers. Specially, we aim to address the issues regarding the usefulness of the ECG data collected from patients themselves. Algorithms for ECG enhancement, ECG quality evaluation and ECG parameters extraction were implemented in the system. The system was demonstrated by a use case, in which ECG data was uploaded to the web server from a mobile phone at a certain frequency and analysis was performed in real time using the server. The system has been proven to be functional, accurate and efficient. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Characteristics and circadian distribution of cardiac arrhythmias in patients with heart failure and sleep-disordered breathing.

PubMed

Omran, Hazem; Bitter, Thomas; Horstkotte, Dieter; Oldenburg, Olaf; Fox, Henrik

2018-05-08

Cardiac arrhythmias and sleep-disordered breathing (SDB) are common comorbidities in heart failure with reduced ejection fraction (HFrEF). However, understanding of the association between arrhythmias and SDB is poor. This study assessed the occurrence and circadian distribution of ventricular arrhythmias in HFrEF patients with and without SDB. This retrospective analysis included HFrEF patients admitted for unattended overnight cardiorespiratory polygraphy and 24-h Holter-ECG recording. Holter-ECG data (events/h) were categorized by time of day: morning, 06:00-13:59; afternoon, 14:00-21:59; nighttime, 22:00-05:59. Respiratory events were expressed using the apnea-hypopnea index (AHI) and an AHI ≥ 15/h was categorized as moderate to severe SDB. 167 patients were included (82% male, age 65 ± 10.4 years, left ventricular ejection fraction 30.9 ± 7.9%); SDB was predominantly central sleep apnea (CSA) in 45.5%, obstructive sleep apnea (OSA) in 23.9% or none/mild (nmSDB) in 17.4%. Morning premature ventricular contractions (PVCs) were detected significantly more frequently in CSA versus nmSDB patients (44.4/h versus 1.8/h; p = 0.02). Non-sustained VT was more frequent in patients with CSA versus versus OSA or nmSDB (17.9 versus 3.2 or 3.2%/h; p = 0.003 and p = 0.005, respectively). There was no significant variation in VT occurrence by time of day in HFrEF patients with CSA (p = 0.3). CSA was an independent predictor of VT occurrence in HFrEF in multivariate logistic regression analysis (odds ratio 4.1, 95% confidence interval 1.5-11.4, p = 0.007). CSA was associated with VT occurrence irrespective of sleep/wake status in HFrEF patients, and independently predicted the occurrence of VT. This association may contribute to chances by which CSA increases sudden death risk in HFrEF patients.

Frequency of exercise-induced ST-T-segment deviations and cardiac arrhythmias in recreational endurance athletes during a marathon race: results of the prospective observational Berlin Beat of Running study.

PubMed

Herm, Juliane; Töpper, Agnieszka; Wutzler, Alexander; Kunze, Claudia; Krüll, Matthias; Brechtel, Lars; Lock, Jürgen; Fiebach, Jochen B; Heuschmann, Peter U; Haverkamp, Wilhelm; Endres, Matthias; Jungehulsing, Gerhard Jan; Haeusler, Karl Georg

2017-08-03

While regular physical exercise has many health benefits, strenuous physical exercise may have a negative impact on cardiac function. The 'Berlin Beat of Running' study focused on feasibility and diagnostic value of continuous ECG monitoring in recreational endurance athletes during a marathon race. We hypothesised that cardiac arrhythmias and especially atrial fibrillation are frequently found in a cohort of recreational endurance athletes. The main secondary hypothesis was that pathological laboratory findings in these athletes are (in part) associated with cardiac arrhythmias. Prospective observational cohort study including healthy volunteers. One hundred and nine experienced marathon runners wore a portable ECG recorder during a marathon race in Berlin, Germany. Athletes underwent blood tests 2-3 days prior, directly after and 1-2 days after the race. Overall, 108 athletes (median 48 years (IQR 45-53), 24% women) completed the marathon in 249±43 min. Blinded ECG analysis revealed abnormal findings during the marathon in 18 (16.8%) athletes. Ten (9.3%) athletes had at least one episode of non-sustained ventricular tachycardia, one of whom had atrial fibrillation; eight (7.5%) individuals showed transient ST-T-segment deviations. Abnormal ECG findings were associated with advanced age (OR 1.11 per year, 95% CI 1.01 to 1.23), while sex and cardiovascular risk profile had no impact. Directly after the race, high-sensitive troponin T was elevated in 18 (16.7%) athletes and associated with ST-T-segment deviation (OR 9.9, 95% CI 1.9 to 51.5), while age, sex and cardiovascular risk profile had no impact. ECG monitoring during a marathon is feasible. Abnormal ECG findings were present in every sixth athlete. Exercise-induced transient ST-T-segment deviations were associated with elevated high-sensitive troponin T (hsTnT) values. ClinicalTrials.gov NCT01428778; Results. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article

Frequency of exercise-induced ST-T-segment deviations and cardiac arrhythmias in recreational endurance athletes during a marathon race: results of the prospective observational Berlin Beat of Running study

PubMed Central

Herm, Juliane; Töpper, Agnieszka; Wutzler, Alexander; Kunze, Claudia; Krüll, Matthias; Brechtel, Lars; Lock, Jürgen; Fiebach, Jochen B; Heuschmann, Peter U; Haverkamp, Wilhelm; Endres, Matthias; Jungehulsing, Gerhard Jan; Haeusler, Karl Georg

2017-01-01

Objectives While regular physical exercise has many health benefits, strenuous physical exercise may have a negative impact on cardiac function. The ‘Berlin Beat of Running’ study focused on feasibility and diagnostic value of continuous ECG monitoring in recreational endurance athletes during a marathon race. We hypothesised that cardiac arrhythmias and especially atrial fibrillation are frequently found in a cohort of recreational endurance athletes. The main secondary hypothesis was that pathological laboratory findings in these athletes are (in part) associated with cardiac arrhythmias. Design Prospective observational cohort study including healthy volunteers. Setting and participants One hundred and nine experienced marathon runners wore a portable ECG recorder during a marathon race in Berlin, Germany. Athletes underwent blood tests 2–3 days prior, directly after and 1–2 days after the race. Results Overall, 108 athletes (median 48 years (IQR 45–53), 24% women) completed the marathon in 249±43 min. Blinded ECG analysis revealed abnormal findings during the marathon in 18 (16.8%) athletes. Ten (9.3%) athletes had at least one episode of non-sustained ventricular tachycardia, one of whom had atrial fibrillation; eight (7.5%) individuals showed transient ST-T-segment deviations. Abnormal ECG findings were associated with advanced age (OR 1.11 per year, 95% CI 1.01 to 1.23), while sex and cardiovascular risk profile had no impact. Directly after the race, high-sensitive troponin T was elevated in 18 (16.7%) athletes and associated with ST-T-segment deviation (OR 9.9, 95% CI 1.9 to 51.5), while age, sex and cardiovascular risk profile had no impact. Conclusions ECG monitoring during a marathon is feasible. Abnormal ECG findings were present in every sixth athlete. Exercise-induced transient ST-T-segment deviations were associated with elevated high-sensitive troponin T (hsTnT) values. Trial registration ClinicalTrials.gov NCT01428778; Results. PMID

Algorithms Based on CWT and Classifiers to Control Cardiac Alterations and Stress Using an ECG and a SCR

PubMed Central

Villarejo, María Viqueira; Zapirain, Begoña García; Zorrilla, Amaia Méndez

2013-01-01

This paper presents the results of using a commercial pulsimeter as an electrocardiogram (ECG) for wireless detection of cardiac alterations and stress levels for home control. For these purposes, signal processing techniques (Continuous Wavelet Transform (CWT) and J48) have been used, respectively. The designed algorithm analyses the ECG signal and is able to detect the heart rate (99.42%), arrhythmia (93.48%) and extrasystoles (99.29%). The detection of stress level is complemented with Skin Conductance Response (SCR), whose success is 94.02%. The heart rate variability does not show added value to the stress detection in this case. With this pulsimeter, it is possible to prevent and detect anomalies for a non-intrusive way associated to a telemedicine system. It is also possible to use it during physical activity due to the fact the CWT minimizes the motion artifacts. PMID:23666135

Algorithms based on CWT and classifiers to control cardiac alterations and stress using an ECG and a SCR.

PubMed

Villarejo, María Viqueira; Zapirain, Begoña García; Zorrilla, Amaia Méndez

2013-05-10

This paper presents the results of using a commercial pulsimeter as an electrocardiogram (ECG) for wireless detection of cardiac alterations and stress levels for home control. For these purposes, signal processing techniques (Continuous Wavelet Transform (CWT) and J48) have been used, respectively. The designed algorithm analyses the ECG signal and is able to detect the heart rate (99.42%), arrhythmia (93.48%) and extrasystoles (99.29%). The detection of stress level is complemented with Skin Conductance Response (SCR), whose success is 94.02%. The heart rate variability does not show added value to the stress detection in this case. With this pulsimeter, it is possible to prevent and detect anomalies for a non-intrusive way associated to a telemedicine system. It is also possible to use it during physical activity due to the fact the CWT minimizes the motion artifacts.

Optimisation of Embryonic and Larval ECG Measurement in Zebrafish for Quantifying the Effect of QT Prolonging Drugs

PubMed Central

Dhillon, Sundeep Singh; Dóró, Éva; Magyary, István; Egginton, Stuart; Sík, Attila; Müller, Ferenc

2013-01-01

Effective chemical compound toxicity screening is of paramount importance for safe cardiac drug development. Using mammals in preliminary screening for detection of cardiac dysfunction by electrocardiography (ECG) is costly and requires a large number of animals. Alternatively, zebrafish embryos can be used as the ECG waveform is similar to mammals, a minimal amount of chemical is necessary for drug testing, while embryos are abundant, inexpensive and represent replacement in animal research with reduced bioethical concerns. We demonstrate here the utility of pre-feeding stage zebrafish larvae in detection of cardiac dysfunction by electrocardiography. We have optimised an ECG recording system by addressing key parameters such as the form of immobilization, recording temperature, electrode positioning and developmental age. Furthermore, analysis of 3 days post fertilization (dpf) zebrafish embryos treated with known QT prolonging drugs such as terfenadine, verapamil and haloperidol led to reproducible detection of QT prolongation as previously shown for adult zebrafish. In addition, calculation of Z-factor scores revealed that the assay was sensitive and specific enough to detect large drug-induced changes in QTc intervals. Thus, the ECG recording system is a useful drug-screening tool to detect alteration to cardiac cycle components and secondary effects such as heart block and arrhythmias in zebrafish larvae before free feeding stage, and thus provides a suitable replacement for mammalian experimentation. PMID:23579446

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.

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

PubMed

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

2018-01-29

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

Extrasystoles: side effect of kangaroo care?

PubMed

Kluthe, Christof; Wauer, Roland R; Rüdiger, Mario

2004-09-01

To present an unpublished reason for an arrhythmic electrocardiogram (ECG) recording during kangaroo care in a preterm infant. Case report. Preterm infant. A preterm infant exhibited cardiac arrhythmia on the ECG monitor during kangaroo care, leading to interruption of kangarooing. Arrhythmia disappeared after placing the baby back into the incubator. The most likely reasons for arrhythmia were excluded. However, arrhythmia reappeared upon continuation of kangaroo care. ECG monitoring revealed the reason for the monitoring error. ECG monitoring during kangaroo care should cause error because of superimposed electric activity from the parent. Oxygen saturation represents a more reliable method of monitoring during kangaroo care.

Arrhythmias in Adults with Congenital Heart Disease: What Are Risk Factors for Specific Arrhythmias?

PubMed

Loomba, Rohit S; Buelow, Matthew W; Aggarwal, Saurabh; Arora, Rohit R; Kovach, Joshua; Ginde, Salil

2017-04-01

An increasing number of patients with congenital heart disease are now surviving into adulthood. This has also led to the emergence of complications from the underlying congenital heart disease, related surgical interventions, and associated combordities. While the prevalence of particular arrhythmias with specific congenital heart disease has been previously described, a detailed analysis of all lesions and a large number of comorbidities has not been previously published. Admissions with congenital heart disease were identified in the National Inpatient Sample. Associated comorbidities were also identified for these patients. Univariate analysis was done to compare those risk factors associated with specific arrhythmias in the setting of congenital heart disease. Next, regression analysis was done to identify what patient characteristics and comorbidities were associated with increased risk of specific arrhythmias. A total of 52,725,227 admissions were included in the analysis. Of these, 109,168 (0.21%) had congenital heart disease. Of those with congenital heart disease, 27,088 (25%) had an arrhythmia at some point. The most common arrhythmia in those with congenital heart disease was atrial fibrillation, which was noted in 86% of those with arrhythmia followed by atrial flutter which was noted in 20% of those with congenital heart disease. The largest burden of arrhythmia was found to be in those with tricuspid atresia with a 51% prevalence of arrhythmia in this group followed by Ebstein anomaly which had an arrhythmia prevalence of 39%. Increasing age, male gender, double outlet right ventricle, atrioventricular septal defect, heart failure, obstructive sleep apnea, transposition of the great arteries, congenitally corrected transposition, and tetralogy of Fallot were frequently noted to be independent risk factors of specific arrhythmias. Approximately, 25% of adult admissions with congenital heart disease are associated with arrhythmia. The burden of

Use of self-gated radial cardiovascular magnetic resonance to detect and classify arrhythmias (atrial fibrillation and premature ventricular contraction).

PubMed

Piekarski, Eve; Chitiboi, Teodora; Ramb, Rebecca; Feng, Li; Axel, Leon

2016-11-25

Arrhythmia can significantly alter the image quality of cardiovascular magnetic resonance (CMR); automatic detection and sorting of the most frequent types of arrhythmias during the CMR acquisition could potentially improve image quality. New CMR techniques, such as non-Cartesian CMR, can allow self-gating: from cardiac motion-related signal changes, we can detect cardiac cycles without an electrocardiogram. We can further use this data to obtain a surrogate for RR intervals (valley intervals: VV). Our purpose was to evaluate the feasibility of an automated method for classification of non-arrhythmic (NA) (regular cycles) and arrhythmic patients (A) (irregular cycles), and for sorting of common arrhythmia patterns between atrial fibrillation (AF) and premature ventricular contraction (PVC), using the cardiac motion-related signal obtained during self-gated free-breathing radial cardiac cine CMR with compressed sensing reconstruction (XD-GRASP). One hundred eleven patients underwent cardiac XD-GRASP CMR between October 2015 and February 2016; 33 were included for retrospective analysis with the proposed method (6 AF, 8 PVC, 19 NA; by recent ECG). We analyzed the VV, using pooled statistics (histograms) and sequential analysis (Poincaré plots), including the median (medVV), the weighted mean (meanVV), the total number of VV values (VVval), and the total range (VVTR) and half range (VVHR) of the cumulative frequency distribution of VV, including the median to half range (medVV/VVHR) and the half range to total range (VVHR/VVTR) ratios. We designed a simple algorithm for using the VV results to differentiate A from NA, and AF from PVC. Between NA and A, meanVV, VVval, VVTR, VVHR, medVV/VVHR and VVHR/VVTR ratios were significantly different (p values = 0.00014, 0.0027, 0.000028, 5×10 -9 , 0.002, respectively). Between AF and PVC, meanVV, VVval and medVV/VVHR ratio were significantly different (p values = 0.018, 0.007, 0.044, respectively). Using our algorithm

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

PubMed

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

2014-01-01

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

Reconstruction of ECG signals in presence of corruption.

PubMed

Ganeshapillai, Gartheeban; Liu, Jessica F; Guttag, John

2011-01-01

We present an approach to identifying and reconstructing corrupted regions in a multi-parameter physiological signal. The method, which uses information in correlated signals, is specifically designed to preserve clinically significant aspects of the signals. We use template matching to jointly segment the multi-parameter signal, morphological dissimilarity to estimate the quality of the signal segment, similarity search using features on a database of templates to find the closest match, and time-warping to reconstruct the corrupted segment with the matching template. In experiments carried out on the MIT-BIH Arrhythmia Database, a two-parameter database with many clinically significant arrhythmias, our method improved the classification accuracy of the beat type by more than 7 times on a signal corrupted with white Gaussian noise, and increased the similarity to the original signal, as measured by the normalized residual distance, by more than 2.5 times.

The effect of Cardiac Arrhythmias Simulation Software on the nurses' learning and professional development.

PubMed

Bazrafkan, Leila; Hemmati, Mehdi

2018-04-01

One of the important tasks of nurses in intensive care unit is interpretation of ECG. The use of training simulator is a new paradigm in the age of computers. This study was performed to evaluate the impact of cardiac arrhythmias simulator software on nurses' learning in the subspecialty Vali-Asr Hospital in 2016. This study was conducted by quasi-experimental randomized Salomon four group design with the participation of 120 nurses in subspecialty Vali-Asr Hospital in Tehran, Iran in 2016 that were selected purposefully and allocated in 4 groups. By this design other confounding factors such as the prior information, maturation and the role of sex and age were controlled by Solomon 4 design. The valid and reliable multiple choice test tools were used to gather information; the validity of the test was approved by experts and its reliability was obtained by Cronbach's alpha coefficient 0.89. At first, the knowledge and skills of the participants were assessed by a pre-test; following the educational intervention with cardiac arrhythmias simulator software during 14 days in ICUs, the mentioned factors were measured for the two groups again by a post-test in the four groups. Data were analyzed using the two way ANOVA. The significance level was considered as p<0.05. Based on randomized four-group Solomon designs and our test results, using cardiac arrhythmias simulator software as an intervention was effective in the nurses' learning since a significant difference was found between pre-test and post-test in the first group (p<0.05). Also, other comparisons by ANOVA test showed that there was no interaction between pre-test and intervention in all of the three knowledge areas of cardiac arrhythmias, their treatments and their diagnosis (P>0.05). The use of software-based simulator for cardiac arrhythmias was effective in nurses' learning in light of its attractive components and interactive method. This intervention increased the knowledge of the nurses in cognitive

A cancelable biometric scheme based on multi-lead ECGs.

PubMed

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

2017-07-01

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

Diagnostic accuracy of a smartphone electrocardiograph in dogs: Comparison with standard 6-lead electrocardiography.

PubMed

Vezzosi, T; Buralli, C; Marchesotti, F; Porporato, F; Tognetti, R; Zini, E; Domenech, O

2016-10-01

The diagnostic accuracy of a smartphone electrocardiograph (ECG) in evaluating heart rhythm and ECG measurements was evaluated in 166 dogs. A standard 6-lead ECG was acquired for 1 min in each dog. A smartphone ECG tracing was simultaneously recorded using a single-lead bipolar ECG recorder. All ECGs were reviewed by one blinded operator, who judged if tracings were acceptable for interpretation and assigned an electrocardiographic diagnosis. Agreement between smartphone and standard ECG in the interpretation of tracings was evaluated. Sensitivity and specificity for the detection of arrhythmia were calculated for the smartphone ECG. Smartphone ECG tracings were interpretable in 162/166 (97.6%) tracings. A perfect agreement between the smartphone and standard ECG was found in detecting bradycardia, tachycardia, ectopic beats and atrioventricular blocks. A very good agreement was found in detecting sinus rhythm versus non-sinus rhythm (100% sensitivity and 97.9% specificity). The smartphone ECG provided tracings that were adequate for analysis in most dogs, with an accurate assessment of heart rate, rhythm and common arrhythmias. The smartphone ECG represents an additional tool in the diagnosis of arrhythmias in dogs, but is not a substitute for a 6-lead ECG. Arrhythmias identified by the smartphone ECG should be followed up with a standard ECG before making clinical decisions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prevention and Treatment of Arrhythmia

MedlinePlus

... your pulse – especially if you have an artificial pacemaker. Put the second and third fingers of one ... Ablation Devices for Arrhythmia - Implantable Cardioverter Defibrillator (ICD) - Pacemaker Treating Arrhythmias in Children • Arrhythmia Tools & Resources Watch, ...

Machine learning on-a-chip: a high-performance low-power reusable neuron architecture for artificial neural networks in ECG classifications.

PubMed

Sun, Yuwen; Cheng, Allen C

2012-07-01

Artificial neural networks (ANNs) are a promising machine learning technique in classifying non-linear electrocardiogram (ECG) signals and recognizing abnormal patterns suggesting risks of cardiovascular diseases (CVDs). In this paper, we propose a new reusable neuron architecture (RNA) enabling a performance-efficient and cost-effective silicon implementation for ANN. The RNA architecture consists of a single layer of physical RNA neurons, each of which is designed to use minimal hardware resource (e.g., a single 2-input multiplier-accumulator is used to compute the dot product of two vectors). By carefully applying the principal of time sharing, RNA can multiplexs this single layer of physical neurons to efficiently execute both feed-forward and back-propagation computations of an ANN while conserving the area and reducing the power dissipation of the silicon. A three-layer 51-30-12 ANN is implemented in RNA to perform the ECG classification for CVD detection. This RNA hardware also allows on-chip automatic training update. A quantitative design space exploration in area, power dissipation, and execution speed between RNA and three other implementations representative of different reusable hardware strategies is presented and discussed. Compared with an equivalent software implementation in C executed on an embedded microprocessor, the RNA ASIC achieves three orders of magnitude improvements in both the execution speed and the energy efficiency. Copyright © 2012 Elsevier Ltd. All rights reserved.

Does Deep Bradycardia Increase the Risk of Arrhythmias and Syncope in Endurance Athletes?

PubMed

Matelot, D; Schnell, F; Khodor, N; Endjah, N; Kervio, G; Carrault, G; Thillaye du Boullay, N; Carre, F

2016-09-01

The aim of this study was to evaluate whether endurance athletes who exhibit deep bradycardia are more prone to arrhythmias and reflex syncope than their non-bradycardic peers. 46 healthy men (ages 19-35) were divided into 3 groups based on whether they were sedentary (SED,<2 h/week) or endurance trained (ET,>6 h/week), and non-bradycardic (NB, resting heart rate (HR)≥60 bpm) or bradycardic (B, resting HR<50 bpm). Resting HR was lower in ETB vs. ETNB and SED (43.8±3.1, 61.3±3.3, 66.1±5.9 bpm, respectively; p<0.001). Thus, 16 SED, 13 ETNB and 17 ETB underwent resting echocardiography, maximal exercise test, tilt test (TT) and 24 h-Holter ECG. Subjects were followed-up during 4.7±1.1 years for training, syncope and cardiac events. Our results showed that incidence of arrhythmias and hypotensive susceptibility did not differ between groups. During follow-up, no episode of syncope or near-syncope was reported. However, cardio-inhibitory syncope occurrence tended to be higher in ETB. Left ventricular end-diastolic diameter index was increased in ETB vs. ETNB and was correlated with resting HR (r=- 0.64; p<0.001). As a result, athletes with deep bradycardia do not present more arrhythmias and more hypotensive susceptibility than their non-bradycardic peers. Cardiac enlargement and autonomic alteration both seem to be involved in an athlete's bradycardia. © Georg Thieme Verlag KG Stuttgart · New York.

Signal processing using sparse derivatives with applications to chromatograms and ECG

NASA Astrophysics Data System (ADS)

Ning, Xiaoran

In this thesis, we investigate the sparsity exist in the derivative domain. Particularly, we focus on the type of signals which posses up to Mth (M > 0) order sparse derivatives. Efforts are put on formulating proper penalty functions and optimization problems to capture properties related to sparse derivatives, searching for fast, computationally efficient solvers. Also the effectiveness of these algorithms are applied to two real world applications. In the first application, we provide an algorithm which jointly addresses the problems of chromatogram baseline correction and noise reduction. The series of chromatogram peaks are modeled as sparse with sparse derivatives, and the baseline is modeled as a low-pass signal. A convex optimization problem is formulated so as to encapsulate these non-parametric models. To account for the positivity of chromatogram peaks, an asymmetric penalty function is also utilized with symmetric penalty functions. A robust, computationally efficient, iterative algorithm is developed that is guaranteed to converge to the unique optimal solution. The approach, termed Baseline Estimation And Denoising with Sparsity (BEADS), is evaluated and compared with two state-of-the-art methods using both simulated and real chromatogram data. Promising result is obtained. In the second application, a novel Electrocardiography (ECG) enhancement algorithm is designed also based on sparse derivatives. In the real medical environment, ECG signals are often contaminated by various kinds of noise or artifacts, for example, morphological changes due to motion artifact, non-stationary noise due to muscular contraction (EMG), etc. Some of these contaminations severely affect the usefulness of ECG signals, especially when computer aided algorithms are utilized. By solving the proposed convex l1 optimization problem, artifacts are reduced by modeling the clean ECG signal as a sum of two signals whose second and third-order derivatives (differences) are sparse

Spatiotemporal Permutation Entropy as a Measure for Complexity of Cardiac Arrhythmia

NASA Astrophysics Data System (ADS)

Schlemmer, Alexander; Berg, Sebastian; Lilienkamp, Thomas; Luther, Stefan; Parlitz, Ulrich

2018-05-01

Permutation entropy (PE) is a robust quantity for measuring the complexity of time series. In the cardiac community it is predominantly used in the context of electrocardiogram (ECG) signal analysis for diagnoses and predictions with a major application found in heart rate variability parameters. In this article we are combining spatial and temporal PE to form a spatiotemporal PE that captures both, complexity of spatial structures and temporal complexity at the same time. We demonstrate that the spatiotemporal PE (STPE) quantifies complexity using two datasets from simulated cardiac arrhythmia and compare it to phase singularity analysis and spatial PE (SPE). These datasets simulate ventricular fibrillation (VF) on a two-dimensional and a three-dimensional medium using the Fenton-Karma model. We show that SPE and STPE are robust against noise and demonstrate its usefulness for extracting complexity features at different spatial scales.

PDF-ECG in clinical practice: A model for long-term preservation of digital 12-lead ECG data.

PubMed

Sassi, Roberto; Bond, Raymond R; Cairns, Andrew; Finlay, Dewar D; Guldenring, Daniel; Libretti, Guido; Isola, Lamberto; Vaglio, Martino; Poeta, Roberto; Campana, Marco; Cuccia, Claudio; Badilini, Fabio

In clinical practice, data archiving of resting 12-lead electrocardiograms (ECGs) is mainly achieved by storing a PDF report in the hospital electronic health record (EHR). When available, digital ECG source data (raw samples) are only retained within the ECG management system. The widespread availability of the ECG source data would undoubtedly permit successive analysis and facilitate longitudinal studies, with both scientific and diagnostic benefits. PDF-ECG is a hybrid archival format which allows to store in the same file both the standard graphical report of an ECG together with its source ECG data (waveforms). Using PDF-ECG as a model to address the challenge of ECG data portability, long-term archiving and documentation, a real-world proof-of-concept test was conducted in a northern Italy hospital. A set of volunteers undertook a basic ECG using routine hospital equipment and the source data captured. Using dedicated web services, PDF-ECG documents were then generated and seamlessly uploaded in the hospital EHR, replacing the standard PDF reports automatically generated at the time of acquisition. Finally, the PDF-ECG files could be successfully retrieved and re-analyzed. Adding PDF-ECG to an existing EHR had a minimal impact on the hospital's workflow, while preserving the ECG digital data. Copyright © 2017 Elsevier Inc. All rights reserved.

Sleep versus wake classification from heart rate variability using computational intelligence: consideration of rejection in classification models.

PubMed

Lewicke, Aaron; Sazonov, Edward; Corwin, Michael J; Neuman, Michael; Schuckers, Stephanie

2008-01-01

Reliability of classification performance is important for many biomedical applications. A classification model which considers reliability in the development of the model such that unreliable segments are rejected would be useful, particularly, in large biomedical data sets. This approach is demonstrated in the development of a technique to reliably determine sleep and wake using only the electrocardiogram (ECG) of infants. Typically, sleep state scoring is a time consuming task in which sleep states are manually derived from many physiological signals. The method was tested with simultaneous 8-h ECG and polysomnogram (PSG) determined sleep scores from 190 infants enrolled in the collaborative home infant monitoring evaluation (CHIME) study. Learning vector quantization (LVQ) neural network, multilayer perceptron (MLP) neural network, and support vector machines (SVMs) are tested as the classifiers. After systematic rejection of difficult to classify segments, the models can achieve 85%-87% correct classification while rejecting only 30% of the data. This corresponds to a Kappa statistic of 0.65-0.68. With rejection, accuracy improves by about 8% over a model without rejection. Additionally, the impact of the PSG scored indeterminate state epochs is analyzed. The advantages of a reliable sleep/wake classifier based only on ECG include high accuracy, simplicity of use, and low intrusiveness. Reliability of the classification can be built directly in the model, such that unreliable segments are rejected.

Sports and arrhythmias: a report of the International Workshop Venice Arrhythmias 2009.

PubMed

Giada, Franco; Biffi, Alessandro; Cannom, David S; Cappato, Riccardo; Capucci, Alessandro; Corrado, Domenico; Delise, Pietro; Drezner, Jonathan A; El-Sherif, Nabil; Estes, Mark; Furlanello, Francesco; Heidbuchel, Hein; Inama, Giuseppe; Lindsay, Bruce D; Maron, Barry J; Maron, Martin S; Mont, Luis; Olshansky, Brian; Pelliccia, Antonio; Thiene, Gaetano; Viskin, Sami; Zeppilli, Paolo; Natale, Andrea; Raviele, Antonio

2010-10-01

This article is a report of an international symposium, endorsed by the Section on Sports Cardiology of the European Association for Cardiovascular Prevention and Rehabilitation, the Italian Society of Sports Cardiology, and the Italian Federation of Sports Medicine, which was held within the 11th International Workshop on Cardiac Arrhythmias (Venice Arrhythmias 2009, Venice, Italy, October 2009). The following main topics were discussed during the symposium: the role of novel diagnostic examinations to assess the risk of sudden death in athletes, controversies on arrhythmic risk evaluation in athletes, controversies on the relationship between sports and arrhythmias, and controversies on antiarrhythmic treatment in athletes.

Hybrid method based on singular value decomposition and embedded zero tree wavelet technique for ECG signal compression.

PubMed

Kumar, Ranjeet; Kumar, A; Singh, G K

2016-06-01

In the field of biomedical, it becomes necessary to reduce data quantity due to the limitation of storage in real-time ambulatory system and telemedicine system. Research has been underway since very beginning for the development of an efficient and simple technique for longer term benefits. This paper, presents an algorithm based on singular value decomposition (SVD), and embedded zero tree wavelet (EZW) techniques for ECG signal compression which deals with the huge data of ambulatory system. The proposed method utilizes the low rank matrix for initial compression on two dimensional (2-D) ECG data array using SVD, and then EZW is initiated for final compression. Initially, 2-D array construction has key issue for the proposed technique in pre-processing. Here, three different beat segmentation approaches have been exploited for 2-D array construction using segmented beat alignment with exploitation of beat correlation. The proposed algorithm has been tested on MIT-BIH arrhythmia record, and it was found that it is very efficient in compression of different types of ECG signal with lower signal distortion based on different fidelity assessments. The evaluation results illustrate that the proposed algorithm has achieved the compression ratio of 24.25:1 with excellent quality of signal reconstruction in terms of percentage-root-mean square difference (PRD) as 1.89% for ECG signal Rec. 100 and consumes only 162bps data instead of 3960bps uncompressed data. The proposed method is efficient and flexible with different types of ECG signal for compression, and controls quality of reconstruction. Simulated results are clearly illustrate the proposed method can play a big role to save the memory space of health data centres as well as save the bandwidth in telemedicine based healthcare systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Differentiating the origin of outflow tract ventricular arrhythmia using a simple, novel approach.

PubMed

Efimova, Elena; Dinov, Borislav; Acou, Willem-Jan; Schirripa, Valentina; Kornej, Jelena; Kosiuk, Jedrzej; Rolf, Sascha; Sommer, Philipp; Richter, Sergio; Bollmann, Andreas; Hindricks, Gerhard; Arya, Arash

2015-07-01

Numerous electrocardiographic (ECG) criteria have been proposed to identify localization of outflow tract ventricular arrhythmias (OT-VAs); however, in some cases, it is difficult to accurately localize the origin of OT-VA using the surface ECG. The purpose of this study was to assess a simple criterion for localization of OT-VAs during electrophysiology study. We measured the interval from the onset of the earliest QRS complex of premature ventricular contractions (PVCs) to the distal right ventricular apical signal (the QRS-RVA interval) in 66 patients (31 men aged 53.3 ± 14.0 years; right ventricular outflow tract [RVOT] origin in 37) referred for ablation of symptomatic outflow tract PVCs. We prospectively validated this criterion in 39 patients (22 men aged 52 ± 15 years; RVOT origin in 19). Compared with patients with RVOT PVCs, the QRS-RVA interval was significantly longer in patients with left ventricular outflow tract (LVOT) PVCs (70 ± 14 vs 33.4±10 ms, P < .001). Receiver operating characteristic analysis showed that a QRS-RVA interval ≥49 ms had sensitivity, specificity, and positive and negative predictive values of 100%, 94.6%, 93.5%, and 100%, respectively, for prediction of an LVOT origin. The same analysis in the validation cohort showed sensitivity, specificity, and positive and negative predictive values of 94.7%, 95%, 95%, and 94.7%, respectively. When these data were combined, a QRS-RVA interval ≥49 ms had sensitivity, specificity, and positive and negative predictive values of 98%, 94.6%, 94.1%, and 98.1%, respectively, for prediction of an LVOT origin. A QRS-RVA interval ≥49 ms suggests an LVOT origin. The QRS-RVA interval is a simple and accurate criterion for differentiating the origin of outflow tract arrhythmia during electrophysiology study; however, the accuracy of this criterion in identifying OT-VA from the right coronary cusp is limited. Copyright © 2015 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Sequential Markov chain Monte Carlo filter with simultaneous model selection for electrocardiogram signal modeling.

PubMed

Edla, Shwetha; Kovvali, Narayan; Papandreou-Suppappola, Antonia

2012-01-01

Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can be used for automated disease classification, is of great importance in precluding manual annotation and providing prompt diagnosis of cardiac diseases. ECG signals consist of several segments with different morphologies (namely the P wave, QRS complex and the T wave) in a single heart beat, which can vary across individuals and diseases. Also, existing statistical ECG models exhibit a reliance upon obtaining a priori information from the ECG data by using preprocessing algorithms to initialize the filter parameters, or to define the user-specified model parameters. In this paper, we propose an ECG modeling technique using the sequential Markov chain Monte Carlo (SMCMC) filter that can perform simultaneous model selection, by adaptively choosing from different representations depending upon the nature of the data. Our results demonstrate the ability of the algorithm to track various types of ECG morphologies, including intermittently occurring ECG beats. In addition, we use the estimated model parameters as the feature set to classify between ECG signals with normal sinus rhythm and four different types of arrhythmia.

Arrhythmias

MedlinePlus

... sign of other heart problems, or an immediate danger to your health. ... patient with suspected arrhythmia. In: Goldman L, Schafer AI, eds. Goldman’s Cecil Medicine . 25th ed. Philadelphia, PA: ...

Myocardial deletion of transcription factor CHF1/Hey2 results in altered myocyte action potential and mild conduction system expansion but does not alter conduction system function or promote spontaneous arrhythmias.

PubMed

Hartman, Matthew E; Liu, Yonggang; Zhu, Wei-Zhong; Chien, Wei-Ming; Weldy, Chad S; Fishman, Glenn I; Laflamme, Michael A; Chin, Michael T

2014-07-01

CHF1/Hey2 is a Notch-responsive basic helix-loop-helix transcription factor involved in cardiac development. Common variants in Hey2 are associated with Brugada syndrome. We hypothesized that absence of CHF1/Hey2 would result in abnormal cellular electrical activity, altered cardiac conduction system (CCS) development, and increased arrhythmogenesis. We isolated neonatal CHF/Hey2-knockout (KO) cardiac myocytes and measured action potentials and ion channel subunit gene expression. We also crossed myocardial-specific CHF1/Hey2-KO mice with cardiac conduction system LacZ reporter mice and stained for conduction system tissue. We also performed ambulatory ECG monitoring for arrhythmias and heart rate variability. Neonatal cardiomyocytes from CHF1/Hey2-KO mice demonstrate a 50% reduction in action potential dV/dT, a 50-75% reduction in SCN5A, KCNJ2, and CACNA1C ion channel subunit gene expression, and an increase in delayed afterdepolarizations from 0/min to 12/min. CHF1/Hey2 cKO CCS-lacZ mice have a ∼3-fold increase in amount of CCS tissue. Ambulatory ECG monitoring showed no difference in cardiac conduction, arrhythmias, or heart rate variability. Wild-type cells or animals were used in all experiments. CHF1/Hey2 may contribute to Brugada syndrome by influencing the expression of SCN5A and formation of the cardiac conduction system, but its absence does not cause baseline conduction defects or arrhythmias in the adult mouse.-Hartman, M. E., Liu, Y., Zhu, W.-Z., Chien, W.-M., Weldy, C. S., Fishman, G. I., Laflamme, M. A., Chin, M. T. Myocardial deletion of transcription factor CHF1/Hey2 results in altered myocyte action potential and mild conduction system expansion but does not alter conduction system function or promote spontaneous arrhythmias. © FASEB.

ECG Changes in Young Healthy Smokers: A Simple and Cost-Effective Method to Assess Cardiovascular Risk According to Pack-Years of Smoking.

PubMed

Sharma, Nirmal Kumar; Jaiswal, Kapil Kumar; Meena, S R; Chandel, Rahul; Chittora, Saurabh; Goga, Prem Singh; Harish, H B; Sagar, Rajesh

2017-06-01

To document the prevalence of ECG abnormalities in young healthy smokers and compare ECG changes in smokers, young healthy non-smokers and amongst smokers with different pack years. This was a prospective case-control study consisting of 200 young healthy male and female individuals, 150 smokers and 50 non-smokers between ages 25-40 years, further categorized and compared according to age, sex and pack years of smoking. The ECG recordings were analyzed for different ECG parameters like heart rate, P-wave duration, P-wave amplitude, PR interval, QRS duration, RR-interval, ST-segment duration, QT interval and QTc interval. The results were compared using statistical tools. In present study abnormalities in ECG parameters were significantly more prevalent in smokers as compared to non-smokers (56.66 % Vs 6.00 %) (p <.0001). Heart rate and QTc-interval increased with increase in the number of pack-years. This increase was reflected more in female with a similar number of pack years. P-wave amplitude tended to increase with increase in the number of pack years more so in males. P-wave duration, PR-interval, QRS-duration and RR-interval tended to decrease with increase in the number of pack years more so in females with similar number of pack years. QT-interval and ST-segment duration tended to decrease with increase in the number of pack years more so in males. ECG abnormalities in this study indicate cardiovascular risk in term of cardiac arrhythmia, pulmonary arterial hypertension, heart blocks etc in such subjects. As this procedure is non-invasive and cost effective it is potentially an effective and yet a simple method for cardiovascular risk evaluation in smokers. Furthermore, such ECG abnormalities may guide the clinician for risk evaluation in smokers and may be used to convince the smokers to quit smoking.

Arrhythmias in left ventricular noncompaction.

PubMed

Miyake, Christina Y; Kim, Jeffrey J

2015-06-01

Left ventricular noncompaction (LVNC) is a newly recognized form of cardiomyopathy that has been associated with heart failure, arrhythmias, thromboembolic events, and sudden death. Both ventricular and supraventricular arrhythmias are now well described as prominent clinical components of LVNC. Throughout the spectrum of age, these arrhythmias have been associated with prognosis and outcome, and their clinical management is therefore an important aspect of patient care. The risk of sudden death seems to be associated with ventricular dilation, systolic dysfunction, and the presence of arrhythmias. Proposed management strategies shown to have efficacy include antiarrhythmic therapy, ablation techniques, and implantable cardioverter-defibrillator implantation. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed

Pandit, Diptangshu; Zhang, Li; Liu, Chengyu; Chattopadhyay, Samiran; Aslam, Nauman; Lim, Chee Peng

2017-06-01

Detection of the R-peak pertaining to the QRS complex of an ECG signal plays an important role for the diagnosis of a patient's heart condition. To accurately identify the QRS locations from the acquired raw ECG signals, we need to handle a number of challenges, which include noise, baseline wander, varying peak amplitudes, and signal abnormality. This research aims to address these challenges by developing an efficient lightweight algorithm for QRS (i.e., R-peak) detection from raw ECG signals. A lightweight real-time sliding window-based Max-Min Difference (MMD) algorithm for QRS detection from Lead II ECG signals is proposed. Targeting to achieve the best trade-off between computational efficiency and detection accuracy, the proposed algorithm consists of five key steps for QRS detection, namely, baseline correction, MMD curve generation, dynamic threshold computation, R-peak detection, and error correction. Five annotated databases from Physionet are used for evaluating the proposed algorithm in R-peak detection. Integrated with a feature extraction technique and a neural network classifier, the proposed ORS detection algorithm has also been extended to undertake normal and abnormal heartbeat detection from ECG signals. The proposed algorithm exhibits a high degree of robustness in QRS detection and achieves an average sensitivity of 99.62% and an average positive predictivity of 99.67%. Its performance compares favorably with those from the existing state-of-the-art models reported in the literature. In regards to normal and abnormal heartbeat detection, the proposed QRS detection algorithm in combination with the feature extraction technique and neural network classifier achieves an overall accuracy rate of 93.44% based on an empirical evaluation using the MIT-BIH Arrhythmia data set with 10-fold cross validation. In comparison with other related studies, the proposed algorithm offers a lightweight adaptive alternative for R-peak detection with good

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.

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

PubMed

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

2015-01-01

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

Validation of a Novel Digital Tool in Automatic Scoring of an Online ECG Examination at an International Cardiology Meeting.

PubMed

Quinn, Kieran L; Crystal, Eugene; Lashevsky, Ilan; Arouny, Banafsheh; Baranchuk, Adrian

2016-07-01

We have previously developed a novel digital tool capable of automatically recognizing correct electrocardiography (ECG) diagnoses in an online exam and demonstrated a significant improvement in diagnostic accuracy when utilizing an inductive-deductive reasoning strategy over a pattern recognition strategy. In this study, we sought to validate these findings from participants at the International Winter Arrhythmia School meeting, one of the foremost electrophysiology events in Canada. Preregistration to the event was sent by e-mail. The exam was administered on day 1 of the conference. Results and analysis were presented the following morning to participants. Twenty-five attendees completed the exam, providing a total of 500 responses to be marked. The online tool accurately identified 195 of a total of 395 (49%) correct responses (49%). In total, 305 responses required secondary manual review, of which 200 were added to the correct responses pool. The overall accuracy of correct ECG diagnosis for all participants was 69% and 84% when using pattern recognition or inductive-deductive strategies, respectively. Utilization of a novel digital tool to evaluate ECG competency can be set up as a workshop at international meetings or educational events. Results can be presented during the sessions to ensure immediate feedback. © 2015 Wiley Periodicals, Inc.

Arrhythmias

MedlinePlus

... electrodes wet (for example, no swimming, showering, or activities that cause a lot of sweating). There are two kinds of Holter monitoring — continuous recording , which means the ECG/EKG is ...

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.

CSE database: extended annotations and new recommendations for ECG software testing.

PubMed

Smíšek, Radovan; Maršánová, Lucie; Němcová, Andrea; Vítek, Martin; Kozumplík, Jiří; Nováková, Marie

2017-08-01

Nowadays, cardiovascular diseases represent the most common cause of death in western countries. Among various examination techniques, electrocardiography (ECG) is still a highly valuable tool used for the diagnosis of many cardiovascular disorders. In order to diagnose a person based on ECG, cardiologists can use automatic diagnostic algorithms. Research in this area is still necessary. In order to compare various algorithms correctly, it is necessary to test them on standard annotated databases, such as the Common Standards for Quantitative Electrocardiography (CSE) database. According to Scopus, the CSE database is the second most cited standard database. There were two main objectives in this work. First, new diagnoses were added to the CSE database, which extended its original annotations. Second, new recommendations for diagnostic software quality estimation were established. The ECG recordings were diagnosed by five new cardiologists independently, and in total, 59 different diagnoses were found. Such a large number of diagnoses is unique, even in terms of standard databases. Based on the cardiologists' diagnoses, a four-round consensus (4R consensus) was established. Such a 4R consensus means a correct final diagnosis, which should ideally be the output of any tested classification software. The accuracy of the cardiologists' diagnoses compared with the 4R consensus was the basis for the establishment of accuracy recommendations. The accuracy was determined in terms of sensitivity = 79.20-86.81%, positive predictive value = 79.10-87.11%, and the Jaccard coefficient = 72.21-81.14%, respectively. Within these ranges, the accuracy of the software is comparable with the accuracy of cardiologists. The accuracy quantification of the correct classification is unique. Diagnostic software developers can objectively evaluate the success of their algorithm and promote its further development. The annotations and recommendations proposed in this work will allow

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.

High level of oxygen treatment causes cardiotoxicity with arrhythmias and redox modulation

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

Chapalamadugu, Kalyan C.; Panguluri, Siva K.; Bennett, Eric S.

2015-01-01

Hyperoxia exposure in mice leads to cardiac hypertrophy and voltage-gated potassium (Kv) channel remodeling. Because redox balance of pyridine nucleotides affects Kv function and hyperoxia alters cellular redox potential, we hypothesized that hyperoxia exposure leads to cardiac ion channel disturbances and redox changes resulting in arrhythmias. In the present study, we investigated the electrical changes and redox abnormalities caused by 72 h hyperoxia treatment in mice. Cardiac repolarization changes were assessed by acquiring electrocardiogram (ECG) and cardiac action potentials (AP). Biochemical assays were employed to identify the pyridine nucleotide changes, Kv1.5 expression and myocardial injury. Hyperoxia treatment caused marked bradycardia,more » arrhythmia and significantly prolonged (ms) the, RR (186.2 ± 10.7 vs. 146.4 ± 6.2), PR (46.8 ± 3.1 vs. 39.3 ± 1.6), QRS (10.8 ± 0.6 vs. 8.5 ± 0.2), QTc (57.1 ± 3.5 vs. 40 ± 1.4) and JT (13.4 ± 2.1 vs. 7.0 ± 0.5) intervals, when compared with normoxia group. Hyperoxia treatment also induced significant increase in cardiac action potential duration (APD) (ex-APD{sub 90}; 73.8 ± 9.5 vs. 50.9 ± 3.1 ms) and elevated levels of serum markers of myocardial injury; cardiac troponin I (TnI) and lactate dehydrogenase (LDH). Hyperoxia exposure altered cardiac levels of mRNA/protein expression of; Kv1.5, Kvβ subunits and SiRT1, and increased ratios of reduced pyridine nucleotides (NADH/NAD and NADPH/NADP). Inhibition of SiRT1 in H9C2 cells using Splitomicin resulted in decreased SiRT1 and Kv1.5 expression, suggesting that SiRT1 may mediate Kv1.5 downregulation. In conclusion, the cardiotoxic effects of hyperoxia exposure involve ion channel disturbances and redox changes resulting in arrhythmias. - Highlights: • Hyperoxia treatment leads to arrhythmia with prolonged QTc and action potential duration. • Hyperoxia treatment alters cardiac pyridine nucleotide [NAD(P)H/NAD(P)] levels. • SiRT1 and Kv1.5 are co

STEM Education in Jordan Applicable to Developing Future Geophysicists: An Example Combining Electrical Engineering and Medical Research

NASA Astrophysics Data System (ADS)

Fraiwan, A.; Khadra, L.; Shahab, W.; Olgaard, D. L.

2010-12-01

Students in developing countries interested in STEM disciplines (science, technology, engineering & math) often choose majors that will improve their job opportunities in their home country when they graduate, e.g. engineering or medicine. Geoscience might be chosen as a sub-discipline of civil engineering, but rarely as a primary major unless there are local economic natural resources. The Institute of International Education administers the ExxonMobil Middle East and North Africa region scholars program designed to develop skilled students with a focus on geoscience and to build relationships with academic leaders by offering select faculty the opportunity to participation in the AGU fall meeting. At the Jordan University of Science and Technology (JUST), research in electrical engineering applied to medicine has potential links to geosciences. In geophysics, neural wavelet analysis (NWA) is commonly used to process complex seismic signals, e.g. for interpreting lithology or identifying hydrocarbons. In this study, NWA was used to characterize cardiac arrhythmias. A classification scheme was developed in which a neural network is used to identify three types of arrhythmia by distinct frequency bands. The performance of this scheme was tested using patient records from two electrocardiography (ECG) databases. These records contain normal ECG signals, as well as abnormal signals from atrial fibrillation (AF), ventricular tachycardia (VT) and ventricular fibrillation (VF) arrhythmias. The continuous wavelet transform is applied over frequencies of 0-50 Hz for times of 0-2s. For a normal ECG, the results show that the strongest signal is in a frequency range of 4-10 Hz. For AF, a low frequency ECG signal in the range of 0-5 Hz extends over the whole time domain. For VT, the low frequency spectrum is in the range of 2-10 Hz, appearing as three distinct bands. For VF, a continuous band in the range of 2-10 Hz extends over the whole time domain. The classification of

Bench study of the accuracy of a commercial AED arrhythmia analysis algorithm in the presence of electromagnetic interferences.

PubMed

Jekova, Irena; Krasteva, Vessela; Ménétré, Sarah; Stoyanov, Todor; Christov, Ivaylo; Fleischhackl, Roman; Schmid, Johann-Jakob; Didon, Jean-Philippe

2009-07-01

This paper presents a bench study on a commercial automated external defibrillator (AED). The objective was to evaluate the performance of the defibrillation advisory system and its robustness against electromagnetic interferences (EMI) with central frequencies of 16.7, 50 and 60 Hz. The shock advisory system uses two 50 and 60 Hz band-pass filters, an adaptive filter to identify and suppress 16.7 Hz interference, and a software technique for arrhythmia analysis based on morphology and frequency ECG parameters. The testing process includes noise-free ECG strips from the internationally recognized MIT-VFDB ECG database that were superimposed with simulated EMI artifacts and supplied to the shock advisory system embedded in a real AED. Measurements under special consideration of the allowed variation of EMI frequency (15.7-17.4, 47-52, 58-62 Hz) and amplitude (1 and 8 mV) were performed to optimize external validity. The accuracy was reported using the American Heart Association (AHA) recommendations for arrhythmia analysis performance. In the case of artifact-free signals, the AHA performance goals were exceeded for both sensitivity and specificity: 99% for ventricular fibrillation (VF), 98% for rapid ventricular tachycardia (VT), 90% for slow VT, 100% for normal sinus rhythm, 100% for asystole and 99% for other non-shockable rhythms. In the presence of EMI, the specificity for some non-shockable rhythms (NSR, N) may be affected in some specific cases of a low signal-to-noise ratio and extreme frequencies, leading to a drop in the specificity with no more than 7% point. The specificity for asystole and the sensitivity for VF and rapid VT in the presence of any kind of 16.7, 50 or 60 Hz EMI simulated artifact were shown to reach the equivalence of sensitivity required for non-noisy signals. In conclusion, we proved that the shock advisory system working in a real AED operates accurately according to the AHA recommendations without artifacts and in the presence of EMI

Bile acids induce arrhythmias in human atrial myocardium--implications for altered serum bile acid composition in patients with atrial fibrillation.

PubMed

Rainer, Peter P; Primessnig, Uwe; Harenkamp, Sandra; Doleschal, Bernhard; Wallner, Markus; Fauler, Guenter; Stojakovic, Tatjana; Wachter, Rolf; Yates, Ameli; Groschner, Klaus; Trauner, Michael; Pieske, Burkert M; von Lewinski, Dirk

2013-11-01

High bile acid serum concentrations have been implicated in cardiac disease, particularly in arrhythmias. Most data originate from in vitro studies and animal models. We tested the hypotheses that (1) high bile acid concentrations are arrhythmogenic in adult human myocardium, (2) serum bile acid concentrations and composition are altered in patients with atrial fibrillation (AF) and (3) the therapeutically used ursodeoxycholic acid has different effects than other potentially toxic bile acids. Multicellular human atrial preparations ('trabeculae') were exposed to primary bile acids and the incidence of arrhythmic events was assessed. Bile acid concentrations were measured in serum samples from 250 patients and their association with AF and ECG parameters analysed. Additionally, we conducted electrophysiological studies in murine myocytes. Taurocholic acid (TCA) concentration-dependently induced arrhythmias in atrial trabeculae (14/28 at 300 µM TCA, p<0.01) while ursodeoxycholic acid did not. Patients with AF had significantly decreased serum levels of ursodeoxycholic acid conjugates and increased levels of non-ursodeoxycholic bile acids. In isolated myocytes, TCA depolarised the resting membrane potential, enhanced Na(+)/Ca(2+) exchanger (NCX) tail current density and induced afterdepolarisations. Inhibition of NCX prevented arrhythmias in atrial trabeculae. High TCA concentrations induce arrhythmias in adult human atria while ursodeoxycholic acid does not. AF is associated with higher serum levels of non-ursodeoxycholic bile acid conjugates and low levels of ursodeoxycholic acid conjugates. These data suggest that higher levels of toxic (arrhythmogenic) and low levels of protective bile acids create a milieu with a decreased arrhythmic threshold and thus may facilitate arrhythmic events.

New FIGO and Swedish intrapartum cardiotocography classification systems incorporated in the fetal ECG ST analysis (STAN) interpretation algorithm: agreements and discrepancies in cardiotocography classification and evaluation of significant ST events.

PubMed

Olofsson, Per; Norén, Håkan; Carlsson, Ann

2018-02-01

The updated intrapartum cardiotocography (CTG) classification system by FIGO in 2015 (FIGO2015) and the FIGO2015-approached classification by the Swedish Society of Obstetricians and Gynecologist in 2017 (SSOG2017) are not harmonized with the fetal ECG ST analysis (STAN) algorithm from 2007 (STAN2007). The study aimed to reveal homogeneity and agreement between the systems in classifying CTG and ST events, and relate them to maternal and perinatal outcomes. Among CTG traces with ST events, 100 traces originally classified as normal, 100 as suspicious and 100 as pathological were randomly selected from a STAN database and classified by two experts in consensus. Homogeneity and agreement statistics between the CTG classifications were performed. Maternal and perinatal outcomes were evaluated in cases with clinically hidden ST data (n = 151). A two-tailed p < 0.05 was regarded as significant. For CTG classes, the heterogeneity was significant between the old and new systems, and agreements were moderate to strong (proportion of agreement, kappa index 0.70-0.86). Between the new classifications, heterogeneity was significant and agreements strong (0.90, 0.92). For significant ST events, heterogeneities were significant and agreements moderate to almost perfect (STAN2007 vs. FIGO2015 0.86, 0.72; STAN2007 vs. SSOG2017 0.92, 0.84; FIGO2015 vs. SSOG2017 0.94, 0.87). Significant ST events occurred more often combined with STAN2007 than with FIGO2015 classification, but not with SSOG2017; correct identification of adverse outcomes was not significantly different between the systems. There are discrepancies in the classification of CTG patterns and significant ST events between the old and new systems. The clinical relevance of the findings remains to be shown. © 2017 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).

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.

Heart Rate Variability and Wavelet-based Studies on ECG Signals from Smokers and Non-smokers

NASA Astrophysics Data System (ADS)

Pal, K.; Goel, R.; Champaty, B.; Samantray, S.; Tibarewala, D. N.

2013-12-01

The current study deals with the heart rate variability (HRV) and wavelet-based ECG signal analysis of smokers and non-smokers. The results of HRV indicated dominance towards the sympathetic nervous system activity in smokers. The heart rate was found to be higher in case of smokers as compared to non-smokers ( p < 0.05). The frequency domain analysis showed an increase in the LF and LF/HF components with a subsequent decrease in the HF component. The HRV features were analyzed for classification of the smokers from the non-smokers. The results indicated that when RMSSD, SD1 and RR-mean features were used concurrently a classification efficiency of > 90 % was achieved. The wavelet decomposition of the ECG signal was done using the Daubechies (db 6) wavelet family. No difference was observed between the smokers and non-smokers which apparently suggested that smoking does not affect the conduction pathway of heart.

Associations between arrhythmia episodes and temporally and spatially resolved black carbon and particulate matter in elderly patients

PubMed Central

Zanobetti, Antonella; Coull, Brent A.; Gryparis, Alexandros; Kloog, Itai; Sparrow, David; Vokonas, Pantel S; Wright, Robert O.; Gold, Diane R; Schwartz, Joel

2015-01-01

Objectives Ambient air pollution has been associated with sudden deaths, some of which are likely due to ventricular arrhythmias. Defibrillator discharge studies have examined the association of air pollution with arrhythmias in sensitive populations. No studies have assessed this association using residence-specific estimates of air pollution exposure. Methods In the Normative Aging Study, we investigated the association between temporally-and spatially-resolved black carbon (BC) and PM2.5 and arrhythmia episodes (bigeminy, trigeminy or couplets episodes) measured as ventricular ectopy (VE) by 4-min electrocardiogram (ECG) monitoring in repeated measures of 701 subjects, during the years 2000 to 2010. We used a binomial distribution (having or not a VE episode) in a mixed effect model with a random intercept for subject, controlling for seasonality, temperature, day of the week, medication use, smoking, having diabetes, BMI and age. We also examined whether these associations were modified by genotype or phenotype. Results We found significant increases in VE with both pollutants and lags; for the estimated concentration averaged over the three days prior to the health assessment we found increases in the odds of having VE with an OR of 1.52 (95% CI: 1.19–1.94) for an IQR (0.30 μg/m3) increase in BC and an OR of 1.39 (95% CI: 1.12–1.71) for an IQR (5.63 μg/m3) increase in PM2.5. We also found higher effects in subjects with the GSTT1 and GSTM1 variants and in obese (P-values<0.05). Conclusion Increased levels of short-term traffic related pollutants may increase the risk of ventricular arrhythmia in elderly subjects. PMID:24142987

[A research on real-time ventricular QRS classification methods for single-chip-microcomputers].

PubMed

Peng, L; Yang, Z; Li, L; Chen, H; Chen, E; Lin, J

1997-05-01

Ventricular QRS classification is key technique of ventricular arrhythmias detection in single-chip-microcomputer based dynamic electrocardiogram real-time analyser. This paper adopts morphological feature vector including QRS amplitude, interval information to reveal QRS morphology. After studying the distribution of QRS morphology feature vector of MIT/BIH DB ventricular arrhythmia files, we use morphological feature vector cluster to classify multi-morphology QRS. Based on the method, morphological feature parameters changing method which is suitable to catch occasional ventricular arrhythmias is presented. Clinical experiments verify missed ventricular arrhythmia is less than 1% by this method.

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.

Management of unstable arrhythmias in cardiogenic shock.

PubMed

Saidi, Abdulfattah; Akoum, Nazem; Bader, Feras

2011-08-01

Atrial and ventricular arrhythmias commonly arise in the setting of cardiogenic shock and often result in hemodynamic deterioration. Causative factors include myocardial ischemia, volume overload, and metabolic disturbances. Correcting these factors plays an important role in managing arrhythmias in this setting. Ventricular arrhythmias are more ominous compared to atrial arrhythmias but both require prompt intervention with electrical shock and anti-arrhythmic drug suppression. Coronary reperfusion is key to improving survival, including reducing the risk of sudden cardiac arrest, in acute myocardial infarction. Case series have also demonstrated the value of intra-aortic balloon pump counter-pulsation in suppressing ventricular arrhythmias in cardiogenic shock. The mechanism of arrhythmia suppression may be due to improved coronary perfusion and afterload reduction. Percutaneous ventricular assist device placement may be effective in this setting; however, data addressing this specific endpoint are lacking. Anti-arrhythmic drug options for ventricular and atrial arrhythmia suppression, in the setting of cardiogenic shock, are relatively limited. Common class I agents are excluded due to the inherent abnormal cardiac structure and function in the setting of cardiogenic shock. Class III drug options include dofetilide and amiodarone. The other Class III agents, sotalol and dronedarone, are excluded due to associated mortality observed in the SWORD and ANDROMEDA trials, respectively. Dofetilide is renally excreted and causes QT interval prolongation. Care should be taken to avoid excessive drug accumulation due to poor kidney perfusion and function. Dofetilide is approved for use for atrial arrhythmias and has not been studied for ventricular arrhythmia suppression. The DIAMOND-CHF trial established its safety in the setting of heart failure. Amiodarone is very effective in suppressing both atrial and ventricular arrhythmias. It is often the drug of choice in heart

[A quality controllable algorithm for ECG compression based on wavelet transform and ROI coding].

PubMed

Zhao, An; Wu, Baoming

2006-12-01

This paper presents an ECG compression algorithm based on wavelet transform and region of interest (ROI) coding. The algorithm has realized near-lossless coding in ROI and quality controllable lossy coding outside of ROI. After mean removal of the original signal, multi-layer orthogonal discrete wavelet transform is performed. Simultaneously,feature extraction is performed on the original signal to find the position of ROI. The coefficients related to the ROI are important coefficients and kept. Otherwise, the energy loss of the transform domain is calculated according to the goal PRDBE (Percentage Root-mean-square Difference with Baseline Eliminated), and then the threshold of the coefficients outside of ROI is determined according to the loss of energy. The important coefficients, which include the coefficients of ROI and the coefficients that are larger than the threshold outside of ROI, are put into a linear quantifier. The map, which records the positions of the important coefficients in the original wavelet coefficients vector, is compressed with a run-length encoder. Huffman coding has been applied to improve the compression ratio. ECG signals taken from the MIT/BIH arrhythmia database are tested, and satisfactory results in terms of clinical information preserving, quality and compress ratio are obtained.

Adaptive EMG noise reduction in ECG signals using noise level approximation

NASA Astrophysics Data System (ADS)

Marouf, Mohamed; Saranovac, Lazar

2017-12-01

In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.

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

Malignant ventricular arrhythmias in alcoholic cardiomyopathy.

PubMed

Guzzo-Merello, Gonzalo; Dominguez, Fernando; González-López, Esther; Cobo-Marcos, Marta; Gomez-Bueno, Manuel; Fernandez-Lozano, Ignacio; Millan, Isabel; Segovia, Javier; Alonso-Pulpon, Luis; Garcia-Pavia, Pablo

2015-11-15

Excessive alcohol consumption is a well-known aetiology of atrial arrhythmias but there is little information concerning the prevalence or incidence of malignant ventricular arrhythmias in alcoholic cardiomyopathy (ACM). This study sought to investigate incidence and predictive factors of ventricular arrhythmias in ACM. Retrospective observational study of the clinical characteristics and long-term arrhythmic events in 282 consecutive patients with ACM (94 individuals) and idiopathic dilated cardiomyopathy (IDCM) (188 individuals) evaluated between 1993 and 2011. During a median follow-up of 38months (IQR:12-77), 42 patients died and 79 underwent heart transplantation [31 (33%) with ACM vs 90 (48%) with IDCM; p=0.017]. A total of 37 (13%) patients [18 (19%) ACM vs 20 (11%) IDCM; p=0.048] suffered malignant ventricular arrhythmias. On multivariate analysis, left bundle branch block (LBBB) (OR 2.4; CI95%: 1.2-5; p=0.015) and alcoholic aetiology (OR 2.3; CI95%: 1.1-4.5; p=0.026) were the only independent predictors of malignant ventricular arrhythmic events. A total of 18 (19%) ACM patients experienced 20 malignant ventricular arrhythmic events (4 aborted SCD, 8 SCD and 8 appropriate ICD therapies). At baseline evaluation, the only independent predictor of malignant ventricular arrhythmias in ACM patients was LBBB (OR 11.2; CI95%: 2.6-50; p=0.001). No malignant ventricular arrhythmias were recorded during follow-up in ACM patients if left ventricular ejection fraction (LVEF) had increased or remained ≥40%. Malignant ventricular arrhythmias are more frequent in ACM than in IDCM. LBBB identifies ACM patients with increased risk of SCD. No malignant ventricular arrhythmias were found during follow-up in ACM patients when LVEF was ≥40%. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The Effects of Nandrolone Decanoate Along with Prolonged Low-Intensity Exercise on Susceptibility to Ventricular Arrhythmias.

PubMed

Binayi, Fateme; Joukar, Siyavash; Najafipour, Hamid; Karimi, Abdolah; Karimi, Ali; Abdollahi, Farzane; Masumi, Yaser

2016-01-01

We examined the influence of chronic administration of nandrolone decanoate with low-intensity endurance swimming exercise on susceptibility to lethal ventricular arrhythmias in rat. The animal groups included the control group, exercise group (EX), nandrolone group (Nan), vehicle group (Arach), trained vehicle group (Arach + Ex) and trained nandrolone group (Nan + Ex) that treated for 8 weeks. Then, arrhythmia induction was performed by intravenous infusion of aconitine and electrocardiogram recorded. Then, malondialdehyde (MDA), hydroxyproline (HYP) and glutathione peroxidase of heart tissue were measured. Chronic administration of nandrolone with low-intensity endurance swimming exercise had no significant effect on blood pressure, heart rate and basal ECG parameters except RR interval that showed increase (P < 0.05). Low-intensity exercise could prevent the incremental effect of nandrolone on MDA and HYP significantly. It also increased the heart hypertrophy index (P < 0.05) and reduced the abating effect of nandrolone on animal weighting. Nandrolone along with exercise significantly increased the duration of VF (P < 0.05) and reduced the VF latency (P < 0.05). The findings suggest that chronic co-administration of nandrolone with low-intensity endurance swimming exercise to some extent facilitates the occurrence of ventricular fibrillation in rat. Complementary studies are needed to elucidate the involved mechanisms of this abnormality.

[Extension of cardiac monitoring function by used of ordinary ECG machine].

PubMed

Chen, Zhencheng; Jiang, Yong; Ni, Lili; Wang, Hongyan

2002-06-01

This paper deals with a portable monitor system on liquid crystal display (LCD) based on this available ordinary ECG machine, which is low power and suitable for China's specific condition. Apart from developing the overall scheme of the system, this paper also has completed the design of the hardware and the software. The 80c196 single chip microcomputer is taken as the central microprocessor and real time electrocardiac single is data treated and analyzed in the system. With the performance of ordinary monitor, this machine also possesses the following functions: five types of arrhythmia analysis, alarm, freeze, and record of automatic pappering, convenient in carrying, with alternate-current (AC) or direct-current (DC) powered. The hardware circuit is simplified and the software structure is optimized in this paper. Multiple low power designs and LCD unit design are adopted and completed in it. Popular in usage, low in cost price, the portable monitor system will have a valuable influence on China's monitor system field.

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.

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.

Adapting detection sensitivity based on evidence of irregular sinus arrhythmia to improve atrial fibrillation detection in insertable cardiac monitors.

PubMed

Pürerfellner, Helmut; Sanders, Prashanthan; Sarkar, Shantanu; Reisfeld, Erin; Reiland, Jerry; Koehler, Jodi; Pokushalov, Evgeny; Urban, Luboš; Dekker, Lukas R C

2017-10-03

Intermittent change in p-wave discernibility during periods of ectopy and sinus arrhythmia is a cause of inappropriate atrial fibrillation (AF) detection in insertable cardiac monitors (ICM). To address this, we developed and validated an enhanced AF detection algorithm. Atrial fibrillation detection in Reveal LINQ ICM uses patterns of incoherence in RR intervals and absence of P-wave evidence over a 2-min period. The enhanced algorithm includes P-wave evidence during RR irregularity as evidence of sinus arrhythmia or ectopy to adaptively optimize sensitivity for AF detection. The algorithm was developed and validated using Holter data from the XPECT and LINQ Usability studies which collected surface electrocardiogram (ECG) and continuous ICM ECG over a 24-48 h period. The algorithm detections were compared with Holter annotations, performed by multiple reviewers, to compute episode and duration detection performance. The validation dataset comprised of 3187 h of valid Holter and LINQ recordings from 138 patients, with true AF in 37 patients yielding 108 true AF episodes ≥2-min and 449 h of AF. The enhanced algorithm reduced inappropriately detected episodes by 49% and duration by 66% with <1% loss in true episodes or duration. The algorithm correctly identified 98.9% of total AF duration and 99.8% of total sinus or non-AF rhythm duration. The algorithm detected 97.2% (99.7% per-patient average) of all AF episodes ≥2-min, and 84.9% (95.3% per-patient average) of detected episodes involved AF. An enhancement that adapts sensitivity for AF detection reduced inappropriately detected episodes and duration with minimal reduction in sensitivity. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Cardiology

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.

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

Aiding the Detection of QRS Complex in ECG Signals by Detecting S Peaks Independently.

PubMed

Sabherwal, Pooja; Singh, Latika; Agrawal, Monika

2018-03-30

In this paper, a novel algorithm for the accurate detection of QRS complex by combining the independent detection of R and S peaks, using fusion algorithm is proposed. R peak detection has been extensively studied and is being used to detect the QRS complex. Whereas, S peaks, which is also part of QRS complex can be independently detected to aid the detection of QRS complex. In this paper, we suggest a method to first estimate S peak from raw ECG signal and then use them to aid the detection of QRS complex. The amplitude of S peak in ECG signal is relatively weak than corresponding R peak, which is traditionally used for the detection of QRS complex, therefore, an appropriate digital filter is designed to enhance the S peaks. These enhanced S peaks are then detected by adaptive thresholding. The algorithm is validated on all the signals of MIT-BIH arrhythmia database and noise stress database taken from physionet.org. The algorithm performs reasonably well even for the signals highly corrupted by noise. The algorithm performance is confirmed by sensitivity and positive predictivity of 99.99% and the detection accuracy of 99.98% for QRS complex detection. The number of false positives and false negatives resulted while analysis has been drastically reduced to 80 and 42 against the 98 and 84 the best results reported so far.

Geraniol blocks calcium and potassium channels in the mammalian myocardium: useful effects to treat arrhythmias.

PubMed

de Menezes-Filho, José Evaldo Rodrigues; Gondim, Antônio Nei Santana; Cruz, Jader Santos; de Souza, Américo Azevedo; Santos, José Nilson Andrade Dos; Conde-Garcia, Eduardo Antônio; de Sousa, Damião Pergentino; Santos, Michel Santana; de Oliveira, Evaleide Diniz; de Vasconcelos, Carla Maria Lins

2014-12-01

Geraniol is a monoterpene present in several essential oils, and it is known to have a plethora of pharmacological activities. In this study, we explored the contractile and electrophysiological properties of geraniol and its antiarrhythmic effects in the heart. The geraniol effects on atrial contractility, L-type Ca(2+) current, K(+) currents, action potential (AP) parameters, ECG profile and on the arrhythmia induced by ouabain were evaluated. In the atrium, geraniol reduced the contractile force (~98%, EC = 1,510 ± 160 μM) and diminished the positive inotropism of CaCl2 and BAY K8644. In cardiomyocytes, the IC a,L was reduced by 50.7% (n = 5) after perfusion with 300 μM geraniol. Moreover, geraniol prolonged the AP duration (APD) measured at 50% (n = 5) after repolarization, without changing the resting potential. The increased APD could be attributed to the blockade of the transient outward K(+) current (Ito ) (59.7%, n = 4), the non-inactivation K(+) current (Iss ) (39.2%, n = 4) and the inward rectifier K(+) current (IK 1 ) (33.7%, n = 4). In isolated hearts, geraniol increased PRi and QTi without affecting the QRS complex (n = 6), and it reduced both the left ventricular pressure (83%) and heart rate (16.5%). Geraniol delayed the time to onset of ouabain-induced arrhythmias by 128%, preventing 30% of the increase in resting tension (n = 6). Geraniol exerts its negative inotropic and chronotropic responses in the heart by decreasing both L-type Ca(2+) and voltage-gated K(+) currents, ultimately acting against ouabain-induced arrhythmias. © 2014 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

Cardiac Arrhythmias in Experimental Syncope

DTIC Science & Technology

1958-11-01

cardiac toward respiratory alkalosis . Regardless of arriythmias by stress procedures. It follows these two extremes in the assumed change in that previous...frequently induced by respiratory maneuvers without syncope. Intravenous aidministration of atropine appatently prevented recurrence of cardiac...arrhythmia induced by respiratory maneuvers. Significant cardiac arrhythmia was also noted in simple orthostatic syncope. Loss of consciousness presents a

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.

Risk of and risk factors for hypoglycemia and associated arrhythmias in patients with type 2 diabetes and cardiovascular disease: a cohort study under real-world conditions.

PubMed

Pistrosch, Frank; Ganz, Xenia; Bornstein, Stefan R; Birkenfeld, Andreas L; Henkel, Elena; Hanefeld, Markolf

2015-10-01

Severe hypoglycemia is one of the strongest predictors of adverse clinical outcomes in patients with type 2 diabetes. Our study addressed the question whether there is a relationship between hypoglycemic events (HE) and severe cardiac arrhythmias in type 2 diabetic patients with established clinical risk factors under real-world conditions. We included 94 patients with type 2 diabetes and documented cardiovascular disease, in which interstitial glucose values and Holter ECG were recorded for 5 days in parallel. Patients received a stable treatment with insulin and/or sulfonylurea and were instructed to record symptoms of hypoglycemia or arrhythmias. Continuous glucose monitoring revealed 54 HE (interstitial glucose <3.1 mmol/l) in a total of 26 patients. Patients perceived only 39 % of HE during the day and 11 % of HE during the night. Patients with HE had a significantly higher number of severe ventricular arrhythmias [ventricular tachycardia (VT) 32.8 ± 60 vs. 0.9 ± 4.2, p = 0.019], and multivariate regression analysis revealed the duration of severe HE and TSH level as independent predictors of the occurrence of a VT. In conclusion, our study suggests that hypoglycemia might be able to trigger at least under certain circumstances, such as low TSH, ventricular arrhythmias under real-world conditions. The large number of unrecognized HE and VT in vulnerable patients treated with insulin or sulfonylurea should encourage the practitioner to focus on stable glucose control and to search for silent HE.

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.

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

PubMed

Helfenbein, Eric; Firoozabadi, Reza; Chien, Simon; Carlson, Eric; Babaeizadeh, Saeed

2014-01-01

Respiration rate (RR) is a critical vital sign that can be monitored to detect acute changes in patient condition (e.g., apnea) and potentially provide an early warning of impending life-threatening deterioration. Monitoring respiration signals is also critical for detecting sleep disordered breathing such as sleep apnea. Additionally, analyzing a respiration signal can enhance the quality of medical images by gating image acquisition based on the same phase of the patient's respiratory cycle. Although many methods exist for measuring respiration, in this review we focus on three ECG-derived respiration techniques we developed to obtain respiration from an ECG signal. The first step in all three techniques is to analyze the ECG to detect beat locations and classify them. 1) The EDR method is based on analyzing the heart axis shift due to respiration. In our method, one respiration waveform value is calculated for each normal QRS complex by measuring the peak to QRS trough amplitude. Compared to other similar EDR techniques, this method does not need removal of baseline wander from the ECG signal. 2) The RSA method uses instantaneous heart rate variability to derive a respiratory signal. It is based on the observed respiratory sinus arrhythmia governed by baroreflex sensitivity. 3) Our EMGDR method for computing a respiratory waveform uses measurement of electromyogram (EMG) activity created by respiratory effort of the intercostal muscles and diaphragm. The ECG signal is high-pass filtered and processed to reduce ECG components and accentuate the EMG signal before applying RMS and smoothing. Over the last five years, we have performed six studies using the above methods: 1) In 1907 sleep lab patients with >1.5M 30-second epochs, EDR achieved an apnea detection accuracy of 79%. 2) In 24 adult polysomnograms, use of EDR and chest belts for RR computation was compared to airflow RR; mean RR error was EDR: 1.8±2.7 and belts: 0.8±2.1. 3) During cardiac MRI, a

Fine scale spatial and temporal variation in temperature and arrhythmia episodes in the VA Normative Aging Study

PubMed Central

Zanobetti, Antonella; Coull, Brent A.; Kloog, Itai; Sparrow, David; Vokonas, Pantel S.; Gold, Diane R.; Schwartz, Joel D.

2017-01-01

Many studies have demonstrated that cold and hot temperatures are associated with increased deaths and hospitalization rates; new findings indicate also an association with more specific cardiac risk factors. Most of these existing studies have relied on few weather stations to characterize exposures; few have used residence-specific estimates of temperature, or examined the exposure-response function. We investigated the association of arrhythmia episodes with spatial and temporal variation in temperature. We also evaluated the association between monitored ambient temperature (central) and the same outcome. This longitudinal analysis included 701 older men participating in the VA Normative Aging Study. Arrhythmia episodes were measured as ventricular ectopy (VE) (bigeminy, trigemini or couplets episodes) by 4min electrocardiogram (ECG) monitoring in repeated visits during 2000–2010. The outcome was defined as having or not VE episodes during a study visit. We applied a mixed effect logistic regression model with a random intercept for subject, controlling for seasonality, weekday, medication use, smoking, diabetes status, body mass index and age. We also examined effect modification by personal characteristics, confounding by air pollution, and the exposure-response function. For 1° C increase in the same day residence-specific temperature, the odds of having VE episodes was 1.10 (95%CI: 1.04–1.17). The odds associated with 1° C increase in central temperature was 1.05 (95%CI: 1.02–1.09). The exposure-response function was non-linear for averages of temperature, presenting a J-shaped pattern, suggesting greater risk at lower and higher temperatures. Increased warm temperature and decreased cold temperature may increase the risk of ventricular arrhythmias. PMID:28001123

On the normal scalar ECG. A new classification system considering age, sex and heart position.

PubMed

Lundh, B

1984-01-01

472 randomly selected men and women from the city of Lund were examined for disease in the heart, lungs and for hypertension. 163 men and 194 women who had no symptom or sign of disease were accepted for the further study. The prevalence of various exclusion criterias, such as symptoms and signs of heart disease, lung disease and other diseases which may possibly affect the ECG are reported as well as the distribution of blood pressures in the sample. A computer-averaged standard 12-lead ECG (leads aVL, I, -aVR, II, aVF, III, V1-V6) was recorded. All measurements of ECG-deflections have been made visually using a magnifying glass (6 times). ST-segments were classified according to the Punsar code by independent visual observers as well as by the computer. The mean frontal QRS-axis shifted to the left with advancing age, but the shift was statistically significant only in men. In both men and women there was a leftward shift of the mean frontal QRS-axis with increased weight, increased chest circumference and increased obesity index. The normal range of axis was found to be 0 degrees to 90 degrees in men and +15 degrees to 90 degrees in women. The problems concerning the definition of the electrical heart position is discussed. The concept of a Q-axis is introduced as an alternative way to indicate electrical heart position. There is a statistical significant relationship between the Q-axis and the QRS-axis in the frontal plane, although this relationship is not always apparent in the individual ECG. The presence or absence of a Q-wave in an individual lead was used to denote a lead as being a left ventricular lead or not. Using the Q-wave as a marker of heart position in the individual lead is more practical than to use the QRS-axis or the transitional zone. Duration and amplitude of the Q-wave have been measured. The upper limit of normal duration exceeded 0.03 s in leads aVL and aVF in men but not in women. The R-wave amplitudes proved to vary with age and heart

Tele-electrocardiography in the epidemiological 'Study of Health in Pomerania' (SHIP).

PubMed

Alte, Dietrich; Völzke, Henry; Robinson, Daniel M; Kleine, Volker; Grabe, Hans Jörgen; John, Ulrich; Felix, Stephan B

2006-01-01

We have evaluated a portable electrocardiogram (ECG) card in the large population-based epidemiological 'Study of Health in Pomerania' (SHIP). In all, 7008 men and women (20-79 years) were randomly selected from population registries and 4310 subjects participated. Participants used an ECG card for four weeks and recorded two ECGs daily. The participants were also encouraged to record additional ECGs in the case of symptomatic arrhythmias, chest pain or dizziness. The ECGs were sent via telephone. Acrobat (.pdf) files arrived at the study centre via email. Arrhythmias were analysed by visual ECG inspection. Seventy-one per cent of the participants sent at least 80% of the requested ECGs for four weeks. There were few problems (about 70) in the total of 38,162 ECGs transmitted. Overall, 94% of all ECGs were rated as 'good'. Physicians required about 1.5 h to read approximately 100 ECGs daily. The functionality and ergonomics of ECG cards appear to be sufficiently developed for large-scale use in epidemiological studies.

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.

β1-Adrenoceptor blocker aggravated ventricular arrhythmia.

PubMed

Wang, Yan; Patel, Dimpi; Wang, Dao Wu; Yan, Jiang Tao; Hsia, Henry H; Liu, Hao; Zhao, Chun Xia; Zuo, Hou Juan; Wang, Dao Wen

2013-11-01

To assess the impact of β1 -adrenoceptor blockers (β1 -blocker) and isoprenaline on the incidence of idiopathic repetitive ventricular arrhythmia that apparently decreases with preprocedural anxiety. From January 2010 to July 2012, six patients were identified who had idiopathic ventricular arrhythmias that apparently decreased (by greater than 90%) with preprocedural anxiety. The number of ectopic ventricular beats per hour (VPH) was calculated from Holter or telemetry monitoring to assess the ectopic burden. The mean VPH of 24 hours from Holter before admission (VPH-m) was used as baseline (100%) for normalization. β1 -Blockers, isoprenaline, and/or aminophylline were administrated successively on the ward and catheter lab to evaluate their effects on the ventricular arrhythmias. Among 97 consecutive patients with idiopathic ventricular arrhythmias, six had reduction in normalized VPHs in the hour before the scheduled procedure time from (104.6 ± 4.6%) to (2.8 ± 1.6%) possibly due to preprocedural anxiety (P < 0.05), then increased to (97.9 ± 9.7%) during β1 -blocker administration (P < 0.05), then quickly reduced to (1.6 ± 1.0%) during subsequent isoprenaline infusion. Repeated β1 -blocker quickly counteracted the inhibitory effect of isoprenaline, and VPHs increased to (120.9 ± 2.4%) from (1.6 ± 1.0%; P < 0.05). Isoprenaline and β1 -blocker showed similar effects on the arrhythmias in catheter lab. In some patients with structurally normal heart and ventricular arrhythmias there is a marked reduction of arrhythmias associated with preprocedural anxiety. These patients exhibit a reproducible sequence of β1 -blocker aggravation and catecholamine inhibition of ventricular arrhythmias, including both repetitive ventricular premature beats and monomorphic ventricular tachycardia. ©2013, The Authors. Journal compilation ©2013 Wiley Periodicals, Inc.

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.

Alcohol, cardiac arrhythmias and sudden death.

PubMed

Kupari, M; Koskinen, P

1998-01-01

Studies in experimental animals have shown varying and apparently opposite effects of alcohol on cardiac rhythm and conduction. Given acutely to non-alcoholic animals, ethanol may even have anti-arrhythmic properties whereas chronic administration clearly increases the animals' susceptibility to cardiac arrhythmias. Chronic heavy alcohol use has been incriminated in the genesis of cardiac arrhythmias in humans. The evidence has come from clinical observations, retrospective case-control studies, controlled studies of consecutive admissions for arrhythmias, and prospective epidemiological investigations. Furthermore, electrophysiological studies have shown that acute alcohol administration facilitates the induction of tachyarrhythmias in selected heavy drinkers. The role of alcohol appears particularly conspicuous in idiopathic atrial fibrillation. Occasionally, ventricular tachyarrhythmias have also been provoked by alcohol intake. Several lines of evidence suggest that heavy drinking increases the risk of sudden cardiac death with fatal arrhythmia as the most likely mechanism. According to epidemiological studies this effect appears most prominent in middle-aged men and is only partly explained by confounding traits such as smoking and social class. The basic arrhythmogenic effects of alcohol are still insufficiently delineated. Subclinical heart muscle injury from chronic heavy use may be instrumental in producing patchy delays in conduction. The hyperadrenergic state of drinking and withdrawal may also contribute, as may electrolyte abnormalities, impaired vagal heart rate control, repolarization abnormalities with prolonged QT intervals and worsening of myocardial ischaemia or sleep apnoea. Most of what we know about alcohol and arrhythmias relates to heavy drinking. The effect of social drinking on clinical arrhythmias in non-alcoholic cardiac patients needs to be addressed further.

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.

Atrial Arrhythmia Summit: Post Summit Report

NASA Technical Reports Server (NTRS)

Barr, Yael

2010-01-01

The Atrial Arrhythmia Summit brought together nationally and internationally recognized experts in cardiology, electrophysiology, exercise physiology, and space medicine in an effort to elucidate the mechanisms, risk factors, and management of atrial arrhythmias in the unique occupational cohort of the U.S. astronaut corps.

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.

Cardiac Arrhythmia and Injury Induced in Rats by Burst and Pulsed Mode Ultrasound with Gas Body Contrast Agent

PubMed Central

Miller, Douglas L.; Dou, Chunyan; Lucchesi, Benedict R.

2009-01-01

Objective Premature complexes (PCs) in the electrocardiogram (ECG) signal have been reported for myocardial contrast echocardiography and also for burst mode (physical therapy) ultrasound with gas body contrast agent at lower peak rarefactional pressure amplitudes (PRPAs). For contrast echocardiography, irreversibly injured cardiomyocytes have been associated with the arrhythmia. The objective was to determine if cardiomyocyte injury is associated with the PCs induced by the burst mode at lower PRPAs. Methods Anesthetized rats were exposed to focused 1.5 MHz ultrasound in a water bath. Evans blue dye was injected IP to stain injured cardiomyocytes and Definity ultrasound contrast agent was infused IV. Continuous burst mode simulated physical therapy ultrasound. Intermittent 2 ms bursts, or envelopes of pulses simulating diagnostic ultrasound, were triggered 1:4 at end systole. PCs were observed on ECG recordings and stained cardiomyocytes were counted in frozen sections. Results The continuous burst mode produced variable PCs and stained cells above 0.3 MPa PRPA. The triggered bursts above 0.3 MPa and pulse envelopes above 1.2 MPa produced statistically significant (P<0.01) PCs and stained cardiomyocytes. Conclusion Irreversible cardiomyocyte injury was associated with the development of PCs for burst mode and occurred at substantially lower PRPAs than for pulsed ultrasound. PMID:19854967

Automated respiratory sinus arrhythmia measurement: Demonstration using executive function assessment.

PubMed

Hegarty-Craver, Meghan; Gilchrist, Kristin H; Propper, Cathi B; Lewis, Gregory F; DeFilipp, Samuel J; Coffman, Jennifer L; Willoughby, Michael T

2017-08-08

Respiratory sinus arrhythmia (RSA) is a quantitative metric that reflects autonomic nervous system regulation and provides a physiological marker of attentional engagement that supports cognitive and affective regulatory processes. RSA can be added to executive function (EF) assessments with minimal participant burden because of the commercial availability of lightweight, wearable electrocardiogram (ECG) sensors. However, the inclusion of RSA data in large data collection efforts has been hindered by the time-intensive processing of RSA. In this study we evaluated the performance of an automated RSA-scoring method in the context of an EF study in preschool-aged children. The absolute differences in RSA across both scoring methods were small (mean RSA differences = -0.02-0.10), with little to no evidence of bias for the automated relative to the hand-scoring approach. Moreover, the relative rank-ordering of RSA across both scoring methods was strong (rs = .96-.99). Reliable changes in RSA from baseline to the EF task were highly similar across both scoring methods (96%-100% absolute agreement; Kappa = .83-1.0). On the basis of these findings, the automated RSA algorithm appears to be a suitable substitute for hand-scoring in the context of EF assessment.

Prevalence of atrial arrhythmias in arrhythmogenic right ventricular dysplasia/cardiomyopathy.

PubMed

Camm, Christian F; James, Cynthia A; Tichnell, Crystal; Murray, Brittney; Bhonsale, Aditya; te Riele, Anneline S J M; Judge, Daniel P; Tandri, Harikrishna; Calkins, Hugh

2013-11-01

Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) is an inherited cardiomyopathy, characterized by right ventricular dysfunction and ventricular arrhythmias. Limited information is available concerning atrial arrhythmias in ARVD/C. The purpose of this study was to characterize spontaneous atrial arrhythmias in a large registry population of ARVD/C patients. Patients (n = 248) from the Johns Hopkins ARVD/C registry who met the diagnostic criteria and had undertaken genotype analysis were included. Medical records of each were reviewed to ascertain incidence and characteristics of atrial arrhythmia episodes. Detailed demographic, phenotypic, and structural information was obtained from registry data. Thirty-five patients with ARVD/C (14%) experienced one or more types of atrial arrhythmia during median follow-up of 5.78 (interquartile range 8.52) years. Atrial fibrillation was the most common atrial arrhythmia, occurring in 80% of ARVD/C patients with atrial arrhythmias. Patients developed atrial arrhythmias at a mean age of 43.0 ± 14.0 years. Atrial arrhythmia patients obtained a total of 22 inappropriate implantable cardioverter-defibrillator shocks during follow-up. Older age at last follow-up (P <.001) and male gender (P = .044) were associated with atrial arrhythmia development. Patients with atrial arrhythmias had a higher occurrence of death (P = .028), heart failure (P <.001), and left atrial enlargement on echocardiography (P = .004). Atrial arrhythmias are common in ARVD/C and present at a younger age than in the general population. They are associated with male gender, increasing age, and left atrial enlargement. Atrial arrhythmias are clinically important as they are associated with inappropriate implantable cardioverter-defibrillator shocks and increased risk of both death and heart failure. © 2013 Heart Rhythm Society. All rights reserved.

On Quantitative Biomarkers of VNS Therapy Using EEG and ECG Signals.

PubMed

Ravan, Maryam; Sabesan, Shivkumar; D'Cruz, O'Neill

2017-02-01

The goal of this work is to objectively evaluate the effectiveness of neuromodulation therapies, specifically, Vagus nerve stimulation (VNS) in reducing the severity of seizures in patients with medically refractory epilepsy. Using novel quantitative features obtained from combination of electroencephalographic (EEG) and electrocardiographic (ECG) signals around seizure events in 16 patients who underwent implantation of closed-loop VNS therapy system, namely AspireSR, we evaluated if automated delivery of VNS at the time of seizure onset reduces the severity of seizures by reducing EEG spatial synchronization as well as the duration and magnitude of heart rate increase. Unsupervised classification was subsequently applied to test the discriminative ability and validity of these features to measure responsiveness to VNS therapy. Results of application of this methodology to compare 105 pre-VNS treatment and 107 post-VNS treatment seizures revealed that seizures that were acutely stimulated using VNS had a reduced ictal spread as well as reduced impact on cardiovascular function compared to the ones that occurred prior to any treatment. Furthermore, application of an unsupervised fuzzy-c-mean classifier to evaluate the ability of the combined EEG-ECG based features to classify pre and post-treatment seizures achieved a classification accuracy of 85.85%. These results indicate the importance of timely delivery of VNS to reduce seizure severity and thus help achieve better seizure control for patients with epilepsy. The proposed set of quantitative features could be used as potential biomarkers for predicting long-term response to VNS therapy.

Is exposure to ionising radiation associated with childhood cardiac arrhythmia in the Russian territories contaminated by the Chernobyl fallout? A cross-sectional population-based study

PubMed Central

Clero, Enora; Doroshchenko, Vladimir; Silenok, Aleksandr; Kurnosova, Irina; Butsenin, Andrei; Denjoy, Isabelle; Franck, Didier; Heuze, Jean-Pierre; Gourmelon, Patrick

2018-01-01

Objective To investigate childhood cardiac arrhythmia and chronic exposure to caesium-137 (137Cs) resulting from the Chernobyl accident. Design Prospective cross-sectional study using exposed/unexposed design conducted in the Bryansk region from May 2009 to May 2013 on children selected on the basis of 137Cs soil deposition: control territories ([137Cs]<37 kBq per square metre, where children were considered as unexposed) and contaminated territories ([137Cs]>555 kBq per square metre, where children were considered as exposed). Setting Russian territories affected by the Chernobyl fallout (Bryansk region). Participants This cross-sectional study included 18 152 children aged 2–18 years and living in the Bryansk region (Russia). Main outcome measures All children received three medical examinations (ECG, echocardiography and 137Cs whole-body activity measurement) and some of them were given with a 24-hour Holter monitoring and blood tests. Results Cardiac arrhythmia was diagnosed in 1172 children living in contaminated territories and 1354 children living in control territories. The crude prevalence estimated to 13.3% in contaminated territories was significantly lower than in control territories with 15.2% over the period 2009–2013 (P<0.001). Considering 137Cs whole-body burden as exposure, cardiac arrhythmia was found in 449 contaminated children and 2077 uncontaminated children, corresponding to an estimated crude prevalence of 14.5% and 14.2%, respectively, which does not differ significantly (P=0.74). Also, we investigated the association between territory, exposure to 137Cs and cardiac arrhythmia: the adjusted OR was not significant (0.90 with 95% CI 0.81 to 1.00; P=0.06) for the territory. For 137Cs whole-body burden, the ORs close to 1 did not reach statistical significance (P for trend=0.97). Conclusion This study does not observe an association between cardiac arrhythmia and 137Cs deposition levels in the Bryansk region exposed to Chernobyl

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.

Burden of arrhythmia in recreational marijuana users.

PubMed

Desai, Rupak; Patel, Upenkumar; Deshmukh, Abhishek; Sachdeva, Rajesh; Kumar, Gautam

2018-08-01

Marijuana or Cannabis is extensively used as a recreational substance globally. Case reports have reported cardiac arrhythmias immediately following recreational marijuana use. However, the burden of arrhythmias in hospitalized marijuana users have not been evaluated through prospective or cross-sectional studies. Therefore, we planned to measure temporal trends of the frequency of arrhythmias in hospitalized marijuana users using National Inpatient Sample (NIS) database in the United States. Copyright © 2018 Elsevier B.V. All rights reserved.

High Frequency QRS ECG Accurately Detects Cardiomyopathy

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

An ECG signals compression method and its validation using NNs.

PubMed

Fira, Catalina Monica; Goras, Liviu

2008-04-01

This paper presents a new algorithm for electrocardiogram (ECG) signal compression based on local extreme extraction, adaptive hysteretic filtering and Lempel-Ziv-Welch (LZW) coding. The algorithm has been verified using eight of the most frequent normal and pathological types of cardiac beats and an multi-layer perceptron (MLP) neural network trained with original cardiac patterns and tested with reconstructed ones. Aspects regarding the possibility of using the principal component analysis (PCA) to cardiac pattern classification have been investigated as well. A new compression measure called "quality score," which takes into account both the reconstruction errors and the compression ratio, is proposed.

Management of Arrhythmias in Heart Failure

PubMed Central

Masarone, Daniele; Limongelli, Giuseppe; Rubino, Marta; Valente, Fabio; Vastarella, Rossella; Ammendola, Ernesto; Gravino, Rita; Verrengia, Marina; Salerno, Gemma; Pacileo, Giuseppe

2017-01-01

Heart failure patients are predisposed to develop arrhythmias. Supraventricular arrhythmias can exacerbate the heart failure symptoms by decreasing the effective cardiac output and their control require pharmacological, electrical, or catheter-based intervention. In the setting of atrial flutter or atrial fibrillation, anticoagulation becomes paramount to prevent systemic or cerebral embolism. Patients with heart failure are also prone to develop ventricular arrhythmias that can present a challenge to the managing clinician. The management strategy depends on the type of arrhythmia, the underlying structural heart disease, the severity of heart failure, and the range from optimization of heart failure therapy to catheter ablation. Patients with heart failure, irrespective of ejection fraction are at high risk for developing sudden cardiac death, however risk stratification is a clinical challenge and requires a multiparametric evaluation for identification of patients who should undergo implantation of a cardioverter defibrillator. Finally, patients with heart failure can also develop symptomatic bradycardia, caused by sinus node dysfunction or atrio-ventricular block. The treatment of bradycardia in these patients with pacing is usually straightforward but needs some specific issue. PMID:29367535

Devices for Arrhythmia

MedlinePlus

... with recurrent arrhythmias, medical devices such as a pacemaker and implantable cardioverter defibrillator (ICD) can help by ... with an ICD Questions to ask your doctor Pacemakers Learn what an artificial pacemaker is, how it ...

Cardiac arrhythmias during or after epileptic seizures

PubMed Central

van der Lende, Marije; Surges, Rainer; Sander, Josemir W; Thijs, Roland D

2016-01-01

Seizure-related cardiac arrhythmias are frequently reported and have been implicated as potential pathomechanisms of Sudden Unexpected Death in Epilepsy (SUDEP). We attempted to identify clinical profiles associated with various (post)ictal cardiac arrhythmias. We conducted a systematic search from the first date available to July 2013 on the combination of two terms: ‘cardiac arrhythmias’ and ‘epilepsy’. The databases searched were PubMed, Embase (OVID version), Web of Science and COCHRANE Library. We attempted to identify all case reports and case series. We identified seven distinct patterns of (post)ictal cardiac arrhythmias: ictal asystole (103 cases), postictal asystole (13 cases), ictal bradycardia (25 cases), ictal atrioventricular (AV)-conduction block (11 cases), postictal AV-conduction block (2 cases), (post)ictal atrial flutter/atrial fibrillation (14 cases) and postictal ventricular fibrillation (3 cases). Ictal asystole had a mean prevalence of 0.318% (95% CI 0.316% to 0.320%) in people with refractory epilepsy who underwent video-EEG monitoring. Ictal asystole, bradycardia and AV-conduction block were self-limiting in all but one of the cases and seen during focal dyscognitive seizures. Seizure onset was mostly temporal (91%) without consistent lateralisation. Postictal arrhythmias were mostly found following convulsive seizures and often associated with (near) SUDEP. The contrasting clinical profiles of ictal and postictal arrhythmias suggest different pathomechanisms. Postictal rather than ictal arrhythmias seem of greater importance to the pathophysiology of SUDEP. PMID:26038597

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.

Obstructive sleep apnoea-hypopnoea and arrhythmias: new updates.

PubMed

Vizzardi, Enrico; Sciatti, Edoardo; Bonadei, Ivano; D'Aloia, Antonio; Curnis, Antonio; Metra, Marco

2017-07-01

Obstructive sleep apnoea-hypopnoea (OSAH) is a prevalent condition characterized by repetitive pharyngeal collapse during sleep, leading to hypoxemia, hypercapnia, and persistent inspiratory efforts against an occluded airway until arousal. Several studies demonstrated that OSAH exerts acute and chronic effects on the cardiovascular system. Thus, although being a respiratory problem, the most important consequences of OSAH are cardiovascular, among which there are arrhythmias. The purpose of this review is to systematically analyse what has been recently published about the relationship between OSAH and every cardiac arrhythmia separately. We searched Pubmed, Scopus, Web of Science and Cochrane Collaboration databases for 'OSAHS arrhythmias', 'OSAH arrhythmias' and 'OSA arrhythmias'. We analyse 1298 articles and meta-analyses, excluding already edited reviews. Arrhythmias, especially of ventricular origin, are frequent in OSAH. Ventricular premature beats, couplets and ventricular tachycardia runs are even more frequent in patients suffering from heart failure. They may be due to left heart remodelling, overwork and ischaemia and can explain at least some sudden deaths occurring between midnight and 6 a.m. Sinus pauses and atrioventricular blocks are increased according to the severity of the disturbance and may be reduced by continuous positive airway pressure therapy, preventing pace-maker implantation. Finally, atrial fibrillation, resistance against antiarrhythmic drugs and recurrences after surgical procedures are strongly related to OSAH. Arrhythmias are frequent in OSAH. Treatment of OSAH may reduce some of them. An implantable cardioverter-defibrillator and continuous positive airway pressure should be considered in some patients.

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.

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

Spectroscopic classification of PTSS-18ecg (SN 2018bhb) as a type Ia supernova around maximum

NASA Astrophysics Data System (ADS)

Zhang, Jujia; Ding, Xu; Wang, Xiaofeng; Li, Wenxiong; Li, Bin; Xu, Zhijian; Tan, Hanjie; Zhao, Haibin; Wang, Lifan; Li, Zhitong

2018-05-01

We obtained an optical spectrum (range 350-890 nm) of PTSS-18ecg (SN 2018bhb), discovered by the PMO-Tsinghua Supernova Survey (PTSS, http://www.cneost.org/ptss/), on UT 2018 May 10.7 with the Li-Jiang 2.4 m telescope (LJT+YFOSC) at Li-Jiang Observatory of Yunnan Observatories.

Flexible Graphene Electrodes for Prolonged Dynamic ECG Monitoring

PubMed Central

Lou, Cunguang; Li, Ruikai; Li, Zhaopeng; Liang, Tie; Wei, Zihui; Run, Mingtao; Yan, Xiaobing; Liu, Xiuling

2016-01-01

This paper describes the development of a graphene-based dry flexible electrocardiography (ECG) electrode and a portable wireless ECG measurement system. First, graphene films on polyethylene terephthalate (PET) substrates and graphene paper were used to construct the ECG electrode. Then, a graphene textile was synthesized for the fabrication of a wearable ECG monitoring system. The structure and the electrical properties of the graphene electrodes were evaluated using Raman spectroscopy, scanning electron microscopy (SEM), and alternating current impedance spectroscopy. ECG signals were then collected from healthy subjects using the developed graphene electrode and portable measurement system. The results show that the graphene electrode was able to acquire the typical characteristics and features of human ECG signals with a high signal-to-noise (SNR) ratio in different states of motion. A week-long continuous wearability test showed no degradation in the ECG signal quality over time. The graphene-based flexible electrode demonstrates comfortability, good biocompatibility, and high electrophysiological detection sensitivity. The graphene electrode also combines the potential for use in long-term wearable dynamic cardiac activity monitoring systems with convenience and comfort for use in home health care of elderly and high-risk adults. PMID:27809270

Effect of ECG filter settings on J-waves.

PubMed

Nakagawa, Mikiko; Tsunemitsu, Chie; Katoh, Sayo; Kamiyama, Yukari; Sano, Nario; Ezaki, Kaori; Miyazaki, Hiroko; Teshima, Yasushi; Yufu, Kunio; Takahashi, Naohiko; Saikawa, Tetsunori

2014-01-01

While J-waves were observed in healthy populations, variations in their reported incidence may be partly explicable by the ECG filter setting. We obtained resting 12-lead ECG recordings in 665 consecutive patients and enrolled 112 (56 men, 56 women, mean age 59.3±16.1years) who manifested J-waves on ECGs acquired with a 150-Hz low-pass filter. We then studied the J-waves on individual ECGs to look for morphological changes when 25-, 35-, 75-, 100-, and 150Hz filters were used. The notching observed with the 150-Hz filter changed to slurring (42%) or was eliminated (28%) with the 25-Hz filter. Similarly, the slurring seen with the 150-Hz filter was eliminated on 71% of ECGs recorded with the 25-Hz filter. The amplitude of J-waves was significantly lower with 25- and 35-Hz than 75-, 100-, and 150-Hz filters (p<0.0001). The ECG filter setting significantly affects the J-wave morphology. © 2013.

A new method for QRS detection in ECG signals using QRS-preserving filtering techniques.

PubMed

Sharma, Tanushree; Sharma, Kamalesh K

2018-03-28

Detection of QRS complexes in ECG signals is required for various purposes such as determination of heart rate, feature extraction and classification. The problem of automatic QRS detection in ECG signals is complicated by the presence of noise spectrally overlapping with the QRS frequency range. As a solution to this problem, we propose the use of least-squares-optimisation-based smoothing techniques that suppress the noise peaks in the ECG while preserving the QRS complexes. We also propose a novel nonlinear transformation technique that is applied after the smoothing operations, which equalises the QRS amplitudes without boosting the supressed noise peaks. After these preprocessing operations, the R-peaks can finally be detected with high accuracy. The proposed technique has a low computational load and, therefore, it can be used for real-time QRS detection in a wearable device such as a Holter monitor or for fast offline QRS detection. The offline and real-time versions of the proposed technique have been evaluated on the standard MIT-BIH database. The offline implementation is found to perform better than state-of-the-art techniques based on wavelet transforms, empirical mode decomposition, etc. and the real-time implementation also shows improved performance over existing real-time QRS detection techniques.

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.

Dependency of exercise-induced T-wave alternans predictive power for the occurrence of ventricular arrhythmias from heart rate.

PubMed

Burattini, Laura; Man, Sumche; Fioretti, Sandro; Di Nardo, Francesco; Swenne, Cees A

2015-07-01

T-wave alternans (TWA) is a noninvasive index of risk for the occurrence of ventricular arrhythmias. It is known that TWA amplitude (TWAA) increases with heart rate (HR) but how the TWA predictive power varies with HR remains unknown. Thus, the aim of this study was to evaluate the dependency of exercise-induced TWA predictive power for the occurrence of ventricular arrhythmias from HR. TWA was identified using our HR adaptive match filter in exercise ECGs from 248 patients with implanted cardiac defibrillator (ICD), of which 72 developed ventricular tachycardia and/or fibrillation during the 4 year follow-up (ICD_Cases) and 176 did not (ICD_Controls). TWA predictive power was evaluated at HRs from 80 to 120 bpm by computing the area under the receiver operating characteristic curve (AUC) obtained using the maximum TWAA (maxTWAA) and the TWAA ratio (TWAAratio; i.e., the ratio between TWAA at a specific HR and at 80 bpm). TWAA increased with HR. At 80 bpm maxTWAA was lower than at 120 bpm in both ICD_Cases (22 μV vs 41 μV; P < 10(-2) ) and ICD_ Controls (16 μV vs 36 μV; P < 10(-4) ). However, only at 80 bpm ICD_Cases showed significantly higher maxTWAA than ICD_Controls (AUC = 0.6486; P = 0.0080). TWAAratio was higher in ICD_Controls than ICD_Cases for all HR but 120 bpm, and its predictive power was maximum at 115 bpm (AUC = 0.6914; P < 0.05). Exercise-induced TWA predictive power for the occurrence of ventricular arrhythmias, quantified using both maxTWAA and TWAAratio, was higher at low rather than at high HR. © 2014 Wiley Periodicals, Inc.

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.

Inhalation of diluted diesel engine emission impacts heart rate variability and arrhythmia occurrence in a rat model of chronic ischemic heart failure.

PubMed

Anselme, Frédéric; Loriot, Stéphane; Henry, Jean-Paul; Dionnet, Frédéric; Napoleoni, Jean-Gérard; Thuillez, Christian; Morin, Jean-Paul

2007-04-01

Both increase in cardiac arrhythmia incidence and decrease in heart rate variability (HRV) have been described following human and experimental animal exposures to air pollutants. However, the potential causal relationship between these two factors remains unclear. Incidence of ventricular arrhythmia and HRV were evaluated during and after a 3 h period of Diesel engine exhaust exposure in ten healthy and ten chronic ischemic heart failure (CHF, 3 months after coronary ligation) Wistar rats using implantable ECG telemetry. Air pollutants were delivered to specifically designed whole body individual exposure chambers at particulate matter concentrations similar to those measured inside cabins of cars inserted in congested urban traffic. Recordings were obtained from unrestrained and unsedated vigil rats. Immediate decrease in RMSSD was observed in both healthy (6.64 +/- 2.62 vs. 4.89 +/- 1.67 ms, P < 0.05) and CHF rats (8.01 +/- 0.89 vs. 6.6 +/- 1.37 ms, P < 0.05) following exposure. An immediate 200-500% increase in ventricular premature beats was observed in CHF rats only. Whereas HRV progressively returned to baseline values within 2.5 h after exposure start, the proarrhythmic effect persisted as late as 5 h after exposure termination in CHF rats. Persistence of ventricular proarrhythmic effects after HRV normalization suggests that HRV reduction is not the mechanism of cardiac arrhythmias in this model. Our methodological approach, closely reflecting the real clinical situations, appeared to be a unique tool to provide further insight into the pathophysiological mechanisms of traffic related airborne pollution health impact.

Noncontact ECG system for unobtrusive long-term monitoring.

PubMed

McDonald, Neil J; Anumula, Harini A; Duff, Eric; Soussou, Walid

2012-01-01

This paper describes measurements made using an ECG system with QUASAR's capacitive bioelectrodes integrated into a pad system that is placed over a chair. QUASAR's capacitive bioelectrode has the property of measuring bioelectric potentials at a small separation from the body. This enables the measurement of ECG signals through fabric, without the removal of clothing or preparation of skin. The ECG was measured through the subject's clothing while the subject sat in the chair without any supporting action from the subject. The ECG pad system is an example of a high compliance system that places minimal requirements upon the subject and, consequently, can be used to generate a long-term record from ECG segments collected on a daily basis, providing valuable information on long-term trends in cardiac health.

A 300-mV 220-nW event-driven ADC with real-time QRS detection for wearable ECG sensors.

PubMed

Zhang, Xiaoyang; Lian, Yong

2014-12-01

This paper presents an ultra-low-power event-driven analog-to-digital converter (ADC) with real-time QRS detection for wearable electrocardiogram (ECG) sensors in wireless body sensor network (WBSN) applications. Two QRS detection algorithms, pulse-triggered (PUT) and time-assisted PUT (t-PUT), are proposed based on the level-crossing events generated from the ADC. The PUT detector achieves 97.63% sensitivity and 97.33% positive prediction in simulation on the MIT-BIH Arrhythmia Database. The t-PUT improves the sensitivity and positive prediction to 97.76% and 98.59% respectively. Fabricated in 0.13 μm CMOS technology, the ADC with QRS detector consumes only 220 nW measured under 300 mV power supply, making it the first nanoWatt compact analog-to-information (A2I) converter with embedded QRS detector.

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.

Is exposure to ionising radiation associated with childhood cardiac arrhythmia in the Russian territories contaminated by the Chernobyl fallout? A cross-sectional population-based study.

PubMed

Jourdain, Jean-Rene; Landon, Geraldine; Clero, Enora; Doroshchenko, Vladimir; Silenok, Aleksandr; Kurnosova, Irina; Butsenin, Andrei; Denjoy, Isabelle; Franck, Didier; Heuze, Jean-Pierre; Gourmelon, Patrick

2018-03-25

To investigate childhood cardiac arrhythmia and chronic exposure to caesium-137 ( 137 Cs) resulting from the Chernobyl accident. Prospective cross-sectional study using exposed/unexposed design conducted in the Bryansk region from May 2009 to May 2013 on children selected on the basis of 137 Cs soil deposition: control territories ([ 137 Cs]<37 kBq per square metre, where children were considered as unexposed) and contaminated territories ([ 137 Cs]>555 kBq per square metre, where children were considered as exposed). Russian territories affected by the Chernobyl fallout (Bryansk region). This cross-sectional study included 18 152 children aged 2-18 years and living in the Bryansk region (Russia). All children received three medical examinations (ECG, echocardiography and 137 Cs whole-body activity measurement) and some of them were given with a 24-hour Holter monitoring and blood tests. Cardiac arrhythmia was diagnosed in 1172 children living in contaminated territories and 1354 children living in control territories. The crude prevalence estimated to 13.3% in contaminated territories was significantly lower than in control territories with 15.2% over the period 2009-2013 (P<0.001). Considering 137 Cs whole-body burden as exposure, cardiac arrhythmia was found in 449 contaminated children and 2077 uncontaminated children, corresponding to an estimated crude prevalence of 14.5% and 14.2%, respectively, which does not differ significantly (P=0.74). Also, we investigated the association between territory, exposure to 137 Cs and cardiac arrhythmia: the adjusted OR was not significant (0.90 with 95% CI 0.81 to 1.00; P=0.06) for the territory. For 137 Cs whole-body burden, the ORs close to 1 did not reach statistical significance (P for trend=0.97). This study does not observe an association between cardiac arrhythmia and 137 Cs deposition levels in the Bryansk region exposed to Chernobyl fallout. The suspected increase of cardiac arrhythmia in children exposed to

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.

Postmortem ICD interrogation in mode of death classification.

PubMed

Nikolaidou, Theodora; Johnson, Miriam J; Ghosh, Justin M; Marincowitz, Carl; Shah, Saumil; Lammiman, Michael J; Schilling, Richard J; Clark, Andrew L

2018-04-01

The definition of sudden death due to arrhythmia relies on the time interval between onset of symptoms and death. However, not all sudden deaths are due to arrhythmia. In patients with an implantable cardioverter defibrillator (ICD), postmortem device interrogation may help better distinguish the mode of death compared to a time-based definition alone. This study aims to assess the proportion of "sudden" cardiac deaths in patients with an ICD that have confirmed arrhythmia. We conducted a literature search for studies using postmortem ICD interrogation and a time-based classification of the mode of death. A modified QUADAS-2 checklist was used to assess risk of bias in individual studies. Outcome data were pooled where sufficient data were available. Our search identified 22 studies undertaken between 1982 and 2015 with 23,600 participants. The pooled results (excluding studies with high risk of bias) suggest that ventricular arrhythmias are present at the time of death in 76% of "sudden" deaths (95% confidence interval [CI] 67-85; range 42-88). Postmortem ICD interrogation identifies 24% of "sudden" deaths to be nonarrhythmic. Postmortem device interrogation should be considered in all cases of unexplained sudden cardiac death. © 2018 Wiley Periodicals, Inc.

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.

Freeware eLearning Flash-ECG for learning electrocardiography.

PubMed

Romanov, Kalle; Kuusi, Timo

2009-06-01

Electrocardiographic (ECG) analysis can be taught in eLearning programmes with suitable software that permits the effective use of basic tools such as a ruler and a magnifier, required for measurements. The Flash-ECG (Research & Development Unit for Medical Education, University of Helsinki, Finland) was developed to enable teachers and students to use scanned and archived ECGs on computer screens and classroom projectors. The software requires only a standard web browser with a Flash plug-in and can be integrated with learning environments (Blackboard/WebCT, Moodle). The Flash-ECG is freeware and is available to medical teachers worldwide.

A cloud computing based 12-lead ECG telemedicine service

PubMed Central

2012-01-01

Background Due to the great variability of 12-lead ECG instruments and medical specialists’ interpretation skills, it remains a challenge to deliver rapid and accurate 12-lead ECG reports with senior cardiologists’ decision making support in emergency telecardiology. Methods We create a new cloud and pervasive computing based 12-lead Electrocardiography (ECG) service to realize ubiquitous 12-lead ECG tele-diagnosis. Results This developed service enables ECG to be transmitted and interpreted via mobile phones. That is, tele-consultation can take place while the patient is on the ambulance, between the onsite clinicians and the off-site senior cardiologists, or among hospitals. Most importantly, this developed service is convenient, efficient, and inexpensive. Conclusions This cloud computing based ECG tele-consultation service expands the traditional 12-lead ECG applications onto the collaboration of clinicians at different locations or among hospitals. In short, this service can greatly improve medical service quality and efficiency, especially for patients in rural areas. This service has been evaluated and proved to be useful by cardiologists in Taiwan. PMID:22838382

SPEAR Trial: Smartphone Pediatric ElectrocARdiogram Trial

PubMed Central

Nguyen, Hoang H.; Van Hare, George F.; Rudokas, Michael; Bowman, Tammy; Silva, Jennifer N. A.

2015-01-01

Objectives Smartphone-enabled ECG devices have the potential to improve patient care by enabling remote ECG assessment of patients with potential and diagnosed arrhythmias. This prospective study aimed to assess the usefulness of pediatric ECG tracings generated by the AliveCor device (Oklahoma City, OK) and to assess user satisfaction. Study Design Enrolled pediatric patients with documented paroxysmal arrhythmia used the AliveCor device over a yearlong study period. Pediatric electrophysiologists reviewed all transmitted ECG tracings. Patient completed surveys were analyzed to assess user satisfaction. Results 35 patients were enrolled with the following diagnoses: supraventricular tachycardia (SVT, 57%), atrial fibrillation (AF, 11%), ectopic atrial tachycardia (EAT, 6%), atrial tachycardia (AT, 3%), and ventricular tachycardia (VT, 23%). A total of 238 tracings were received from 20 patients, 96% of which were of diagnostic quality for sinus rhythm, sinus tachycardia, SVT, and AF. 126 patient satisfaction surveys (64% from parents) were completed. 98% of the survey responses indicated that it was easy to obtain tracings, 93% found it easy to transmit the tracings, 98% showed added comfort in managing arrhythmia by having the device, and 93% showed interest in continued use of the device after the study period ended. Conclusions Smartphone-enabled ECG devices can generate tracings of diagnostic quality in children. User satisfaction was extremely positive. Use of the device to manage certain patients with AF and SVT showcases the future role of remote ECGs in the successful outpatient management of arrhythmias in children by potentially reducing Emergency Department visits and healthcare costs. PMID:26295569

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.

Effects of Heterogeneous Diffuse Fibrosis on Arrhythmia Dynamics and Mechanism

PubMed Central

Kazbanov, Ivan V.; ten Tusscher, Kirsten H. W. J.; Panfilov, Alexander V.

2016-01-01

Myocardial fibrosis is an important risk factor for cardiac arrhythmias. Previous experimental and numerical studies have shown that the texture and spatial distribution of fibrosis may play an important role in arrhythmia onset. Here, we investigate how spatial heterogeneity of fibrosis affects arrhythmia onset using numerical methods. We generate various tissue textures that differ by the mean amount of fibrosis, the degree of heterogeneity and the characteristic size of heterogeneity. We study the onset of arrhythmias using a burst pacing protocol. We confirm that spatial heterogeneity of fibrosis increases the probability of arrhythmia induction. This effect is more pronounced with the increase of both the spatial size and the degree of heterogeneity. The induced arrhythmias have a regular structure with the period being mostly determined by the maximal local fibrosis level. We perform ablations of the induced fibrillatory patterns to classify their type. We show that in fibrotic tissue fibrillation is usually of the mother rotor type but becomes of the multiple wavelet type with increase in tissue size. Overall, we conclude that the most important factor determining the formation and dynamics of arrhythmia in heterogeneous fibrotic tissue is the value of maximal local fibrosis. PMID:26861111

Growth Factor-Induced Mobilization of Cardiac Progenitor Cells Reduces the Risk of Arrhythmias, in a Rat Model of Chronic Myocardial Infarction

PubMed Central

Graiani, Gallia; Rossi, Stefano; Agnetti, Aldo; Stillitano, Francesca; Lagrasta, Costanza; Baruffi, Silvana; Berni, Roberta; Frati, Caterina; Vassalle, Mario; Squarcia, Umberto; Cerbai, Elisabetta; Macchi, Emilio; Stilli, Donatella; Quaini, Federico; Musso, Ezio

2011-01-01

Heart repair by stem cell treatment may involve life-threatening arrhythmias. Cardiac progenitor cells (CPCs) appear best suited for reconstituting lost myocardium without posing arrhythmic risks, being commissioned towards cardiac phenotype. In this study we tested the hypothesis that mobilization of CPCs through locally delivered Hepatocyte Growth Factor and Insulin-Like Growth Factor-1 to heal chronic myocardial infarction (MI), lowers the proneness to arrhythmias. We used 133 adult male Wistar rats either with one-month old MI and treated with growth factors (GFs, n = 60) or vehicle (V, n = 55), or sham operated (n = 18). In selected groups of animals, prior to and two weeks after GF/V delivery, we evaluated stress-induced ventricular arrhythmias by telemetry-ECG, cardiac mechanics by echocardiography, and ventricular excitability, conduction velocity and refractoriness by epicardial multiple-lead recording. Invasive hemodynamic measurements were performed before sacrifice and eventually the hearts were subjected to anatomical, morphometric, immunohistochemical, and molecular biology analyses. When compared with untreated MI, GFs decreased stress-induced arrhythmias and concurrently prolonged the effective refractory period (ERP) without affecting neither the duration of ventricular repolarization, as suggested by measurements of QTc interval and mRNA levels for K-channel α-subunits Kv4.2 and Kv4.3, nor the dispersion of refractoriness. Further, markers of cardiomyocyte reactive hypertrophy, including mRNA levels for K-channel α-subunit Kv1.4 and β-subunit KChIP2, interstitial fibrosis and negative structural remodeling were significantly reduced in peri-infarcted/remote ventricular myocardium. Finally, analyses of BrdU incorporation and distribution of connexin43 and N-cadherin indicated that cytokines generated new vessels and electromechanically-connected myocytes and abolished the correlation of infarct size with deterioration of mechanical

Paroxysmal atrial fibrillation recognition based on multi-scale Rényi entropy of ECG.

PubMed

Xin, Yi; Zhao, Yizhang; Mu, Yuanhui; Li, Qin; Shi, Caicheng

2017-07-20

Atrial fibrillation (AF) is a common type of arrhythmia disease, which has a high morbidity and can lead to some serious complications. The ability to detect and in turn prevent AF is extremely significant to the patient and clinician. Using ECG to detect AF and develop a robust and effective algorithm is the primary objective of this study. Some studies show that after AF occurs, the regulatory mechanism of vagus nerve and sympathetic nerve will change. Each R-R interval will be absolutely unequal. After studying the physiological mechanism of AF, we will calculate the Rényi entropy of the wavelet coefficients of heart rate variability (HRV) in order to measure the complexity of PAF signals, as well as extract the multi-scale features of paroxysmal atrial fibrillation (PAF). The data used in this study is obtained from MIT-BIH PAF Prediction Challenge Database and the correct rate in classifying PAF patients from normal persons is 92.48%. The results of this experiment proved that AF could be detected by using this method and, in turn, provide opinions for clinical diagnosis.

[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.

[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.

The Renin-Angiotensin-Aldosterone System (RAAS) and Cardiac Arrhythmias

PubMed Central

Iravanian, Shahriar; Dudley, Samuel C.

2008-01-01

The role of the renin-angiotensin-aldosterone system (RAAS) in many cardiovascular disorders, including hypertension, cardiac hypertrophy, and atherosclerosis is well established, whereas its relationship with cardiac arrhythmias is a new area of investigation. Atrial fibrillation and malignant ventricular tachyarrhythmias, especially in the setting of cardiac hypertrophy or failure, appear to be examples of RAAS-related arrhythmias, since treatment with RAAS modulators, including angiotensin converting enzyme inhibitors, angiotensin receptor blockers and mineralocorticoid receptor blockers, reduces the incidence of these arrhythmias. RAAS has a multitude of electrophysiological effects and can potentially cause arrhythmia through a variety of mechanisms. We review new experimental results that suggest RAAS has pro-arrhythmic effects on membrane and sarcoplasmic reticulum ion channels and that increased oxidative stress is likely contributing to the increased arrhythmic incidence. A summary of ongoing clinical trials that will address the clinical usefulness of RAAS modulators for prevention or treatment of arrhythmias is presented. PMID:18456194

The renin-angiotensin-aldosterone system (RAAS) and cardiac arrhythmias.

PubMed

Iravanian, Shahriar; Dudley, Samuel C

2008-06-01

The role of the renin-angiotensin-aldosterone system (RAAS) in many cardiovascular disorders, including hypertension, cardiac hypertrophy, and atherosclerosis, is well established, whereas its relationship with cardiac arrhythmias is a new area of investigation. Atrial fibrillation and malignant ventricular tachyarrhythmias, especially in the setting of cardiac hypertrophy or failure, seem to be examples of RAAS-related arrhythmias because treatment with RAAS modulators, including angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and mineralocorticoid receptor blockers, reduces the incidence of these arrhythmias. RAAS has a multitude of electrophysiological effects and can potentially cause arrhythmia through a variety of mechanisms. We review new experimental results that suggest that RAAS has proarrhythmic effects on membrane and sarcoplasmic reticulum ion channels and that increased oxidative stress is likely contributing to the increased arrhythmic incidence. A summary of ongoing clinical trials that will address the clinical usefulness of RAAS modulators for prevention or treatment of arrhythmias is presented.

Novel non-invasive algorithm to identify the origins of re-entry and ectopic foci in the atria from 64-lead ECGs: A computational study.

PubMed

Alday, Erick A Perez; Colman, Michael A; Langley, Philip; Zhang, Henggui

2017-03-01

Atrial tachy-arrhytmias, such as atrial fibrillation (AF), are characterised by irregular electrical activity in the atria, generally associated with erratic excitation underlain by re-entrant scroll waves, fibrillatory conduction of multiple wavelets or rapid focal activity. Epidemiological studies have shown an increase in AF prevalence in the developed world associated with an ageing society, highlighting the need for effective treatment options. Catheter ablation therapy, commonly used in the treatment of AF, requires spatial information on atrial electrical excitation. The standard 12-lead electrocardiogram (ECG) provides a method for non-invasive identification of the presence of arrhythmia, due to irregularity in the ECG signal associated with atrial activation compared to sinus rhythm, but has limitations in providing specific spatial information. There is therefore a pressing need to develop novel methods to identify and locate the origin of arrhythmic excitation. Invasive methods provide direct information on atrial activity, but may induce clinical complications. Non-invasive methods avoid such complications, but their development presents a greater challenge due to the non-direct nature of monitoring. Algorithms based on the ECG signals in multiple leads (e.g. a 64-lead vest) may provide a viable approach. In this study, we used a biophysically detailed model of the human atria and torso to investigate the correlation between the morphology of the ECG signals from a 64-lead vest and the location of the origin of rapid atrial excitation arising from rapid focal activity and/or re-entrant scroll waves. A focus-location algorithm was then constructed from this correlation. The algorithm had success rates of 93% and 76% for correctly identifying the origin of focal and re-entrant excitation with a spatial resolution of 40 mm, respectively. The general approach allows its application to any multi-lead ECG system. This represents a significant extension to

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.

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.

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.

Ventricular Arrhythmias in the North American Multidisciplinary Study of ARVC

PubMed Central

Link, Mark S.; Laidlaw, Douglas; Polonsky, Bronislava; Zareba, Wojciech; McNitt, Scott; Gear, Kathleen; Marcus, Frank; Mark Estes, NA

2015-01-01

BACKGROUND Arrhythmogenic right ventricular cardiomyopathy (ARVC) is associated with sudden cardiac death. However, the selection of patients for implanted cardioverter-defibrillators (ICDs), as well as programming of the ICD, is unclear. OBJECTIVES The objective of this study was to identify predictors, characteristics, and treatment of ventricular arrhythmias in patients with ARVC. METHODS The Multidisciplinary Study of Right Ventricular Cardiomyopathy established the North American ARVC Registry and enrolled patients with a diagnosis of ARVC. Patients were followed prospectively. RESULTS Of 137 patients enrolled, 108 received ICDs. Forty-eight patients had 502 sustained episodes of ventricular arrhythmias, including 489 that were monomorphic and 13 that were polymorphic. In the patients with ICDs, independent predictors of ventricular arrhythmias in follow-up included spontaneous sustained ventricular arrhythmias before ICD implantation and T-wave inversions inferiorly. The only independent predictor for life-threatening arrhythmias, defined as sustained ventricular tachycardia (VT) ≥240 beats/min or ventricular fibrillation, was a younger age at enrollment. Anti-tachycardia pacing (ATP), independent of the cycle length of the VT, was successful in terminating 92% of VT episodes. CONCLUSIONS In the North American ARVC Registry, the majority of ventricular arrhythmias in follow-up are monomorphic. Risk factors for ventricular arrhythmias were spontaneous ventricular arrhythmias before enrollment and a younger age at ICD implantation. ATP is highly successful in terminating VT, and all ICDs should be programmed for ATP, even for rapid VT. PMID:25011714

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.

Statistical sensor fusion of ECG data using automotive-grade sensors

NASA Astrophysics Data System (ADS)

Koenig, A.; Rehg, T.; Rasshofer, R.

2015-11-01

Driver states such as fatigue, stress, aggression, distraction or even medical emergencies continue to be yield to severe mistakes in driving and promote accidents. A pathway towards improving driver state assessment can be found in psycho-physiological measures to directly quantify the driver's state from physiological recordings. Although heart rate is a well-established physiological variable that reflects cognitive stress, obtaining heart rate contactless and reliably is a challenging task in an automotive environment. Our aim was to investigate, how sensory fusion of two automotive grade sensors would influence the accuracy of automatic classification of cognitive stress levels. We induced cognitive stress in subjects and estimated levels from their heart rate signals, acquired from automotive ready ECG sensors. Using signal quality indices and Kalman filters, we were able to decrease Root Mean Squared Error (RMSE) of heart rate recordings by 10 beats per minute. We then trained a neural network to classify the cognitive workload state of subjects from heart rate and compared classification performance for ground truth, the individual sensors and the fused heart rate signal. We obtained an increase of 5 % higher correct classification by fusing signals as compared to individual sensors, staying only 4 % below the maximally possible classification accuracy from ground truth. These results are a first step towards real world applications of psycho-physiological measurements in vehicle settings. Future implementations of driver state modeling will be able to draw from a larger pool of data sources, such as additional physiological values or vehicle related data, which can be expected to drive classification to significantly higher values.

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.

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

PubMed

Poggi, Elena; Giannattasio, Alessandro; Bolloli, Sara; Beccaria, Andrea; Mezzano, Paola; Rocca, Paola; Del Vecchio, Cecilia

2016-11-01

Sport is very important for health promotion and conservation. Active lifestyle and regular exercise reduce cardiovascular disease incidence. The Italian Ministry of Health issued the Law Decree no. 243 (10/18/2014) concerning "guidelines for certification about non-competitive sports" to promote safety in sports. This regulation defines the activities for which a certificate is required, the professional actors involved and the clinical exams to be performed according to the patient's health status. In particular, the Law Decree recommends to perform an electrocardiogram (ECG) "at least once in a lifetime", introducing much greater news into pediatric practice. We proposed a survey evaluating frequency of ECG implementation for non-competitive sports and cardiovascular diseases incidence was administered to 7 Ligurian pediatricians. The number of ECG/year for pediatrician increased from 10 ECG/year to 50 ECG/year with an indication of suitability to non-competitive sports. One case of QT prolongation and 2 cases of type 1 Brugada ECG pattern were diagnosed. In addition, 3 patients had an atrial septal defect and 3 children had a ventricular septal defect. Forty-three percent of the pediatricians considered useful performing the ECG. ECG in children has enhanced the positive effects on the community health. However, it remains to be defined in agreement with scientific societies the age at which to perform ECG, the sports for which ECG is required and the cost-benefit ratio for the National Health System and families.

Unveiling the Biometric Potential of Finger-Based ECG Signals

PubMed Central

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications. PMID:21837235

Unveiling the biometric potential of finger-based ECG signals.

PubMed

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

A novel biometric authentication approach using ECG and EMG signals.

PubMed

Belgacem, Noureddine; Fournier, Régis; Nait-Ali, Amine; Bereksi-Reguig, Fethi

2015-05-01

Security biometrics is a secure alternative to traditional methods of identity verification of individuals, such as authentication systems based on user name and password. Recently, it has been found that the electrocardiogram (ECG) signal formed by five successive waves (P, Q, R, S and T) is unique to each individual. In fact, better than any other biometrics' measures, it delivers proof of subject's being alive as extra information which other biometrics cannot deliver. The main purpose of this work is to present a low-cost method for online acquisition and processing of ECG signals for person authentication and to study the possibility of providing additional information and retrieve personal data from an electrocardiogram signal to yield a reliable decision. This study explores the effectiveness of a novel biometric system resulting from the fusion of information and knowledge provided by ECG and EMG (Electromyogram) physiological recordings. It is shown that biometrics based on these ECG/EMG signals offers a novel way to robustly authenticate subjects. Five ECG databases (MIT-BIH, ST-T, NSR, PTB and ECG-ID) and several ECG signals collected in-house from volunteers were exploited. A palm-based ECG biometric system was developed where the signals are collected from the palm of the subject through a minimally intrusive one-lead ECG set-up. A total of 3750 ECG beats were used in this work. Feature extraction was performed on ECG signals using Fourier descriptors (spectral coefficients). Optimum-Path Forest classifier was used to calculate the degree of similarity between individuals. The obtained results from the proposed approach look promising for individuals' authentication.

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.

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

Decreased heart rate and enhanced sinus arrhythmia during interictal sleep demonstrate autonomic imbalance in generalized epilepsy

PubMed Central

Sivakumar, Siddharth S.; Namath, Amalia G.; Tuxhorn, Ingrid E.; Lewis, Stephen J.

2016-01-01

We hypothesized that epilepsy affects the activity of the autonomic nervous system even in the absence of seizures, which should manifest as differences in heart rate variability (HRV) and cardiac cycle. To test this hypothesis, we investigated ECG traces of 91 children and adolescents with generalized epilepsy and 25 neurologically normal controls during 30 min of stage 2 sleep with interictal or normal EEG. Mean heart rate (HR) and high-frequency HRV corresponding to respiratory sinus arrhythmia (RSA) were quantified and compared. Blood pressure (BP) measurements from physical exams of all subjects were also collected and analyzed. RSA was on average significantly stronger in patients with epilepsy, whereas their mean HR was significantly lower after adjusting for age, body mass index, and sex, consistent with increased parasympathetic tone in these patients. In contrast, diastolic (and systolic) BP at rest was not significantly different, indicating that the sympathetic tone is similar. Remarkably, five additional subjects, initially diagnosed as neurologically normal but with enhanced RSA and lower HR, eventually developed epilepsy, suggesting that increased parasympathetic tone precedes the onset of epilepsy in children. ECG waveforms in epilepsy also displayed significantly longer TP intervals (ventricular diastole) relative to the RR interval. The relative TP interval correlated positively with RSA and negatively with HR, suggesting that these parameters are linked through a common mechanism, which we discuss. Altogether, our results provide evidence for imbalanced autonomic function in generalized epilepsy, which may be a key contributing factor to sudden unexpected death in epilepsy. PMID:26888110

Biometric and Emotion Identification: An ECG Compression Based Method

PubMed Central

Brás, Susana; Ferreira, Jacqueline H. T.; Soares, Sandra C.; Pinho, Armando J.

2018-01-01

We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model. PMID:29670564

The Development of a Portable ECG Monitor Based on DSP

NASA Astrophysics Data System (ADS)

Nan, CHI Jian; Tao, YAN Yan; Meng Chen, LIU; Li, YANG

With the advent of global information, researches of Smart Home system are in the ascendant, the ECG real-time detection, and wireless transmission of ECG become more useful. In order to achieve the purpose we developed a portable ECG monitor which achieves the purpose of cardiac disease remote monitoring, and will be used in the physical and psychological disease surveillance in smart home system, we developed this portable ECG Monitor, based on the analysis of existing ECG Monitor, using TMS320F2812 as the core controller, which complete the signal collection, storage, processing, waveform display and transmission.

Arrhythmias in Patients with Atrial Defects.

PubMed

Contractor, Tahmeed; Mandapati, Ravi

2017-06-01

Atrial arrhythmias are common in patients with atrial septal defects. A myriad of factors are responsible for these that include remodeling related to the defect and scar created by the repair or closure. An understanding of potential arrhythmias, along with entrainment and high-density activation mapping can result in accurate diagnosis and successful ablation. Atrial fibrillation is being seen increasingly after patent foramen ovale closure and may be the primary etiology of recurrent stroke in these patients. Copyright © 2017 Elsevier Inc. 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.

Cardiac arrhythmias during exercise testing in healthy men.

NASA Technical Reports Server (NTRS)

Beard, E. F.; Owen, C. A.

1973-01-01

Clinically healthy male executives who participate in a long-term physical conditioning program have demonstrated cardiac arrhythmia during and after periodic ergometric testing at submaximal and maximal levels. In 1,385 tests on 248 subjects, it was found that 34% of subjects demonstrated an arrhythmia at some time and 13% of subjects developed arrhythmia on more than one test. Premature systoles of ventricular origin were most common, but premature systoles of atrial origin, premature systoles of junctional origin, paroxysmal atrial tachycardia, atrioventricular block, wandering pacemaker, and pre-excitation were also seen. Careful post-test monitoring and pulse rate regulated training sessions are suggested for such programs.

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).

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.

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.

Management of supraventricular arrhythmias in adults with congenital heart disease.

PubMed

Wasmer, Kristina; Eckardt, Lars

2016-10-15

Supraventricular arrhythmias are a frequent complication in adults with congenital heart disease (ACHD). The prevalence increases with time since surgery, complexity of the underlying defect, type of repair and older age at surgery. Arrhythmias are the most frequent reason for hospital admission and along with heart failure the leading cause of death. The arrhythmia-associated increase in morbidity and mortality makes their management a key task in patients with ACHD. Intra-atrial re-entry is the most frequent arrhythmia mechanism. Less common arrhythmia mechanisms are supraventricular tachycardias in the presence of an accessory pathway, atrioventricular nodal re-entrant tachycardia or focal tachycardias. Patient management includes stroke prevention, acute termination and prevention of arrhythmia recurrence. Acute treatment depends on patients' symptoms. In cases of haemodynamic instability, immediate cardioversion is warranted. For stable patients, acute treatment includes rate control and termination by antiarrhythmic drugs or electrical cardioversion. Following a symptomatic arrhythmia, catheter ablation or treatment with antiarrhythmic drugs is recommended to prevent recurrences. Advances in mapping and ablation technology are now associated with high success rates of catheter ablation. In patients with a complex substrate recurrence rates of 50% remain high. However, in the presence of side effects and complications associated with long-term antiarrhythmic drug therapy, redo procedures are encouraged by current guidelines. 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/

Etiological diagnosis, prognostic significance and role of electrophysiological study in patients with Brugada ECG and syncope.

PubMed

Giustetto, Carla; Cerrato, Natascia; Ruffino, Enrico; Gribaudo, Elena; Scrocco, Chiara; Barbonaglia, Lorella; Bianchi, Francesca; Bortnik, Miriam; Rossetti, Guido; Carvalho, Paula; Riccardi, Riccardo; Castagno, Davide; Anselmino, Matteo; Bergamasco, Laura; Gaita, Fiorenzo

2017-08-15

Syncope is considered a risk factor for life-threatening arrhythmias in Brugada patients. Distinguishing a benign syncope from one due to ventricular arrhythmias is often difficult, unless an ECG is recorded during the episode. Aim of the study was to analyze the characteristics of syncopal episodes in a large population of Brugada patients and evaluate the role of electrophysiological study (EPS) and the prognosis in the different subgroups. One hundred ninety-five Brugada patients with history of syncope were considered. Syncope were classified as neurally mediated (group 1, 61%) or unexplained (group 2, 39%) on the basis of personal and family history, clinical features, triggers, situations, associated signs, concomitant therapy. Most patients underwent EPS; they received ICD or implantable loop-recorder on the basis of the result of investigations and physician's judgment. At 62±45months of mean follow-up, group 1 showed a significantly lower incidence of arrhythmic events (2%) as compared to group 2 (9%, p<0.001). Group 2 patients with positive EPS showed the highest risk of arrhythmic events (27%). No ventricular events occurred in subjects with negative EPS. Etiological definition of syncope in Brugada patients is important, as it allows identifying two groups with different outcome. Patients with unexplained syncope and ventricular fibrillation induced at EPS have the highest risk of arrhythmic events. Patients presenting with neurally mediated syncope showed a prognosis similar to that of the asymptomatic and the role of EPS in this group is unproven. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

[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.

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.

Atrial Arrhythmias in Astronauts. Summary of a NASA Summit

NASA Technical Reports Server (NTRS)

Barr, Yael; Watkins, Sharmila; Polk, J. D.

2011-01-01

This slide presentation reviews the findings of a panel of heart experts brought together to study if atrial arrhythmias more prevalent in astronauts, and potential risk factors that may predispose astronauts to atrial arrhythmias. The objective of the panel was to solicit expert opinion on screening, diagnosis, and treatment options, identify gaps in knowledge, and propose relevant research initiatives. While Atrial Arrhythmias occur in approximately the same percents in astronauts as in the general population, they seem to occur at younger ages in astronauts. Several reasons for this predisposition were given: gender, hypertension, endurance training, and triggering events. Potential Space Flight-Related Risk factors that may play a role in precipitating lone atrial fibrillation were reviewed. There appears to be no evidence that any variable of the space flight environment increases the likelihood of developing atrial arrhythmias during space flight.

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

Emerging molecular therapies targeting myocardial infarction-related arrhythmias.

PubMed

Driessen, Helen E; van Veen, Toon A B; Boink, Gerard J J

2017-04-01

Cardiac disease is the leading cause of death in the developed world. Ventricular arrhythmias associated with myocardial ischaemia and/or infarction are a major contributor to cardiovascular mortality, and require improved prevention and treatment. Drugs, devices, and radiofrequency catheter ablation have made important inroads, but have significant limitations ranging from incomplete success to undesired toxicities and major side effects. These limitations derive from the nature of the intervention. Drugs are frequently ineffective, target the entire heart, and often do not deal with the specific arrhythmia trigger or substrate. Devices can terminate rapid rhythms but at best indirectly affect the underlying disease, while ablation, even when appropriately targeted, induces additional tissue damage. In contrast, exploration of gene and cell therapies are expected to provide a targeted, non-destructive, and potentially regenerative approach to ischaemia- and infarction-related arrhythmias. Although these approaches are in the early stages of development, they carry substantial potential to advance arrhythmia prevention and treatment. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For permissions please email: journals.permissions@oup.com.

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.

[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.

Software design of a remote real-time ECG monitoring system

NASA Astrophysics Data System (ADS)

Yu, Chengbo; Tao, Hongyan

2005-12-01

Heart disease is one of the main diseases that threaten the health and lives of human beings. At present, the normal remote ECG monitoring system has the disadvantages of a short testing distance and limitation of monitoring lines. Because of accident and paroxysmal disease, ECG monitoring has extended from the hospital to the family. Therefore, remote ECG monitoring through the Internet has the actual value and significance. The principle and design method of software of the remote dynamic ECG monitor was presented and discussed. The monitoring software is programmed with Delphi software based on client-sever interactive mode. The application program of the system, which makes use of multithreading technology, is shown to perform in an excellent manner. The program includes remote link users and ECG processing, i.e. ECG data's receiving, real-time displaying, recording and replaying. The system can connect many clients simultaneously and perform real-time monitoring to patients.

Cardiac arrhythmia induced by interferon beta-1a.

PubMed

Kastalli, Sarrah; El Aïdli, Sihem; Mourali, Sami; Zaïem, Ahmed; Daghfous, Riadh; Lakhal, Mohamed

2012-04-01

Cardiac adverse effects have never been reported with interferon (INF) beta. We report a case of left bundle branch block in a 35-year-old woman treated with INF beta-1a for multiple sclerosis. Five years after INF therapy, she presented loss of consciousness, retrosternal pains, short breath and lowered tolerance of effort. ECG and Holter 24-h ECG monitoring revealed permanent complete left bundle branch block. Nine months after stopping INF, no abnormalities were found at ECG and echocardiogram examination. © 2011 The Authors Fundamental and Clinical Pharmacology © 2011 Société Française de Pharmacologie et de Thérapeutique.

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.

ECG fiducial point extraction using switching Kalman filter.

PubMed

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

2018-04-01

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

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

PubMed Central

Green, Cynthia L.; Kligfield, Paul; George, Samuel; Gussak, Ihor; Vajdic, Branislav; Sager, Philip; Krucoff, Mitchell W.

2013-01-01

Background The Cardiac Safety Research Consortium (CSRC) provides both “learning” and blinded “testing” digital ECG datasets from thorough QT (TQT) studies annotated for submission to the US Food and Drug Administration (FDA) to developers of ECG analysis technologies. This manuscript reports the first results from a blinded “testing” dataset that examines Developer re-analysis of original Sponsor-reported core laboratory data. Methods 11,925 anonymized ECGs including both moxifloxacin and placebo arms of a parallel-group TQT in 191 subjects were blindly analyzed using a novel ECG analysis algorithm applying intelligent automation. Developer measured ECG intervals were submitted to CSRC for unblinding, temporal reconstruction of the TQT exposures, and statistical comparison to core laboratory findings previously submitted to FDA by the pharmaceutical sponsor. Primary comparisons included baseline-adjusted interval measurements, baseline- and placebo-adjusted moxifloxacin QTcF changes (ddQTcF), and associated variability measures. Results Developer and Sponsor-reported baseline-adjusted data were similar with average differences less than 1 millisecond (ms) for all intervals. Both Developer and Sponsor-reported data demonstrated assay sensitivity with similar ddQTcF changes. Average within-subject standard deviation for triplicate QTcF measurements was significantly lower for Developer than Sponsor-reported data (5.4 ms and 7.2 ms, respectively; p<0.001). Conclusion The virtually automated ECG algorithm used for this analysis produced similar yet less variable TQT results compared to the Sponsor-reported study, without the use of a manual core laboratory. These findings indicate CSRC ECG datasets can be useful for evaluating novel methods and algorithms for determining QT/QTc prolongation by drugs. While the results should not constitute endorsement of specific algorithms by either CSRC or FDA, the value of a public domain digital ECG warehouse to

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

PubMed

Shihui Yin; Chisung Bae; Sang Joon Kim; Jae-Sun Seo

2017-07-01

As a plethora of wearable devices are being introduced, significant concerns exist on the privacy and security of personal data stored on these devices. Expanding on recent works of using electrocardiogram (ECG) as a modality for biometric authentication, in this work, we investigate the possibility of using personal ECG signals as the individually unique source for physical unclonable function (PUF), which eventually can be used as the key for encryption and decryption engines. We present new signal processing and machine learning algorithms that learn and extract maximally different ECG features for different individuals and minimally different ECG features for the same individual over time. Experimental results with a large 741-subject in-house ECG database show that the distributions of the intra-subject (same person) Hamming distance of extracted ECG features and the inter-subject Hamming distance have minimal overlap. 256-b random numbers generated from the ECG features of 648 (out of 741) subjects pass the NIST randomness tests.

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

PubMed

Asgari, Shadnaz; Mehrnia, Alireza

2017-01-01

Wearable and implantable Electrocardiograph (ECG) devices are becoming prevailing tools for continuous real-time personal health monitoring. The ECG signal can be contaminated by various types of noise and artifacts (e.g., powerline interference, baseline wandering) that must be removed or suppressed for accurate ECG signal processing. Limited device size, power consumption and cost are critical issues that need to be carefully considered when designing any portable health monitoring device, including a battery-powered ECG device. This work presents a novel low-complexity noise suppression reconfigurable finite impulse response (FIR) filter structure for wearable ECG and heart monitoring devices. The design relies on a recently introduced optimally-factored FIR filter method. The new filter structure and several of its useful features are presented in detail. We also studied the hardware complexity of the proposed structure and compared it with the state-of-the-art. The results showed that the new ECG filter has a lower hardware complexity relative to the state-of-the-art ECG filters.

Rate of cardiac arrhythmias and silent brain lesions in experienced marathon runners: rationale, design and baseline data of the Berlin Beat of Running study.

PubMed

Haeusler, Karl Georg; Herm, Juliane; Kunze, Claudia; Krüll, Matthias; Brechtel, Lars; Lock, Jürgen; Hohenhaus, Marc; Heuschmann, Peter U; Fiebach, Jochen B; Haverkamp, Wilhelm; Endres, Matthias; Jungehulsing, Gerhard Jan

2012-08-31

Regular exercise is beneficial for cardiovascular health but a recent meta-analysis indicated a relationship between extensive endurance sport and a higher risk of atrial fibrillation, an independent risk factor for stroke. However, data on the frequency of cardiac arrhythmias or (clinically silent) brain lesions during and after marathon running are missing. In the prospective observational "Berlin Beat of Running" study experienced endurance athletes underwent clinical examination (CE), 3 Tesla brain magnetic resonance imaging (MRI), carotid ultrasound imaging (CUI) and serial blood sampling (BS) within 2-3 days prior (CE, MRI, CUI, BS), directly after (CE, BS) and within 2 days after (CE, MRI, BS) the 38th BMW BERLIN-MARATHON 2011. All participants wore a portable electrocardiogram (ECG)-recorder throughout the 4 to 5 days baseline study period. Participants with pathological MRI findings after the marathon, troponin elevations or detected cardiac arrhythmias will be asked to undergo cardiac MRI to rule out structural abnormalities. A follow-up is scheduled after one year. Here we report the baseline data of the enrolled 110 athletes aged 36-61 years. Their mean age was 48.8 ± 6.0 years, 24.5% were female, 8.2% had hypertension and 2.7% had hyperlipidaemia. Participants have attended a mean of 7.5 ± 6.6 marathon races within the last 5 years and a mean of 16 ± 36 marathon races in total. Their weekly running distance prior to the 38th BMW BERLIN-MARATHON was 65 ± 17 km. Finally, 108 (98.2%) Berlin Beat-Study participants successfully completed the 38th BMW BERLIN-MARATHON 2011. Findings from the "Berlin Beats of Running" study will help to balance the benefits and risks of extensive endurance sport. ECG-recording during the marathon might contribute to identify athletes at risk for cardiovascular events. MRI results will give new insights into the link between physical stress and brain damage. clinicaltrials.gov NCT01428778.

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.

Arrhythmias Following Comprehensive Stage II Surgical Palliation in Single Ventricle Patients.

PubMed

Wilhelm, Carolyn M; Paulus, Diane; Cua, Clifford L; Kertesz, Naomi J; Cheatham, John P; Galantowicz, Mark; Fernandez, Richard P

2016-03-01

Post-operative arrhythmias are common in pediatric patients following cardiac surgery. Following hybrid palliation in single ventricle patients, a comprehensive stage II palliation is performed. The incidence of arrhythmias in patients following comprehensive stage II palliation is unknown. The purpose of this study is to determine the incidence of arrhythmias following comprehensive stage II palliation. A single-center retrospective chart review was performed on all single ventricle patients undergoing a comprehensive stage II palliation from January 2010 to May 2014. Pre-operative, operative, and post-operative data were collected. A clinically significant arrhythmia was defined as an arrhythmia which led to cardiopulmonary resuscitation or required treatment with either pacing or antiarrhythmic medication. Statistical analysis was performed with Wilcoxon rank-sum test and Fisher's exact test with p < 0.05 significant. Forty-eight single ventricle patients were reviewed (32 hypoplastic left heart syndrome, 16 other single ventricle variants). Age at surgery was 185 ± 56 days. Cardiopulmonary bypass time was 259 ± 45 min. Average vasoactive-inotropic score was 5.97 ± 7.58. Six patients (12.5 %) had clinically significant arrhythmias: four sinus bradycardia, one 2:1 atrioventricular block, and one slow junctional rhythm. No tachyarrhythmias were documented for this patient population. Presence of arrhythmia was associated with elevated lactate (p = 0.04) and cardiac arrest (p = 0.002). Following comprehensive stage II palliation, single ventricle patients are at low risk for development of tachyarrhythmias. The most frequent arrhythmia seen in these patients was sinus bradycardia associated with respiratory compromise.

An Improvement To The k-Nearest Neighbor Classifier For ECG Database

NASA Astrophysics Data System (ADS)

Jaafar, Haryati; Hidayah Ramli, Nur; Nasir, Aimi Salihah Abdul

2018-03-01

The k nearest neighbor (kNN) is a non-parametric classifier and has been widely used for pattern classification. However, in practice, the performance of kNN often tends to fail due to the lack of information on how the samples are distributed among them. Moreover, kNN is no longer optimal when the training samples are limited. Another problem observed in kNN is regarding the weighting issues in assigning the class label before classification. Thus, to solve these limitations, a new classifier called Mahalanobis fuzzy k-nearest centroid neighbor (MFkNCN) is proposed in this study. Here, a Mahalanobis distance is applied to avoid the imbalance of samples distribition. Then, a surrounding rule is employed to obtain the nearest centroid neighbor based on the distributions of training samples and its distance to the query point. Consequently, the fuzzy membership function is employed to assign the query point to the class label which is frequently represented by the nearest centroid neighbor Experimental studies from electrocardiogram (ECG) signal is applied in this study. The classification performances are evaluated in two experimental steps i.e. different values of k and different sizes of feature dimensions. Subsequently, a comparative study of kNN, kNCN, FkNN and MFkCNN classifier is conducted to evaluate the performances of the proposed classifier. The results show that the performance of MFkNCN consistently exceeds the kNN, kNCN and FkNN with the best classification rates of 96.5%.

A single exposure to acrolein causes arrhythmogenesis, cardiac electrical dysfunction and decreased heart rate variability in hypertensive rats

EPA Science Inventory

Epidemiological studies demonstrate an association between cardiovascular morbidity, arrhythmias, and exposure to air toxicants such as acrolein. We hypothesized that a single exposure to acrolein would increase arrhythmias and cause changes in the electrocardiogram (ECG) of hype...

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

[Complex ventricular arrhythmias and carvedilol: efficacy in hemodialyzed uremic patients].

PubMed

Cice, G; Tagliamonte, E; Ferrara, L; Di Benedetto, A; Iacono, A

1998-06-01

Carvedilol has been shown to be effective in systemic hypertension and coronary artery disease in patients with end-stage renal disease, on maintenance hemodialysis. The aim of our study was to assess the effects of carvedilol on ventricular arrhythmias in these patients. Ninety-eight uremic patients maintained on hemodialysis, with complex ventricular arrhythmias (class III, IV and V of Lown's classification), not only during dialysis, were included in the study. They were divided into two groups, with mild-to-moderate hypertension or coronary artery disease. The efficacy and safety of carvedilol (50 mg/day) was compared to placebo in a 6-week randomized, double-blind study. Carvedilol significantly reduced, in both hypertensive and ischemic patients, total ventricular premature contractions (82.7 +/- 11.3 vs 358.1 +/- 73.9, p < 0.001; 88.3 +/- 24.4 vs 369.9 +/- 77.8, p < 0.001), repetitive ventricular premature contractions (1.3 +/- 1.3 vs 6.3 +/- 3.5, p < 0.001; 1.2 +/- 0.7 vs 6.9 +/- 2.6, p < 0.001) and episodes of ventricular tachycardia (1.1 +/- 1.2 vs 11.8 +/- 7.5, p < 0.001; 1.4 +/- 1.2 vs 14.0 +/- 8.3, p < 0.001). In placebo-treated patients, instead, these parameters were not significantly changed (329.1 +/- 76.5 vs 361.7 +/- 71.7, NS, and 324.6 +/- 79.7 vs 359.3 +/- 58.1, NS; 6.2 +/- 3.7 vs 7.3 +/- 3.7, NS, and 4.9 +/- 2.2 vs 6.1 +/- 3.2, NS; 9.8 +/- 6.3 vs 13.3 +/- 8.0, NS, and 9.0 +/- 6.2 vs 12.4 +/- 7.8, NS). Carvedilol confirmed a significant effect on myocardial ischemia and systemic hypertension. No significant side effects were reported. Ventricular arrhythmias are frequent in patients with end-stage renal disease maintained on hemodialysis. They are often due to an underlying cardiac disease, namely systemic hypertension with left ventricular hypertrophy and coronary artery disease. The results of our study show that the antiarrhythmic effect of carvedilol is linked, at least partly, to an improvement of the underlying cardiac disease. Uremic

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.

History of research in Japan on electrocardiography in the racehorse

PubMed Central

HIRAGA, Atsushi; SUGANO, Shigeru

2015-01-01

ABSTRACT Since the first recording of electrocardiograms (ECGs) of a horse in Japan was carried out in 1944, studies on ECGs have been performed intensively. During the early stages of research from the 1950s to 1960s, leads to use for ECG recording were evaluated using several different approaches including unipolar leads, bipolar limb leads, and bipolar chest leads. Based on these studies, the AB lead, which is oriented along the long axis of the heart, became the standard reference method in Japan. Electrodes of the AB lead are placed on the upper 1/4th point along a straight line between the withers and the left shoulder blade (base: B), and 10 cm posterior to the left olecranon (apex: A). The incidence of equine arrhythmias among racehorses has been surveyed, and details of the electrocardiographic characteristics of several arrhythmias have been investigated. In particular, atrial fibrillation (AF) has been extensively studied, and papers have reported findings such as that paroxysmal AF occurs during racing and described electrocardiographic changes that occur at the onset of AF during exercise. Development of a radiotelemetry system for ECG recording enabled the first recording of equine ECGs during galloping in 1964, the detection of arrhythmias, and calculation of heart rate during exercise. Studies on comparative and developmental changes of ECGs have described characteristics of the equine ECGs. Future research on changes in cardiac function, including autonomic function, that occur with aging may lead to new developments in equine electrocardiography and contribute to improving the health and welfare of the horse. PMID:25829865

[Observations and significance of extrasystole in very young athletes].

PubMed

Rossini, G; Mazzoli, M; Dalmastri, G; Crescimbeni, L; Berti, P; Arata, G; Losi, G; Martines, G

1982-01-01

80 very young football players (from 8 to 12) have been examined for three months by some clinical and instrumental cardiologic tests (starting E.C.G. and after graduated stresses on a football court). The starting E.C.G. showed variable extresystolic arrhythmias in 8 subjects, without any sure signs of a cardiopathy, to point out by deeper tests (such as polygraphic, echocardiographic test and rx heart teleradiography). The above-mentioned arrhythmias felt the effects of training variably, since they regressed in 6 cases, however two subjects needed a pharmacological intervention. They are still talking over the meaning to give to extrasystolic arrhythmias in very young people in evaluation of attitude to agonism and in programming training.

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

Biometric sample extraction using Mahalanobis distance in Cardioid based graph using electrocardiogram signals.

PubMed

Sidek, Khairul; Khali, Ibrahim

2012-01-01

In this paper, a person identification mechanism implemented with Cardioid based graph using electrocardiogram (ECG) is presented. Cardioid based graph has given a reasonably good classification accuracy in terms of differentiating between individuals. However, the current feature extraction method using Euclidean distance could be further improved by using Mahalanobis distance measurement producing extracted coefficients which takes into account the correlations of the data set. Identification is then done by applying these extracted features to Radial Basis Function Network. A total of 30 ECG data from MITBIH Normal Sinus Rhythm database (NSRDB) and MITBIH Arrhythmia database (MITDB) were used for development and evaluation purposes. Our experimentation results suggest that the proposed feature extraction method has significantly increased the classification performance of subjects in both databases with accuracy from 97.50% to 99.80% in NSRDB and 96.50% to 99.40% in MITDB. High sensitivity, specificity and positive predictive value of 99.17%, 99.91% and 99.23% for NSRDB and 99.30%, 99.90% and 99.40% for MITDB also validates the proposed method. This result also indicates that the right feature extraction technique plays a vital role in determining the persistency of the classification accuracy for Cardioid based person identification mechanism.

Non-invasive Fetal ECG Signal Quality Assessment for Multichannel Heart Rate Estimation.

PubMed

Andreotti, Fernando; Graser, Felix; Malberg, Hagen; Zaunseder, Sebastian

2017-12-01

The noninvasive fetal ECG (NI-FECG) from abdominal recordings offers novel prospects for prenatal monitoring. However, NI-FECG signals are corrupted by various nonstationary noise sources, making the processing of abdominal recordings a challenging task. In this paper, we present an online approach that dynamically assess the quality of NI-FECG to improve fetal heart rate (FHR) estimation. Using a naive Bayes classifier, state-of-the-art and novel signal quality indices (SQIs), and an existing adaptive Kalman filter, FHR estimation was improved. For the purpose of training and validating the proposed methods, a large annotated private clinical dataset was used. The suggested classification scheme demonstrated an accuracy of Krippendorff's alpha in determining the overall quality of NI-FECG signals. The proposed Kalman filter outperformed alternative methods for FHR estimation achieving accuracy. The proposed algorithm was able to reliably reflect changes of signal quality and can be used in improving FHR estimation. NI-ECG signal quality estimation and multichannel information fusion are largely unexplored topics. Based on previous works, multichannel FHR estimation is a field that could strongly benefit from such methods. The developed SQI algorithms as well as resulting classifier were made available under a GNU GPL open-source license and contributed to the FECGSYN toolbox.

A troubled beginning: evolving concepts of an old arrhythmia.

PubMed

Hanon, Sam; Shapiro, Michael; Schweitzer, Paul

2005-07-01

The development of the sphygmograph in the nineteenth century marked the beginning of graphic registration of the arterial and venous pulse. Mackenzie, among other investigators, used this technique to study cardiac rhythm. In the early 20th century, Einthoven developed the electrocardiogram, which replaced the less sophisticated arterial and venous registrations of cardiac events and allowed for more detailed arrhythmia analysis. Interestingly, the early study of cardiac arrhythmias was obscured by misinterpretation. Specifically, atrial fibrillation stands out as a rhythm that was extensively studied though misconstrued in its early history. What follows is an in-depth consideration of the original investigations and evolving theories of this important arrhythmia.

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...

The Association between Nocturnal Cardiac Arrhythmias and Sleep-Disordered Breathing: The DREAM Study.

PubMed

Selim, Bernardo J; Koo, Brian B; Qin, Li; Jeon, Sangchoon; Won, Christine; Redeker, Nancy S; Lampert, Rachel J; Concato, John P; Bravata, Dawn M; Ferguson, Jared; Strohl, Kingman; Bennett, Adam; Zinchuk, Andrey; Yaggi, Henry K

2016-06-15

To determine whether sleep-disordered breathing (SDB) is associated with cardiac arrhythmia in a clinic-based population with multiple cardiovascular comorbidities and severe SDB. This was a cross-sectional analysis of 697 veterans who underwent polysomnography for suspected SDB. SDB was categorized according to the apnea-hypopnea index (AHI): none (AHI < 5), mild (5 ≥ AHI < 15), and moderate-severe (AHI ≥ 15). Nocturnal cardiac arrhythmias consisted of: (1) complex ventricular ectopy, (CVE: non-sustained ventricular tachycardia, bigeminy, trigeminy, or quadrigeminy), (2) combined supraventricular tachycardia, (CST: atrial fibrillation or supraventricular tachycardia), (3) intraventricular conduction delay (ICD), (4) tachyarrhythmias (ventricular and supraventricular), and (5) any cardiac arrhythmia. Unadjusted, adjusted logistic regression, and Cochran-Armitage testing examined the association between SDB and cardiac arrhythmias. Linear regression models explored the association between hypoxia, arousals, and cardiac arrhythmias. Compared to those without SDB, patients with moderate-severe SDB had almost three-fold unadjusted odds of any cardiac arrhythmia (2.94; CI 95%, 2.01-4.30; p < 0.0001), two-fold odds of tachyarrhythmias (2.16; CI 95%,1.47-3.18; p = 0.0011), two-fold odds of CVE (2.01; 1.36-2.96; p = 0.003), and two-fold odds of ICD (2.50; 1.58-3.95; p = 0.001). A linear trend was identified between SDB severity and all cardiac arrhythmia subtypes (p value linear trend < 0.0001). After adjusting for age, BMI, gender, and cardiovascular diseases, moderate-severe SDB patients had twice the odds of having nocturnal cardiac arrhythmias (2.24; 1.48-3.39; p = 0.004). Frequency of obstructive respiratory events and hypoxia were strong predictors of arrhythmia risk. SDB is independently associated with nocturnal cardiac arrhythmias. Increasing severity of SDB was associated with an increasing risk for any cardiac arrhythmia. © 2016 American Academy of Sleep

[Analysis of the heart sound with arrhythmia based on nonlinear chaos theory].

PubMed

Ding, Xiaorong; Guo, Xingming; Zhong, Lisha; Xiao, Shouzhong

2012-10-01

In this paper, a new method based on the nonlinear chaos theory was proposed to study the arrhythmia with the combination of the correlation dimension and largest Lyapunov exponent, through computing and analyzing these two parameters of 30 cases normal heart sound and 30 cases with arrhythmia. The results showed that the two parameters of the heart sounds with arrhythmia were higher than those with the normal, and there was significant difference between these two kinds of heart sounds. That is probably due to the irregularity of the arrhythmia which causes the decrease of predictability, and it's more complex than the normal heart sound. Therefore, the correlation dimension and the largest Lyapunov exponent can be used to analyze the arrhythmia and for its feature extraction.

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.

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 ...

Live ECG readings using Google Glass in emergency situations.

PubMed

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

2015-01-01

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

ECG 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

Classification of holter registers by dynamic clustering using multi-dimensional particle swarm optimization.

PubMed

Kiranyaz, Serkan; Ince, Turker; Pulkkinen, Jenni; Gabbouj, Moncef

2010-01-01

In this paper, we address dynamic clustering in high dimensional data or feature spaces as an optimization problem where multi-dimensional particle swarm optimization (MD PSO) is used to find out the true number of clusters, while fractional global best formation (FGBF) is applied to avoid local optima. Based on these techniques we then present a novel and personalized long-term ECG classification system, which addresses the problem of labeling the beats within a long-term ECG signal, known as Holter register, recorded from an individual patient. Due to the massive amount of ECG beats in a Holter register, visual inspection is quite difficult and cumbersome, if not impossible. Therefore the proposed system helps professionals to quickly and accurately diagnose any latent heart disease by examining only the representative beats (the so called master key-beats) each of which is representing a cluster of homogeneous (similar) beats. We tested the system on a benchmark database where the beats of each Holter register have been manually labeled by cardiologists. The selection of the right master key-beats is the key factor for achieving a highly accurate classification and the proposed systematic approach produced results that were consistent with the manual labels with 99.5% average accuracy, which basically shows the efficiency of the system.

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.

Classification of ictal and seizure-free HRV signals with focus on lateralization of epilepsy.

PubMed

Behbahani, Soroor; Dabanloo, Nader Jafarnia; Nasrabadi, Ali Motie; Dourado, Antonio

2016-01-01

Epileptic onsets often affect the autonomic function of the body during a seizure, whether it is in ictal, interictal or post-ictal periods. The different effects of localization and lateralization of seizures on heart rate variability (HRV) emphasize the importance of autonomic function changes in epileptic patients. On the other hand, the detection of seizures is of primary interests in evaluating the epileptic patients. In the current paper, we analyzed the HRV signal to develop a reliable offline seizure-detection algorithm to focus on the effects of lateralization on HRV. We assessed the HRV during 5-min segments of continuous electrocardiogram (ECG) recording with a total number of 170 seizures occurred in 16 patients, composed of 86 left-sided and 84 right-sided focus seizures. Relatively high and low-frequency components of the HRV were computed using spectral analysis. Poincaré parameters of each heart rate time series considered as non-linear features. We fed these features to the Support Vector Machines (SVMs) to find a robust classification method to classify epileptic and non-epileptic signals. Leave One Out Cross-Validation (LOOCV) approach was used to demonstrate the consistency of the classification results. Our obtained classification accuracy confirms that the proposed scheme has a potential in classifying HRV signals to epileptic and non-epileptic classes. The accuracy rates for right-sided and left-sided focus seizures were obtained as 86.74% and 79.41%, respectively. The main finding of our study is that the patients with right-sided focus epilepsy showed more reduction in parasympathetic activity and more increase in sympathetic activity. It can be a marker of impaired vagal activity associated with increased cardiovascular risk and arrhythmias. Our results suggest that lateralization of the seizure onset zone could exert different influences on heart rate changes. A right-sided seizure would cause an ictal tachycardia whereas a left

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.

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.

Dual chamber arrhythmia detection in the implantable cardioverter defibrillator.

PubMed

Dijkman, B; Wellens, H J

2000-10-01

Dual chamber implantable cardioverter defibrillator (ICD) technology extended ICD therapy to more than termination of hemodynamically unstable ventricular tachyarrhythmias. It created the basis for dual chamber arrhythmia management in which dependable detection is important for treatment and prevention of both ventricular and atrial arrhythmias. Dual chamber detection algorithms were investigated in two Medtronic dual chamber ICDs: the 7250 Jewel AF (33 patients) and the 7271 Gem DR (31 patients). Both ICDs use the same PR Logic algorithm to interpret tachycardia as ventricular tachycardia (VT), supraventricular tachycardia (SVT), or dual (VT+ SVT). The accuracy of dual chamber detection was studied in 310 of 1,367 spontaneously occurring tachycardias in which rate criterion only was not sufficient for arrhythmia diagnosis. In 78 episodes there was a double tachycardia, in 223 episodes SVT was detected in the VT or ventricular fibrillation zone, and in 9 episodes arrhythmia was detected outside the boundaries of the PR Logic functioning. In 100% of double tachycardias the VT was correctly diagnosed and received priority treatment. SVT was seen in 59 (19%) episodes diagnosed as VT. The causes of inappropriate detection were (1) algorithm failure (inability to fulfill the PRarrhythmias. Dual chamber detection algorithms evaluated in a subset of diagnostically difficult arrhythmias allow safe detection of double tachycardias but require further extension and programmability to

Types of Arrhythmia in Children

MedlinePlus

... even though they may need to keep taking medicine. Your child will probably need periodic check-ups but will ... minute. Understand and manage medications Parents of a child taking medicine for an arrhythmia should give the medicine at ...

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.

Cholinesterase inhibition reduces arrhythmias in asymptomatic Chagas disease.

PubMed

Castro, Renata R T; Porphirio, Graciema; Xavier, Sergio S; Moraes, Ruy S; Ferlin, Elton L; Ribeiro, Jorge P; da Nóbrega, Antonio C L

2017-10-01

Parasympathetic dysfunction may play a role in the genesis of arrhythmias in Chagas disease. This study evaluates the acute effects of pyridostigmine (PYR), a reversible cholinesterase inhibitor, on the occurrence of arrhythmias in patients with Chagas cardiac disease. Following a double-blind, randomized, placebo-controlled, cross-over protocol, 17 patients (age 50±2 years) with Chagas cardiac disease type B underwent 24-hour Holter recordings after oral administration of either pyridostigmine bromide (45 mg, 3 times/day) or placebo (PLA). Pyridostigmine reduced the 24-hours incidence (median [25%-75%]) of premature ventricular beats-PLA: 2998 (1920-4870), PYR: 2359 (940-3253), P=.044; ventricular couplets-PLA: 84 (15-159), PYR: 33 (6-94), P=.046. Although the total number of nonsustained ventricular tachycardia in the entire group was not different (P=.19) between PLA (1 [0-8]) and PYR (0 [0-4]), there were fewer episodes under PYR in 72% of the patients presenting this type of arrhythmia (P=.033). Acute administration of pyridostigmine reduced the incidence of nonsustained ventricular arrhythmias in patients with Chagas cardiac disease. Further studies that address the use of pyridostigmine by patients with Chagas cardiac disease under a more prolonged follow-up are warranted. © 2017 John Wiley & Sons Ltd.

Detection and Prevention of Arrhythmias During Space Flight

NASA Technical Reports Server (NTRS)

Pillai, Dilip; Rosenbaum, David; Liszka, Kathy; York, David; Mackin, Michael; Lichter, Michael

2004-01-01

Objectives of this research include:determine if orthogonal lead sets can; determine if orthogonal lead sets can correct artifactual ECG changes caused by correct artifactual ECG changes caused by microgravity- induced alterations in cardiac position; determine if markers of susceptibility to SCD (TWA and QT restitution) can be reliably measured during space flight; determine the effects of continuous microgravity on markers of susceptibility to SCD.

Cardiac arrhythmias from a malpositioned Greenfield filter in a traumatic quadriplegic.

PubMed

Bach, J R; Zaneuski, R; Lee, H

1990-10-01

A case study is presented of premature Greenfield filter discharge with intracardiac migration and resulting life-threatening arrhythmias. These arrhythmias also interfered with the patient's transition from ventilatory support via orotracheal intubation to noninvasive positive airway pressure ventilatory support methods. The patient's arrhythmias were controlled by a demand cardiac pacemaker and cardiac glycoside therapy. No anticoagulants were used. She had no further filter migration nor significant complications for 16 months after hospital discharge.

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

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.

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

Increasing Prevalence of Atrial Fibrillation and Permanent Atrial Arrhythmias in Congenital Heart Disease.

PubMed

Labombarda, Fabien; Hamilton, Robert; Shohoudi, Azadeh; Aboulhosn, Jamil; Broberg, Craig S; Chaix, Marie A; Cohen, Scott; Cook, Stephen; Dore, Annie; Fernandes, Susan M; Fournier, Anne; Kay, Joseph; Macle, Laurent; Mondésert, Blandine; Mongeon, François-Pierre; Opotowsky, Alexander R; Proietti, Anna; Rivard, Lena; Ting, Jennifer; Thibault, Bernard; Zaidi, Ali; Khairy, Paul

2017-08-15

Atrial arrhythmias are the most common complication encountered in the growing and aging population with congenital heart disease. This study sought to assess the types and patterns of atrial arrhythmias, associated factors, and age-related trends. A multicenter cohort study enrolled 482 patients with congenital heart disease and atrial arrhythmias, age 32.0 ± 18.0 years, 45.2% female, from 12 North American centers. Qualifying arrhythmias were classified by a blinded adjudicating committee. The most common presenting arrhythmia was intra-atrial re-entrant tachycardia (IART) (61.6%), followed by atrial fibrillation (28.8%), and focal atrial tachycardia (9.5%). The proportion of arrhythmias due to IART increased with congenital heart disease complexity from 47.2% to 62.1% to 67.0% in patients with simple, moderate, and complex defects, respectively (p = 0.0013). Atrial fibrillation increased with age to surpass IART as the most common arrhythmia in those ≥50 years of age (51.2% vs. 44.2%; p < 0.0001). Older age (odds ratio [OR]: 1.024 per year; 95% confidence interval [CI]: 1.010 to 1.039; p = 0.001) and hypertension (OR: 2.00; 95% CI: 1.08 to 3.71; p = 0.029) were independently associated with atrial fibrillation. During a mean follow-up of 11.3 ± 9.4 years, the predominant arrhythmia pattern was paroxysmal in 62.3%, persistent in 28.2%, and permanent in 9.5%. Permanent atrial arrhythmias increased with age from 3.1% to 22.6% in patients <20 years to ≥50 years, respectively (p < 0.0001). IART is the most common presenting atrial arrhythmia in patients with congenital heart disease, with a predominantly paroxysmal pattern. However, atrial fibrillation increases in prevalence and atrial arrhythmias progressively become permanent as the population ages. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

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.

Asymptomatic Intradialytic Supraventricular Arrhythmias and Adverse Outcomes in Patients on Hemodialysis

PubMed Central

Pérez de Prado, Armando; López-Gómez, Juan M.; Quiroga, Borja; Goicoechea, Marian; García-Prieto, Ana; Torres, Esther; Reque, Javier; Luño, José

2016-01-01

Background and objectives Supraventricular arrhythmias are associated with high morbidity and mortality. Nevertheless, this condition has received little attention in patients on hemodialysis. The objective of this study was to analyze the incidence of intradialysis supraventricular arrhythmia and its long–term prognostic value. Design, setting, participants, & measurements We designed an observational and prospective study in a cohort of patients on hemodialysis with a 10-year follow-up period. All patients were recruited for study participation and were not recruited for clinical indications. The study population comprised 77 patients (42 men and 35 women; mean age =58±15 years old) with sinus rhythm monitored using a Holter electrocardiogram over six consecutive hemodialysis sessions at recruitment. Results Hypertension was present in 68.8% of patients, and diabetes was present in 29.9% of patients. Supraventricular arrhythmias were recorded in 38 patients (49.3%); all of these were short, asymptomatic, and self-limiting. Age (hazard ratio, 1.04 per year; 95% confidence interval, 1.00 to 1.08) and right atrial enlargement (hazard ratio, 4.29; 95% confidence interval, 1.30 to 14.09) were associated with supraventricular arrhythmia in the multivariate analysis. During a median follow-up of 40 months, 57 patients died, and cardiovascular disease was the main cause of death (52.6%). The variables associated with all-cause mortality in the Cox model were age (hazard ratio, 1.04 per year; 95% confidence interval, 1.00 to 1.08), C-reactive protein (hazard ratio, 1.04 per 1 mg/L; 95% confidence interval, 1.00 to 1.08), and supraventricular arrhythmia (hazard ratio, 3.21; 95% confidence interval, 1.29 to 7.96). Patients with supraventricular arrhythmia also had a higher risk of nonfatal cardiovascular events (hazard ratio, 4.32; 95% confidence interval, 2.11 to 8.83) and symptomatic atrial fibrillation during follow-up (hazard ratio, 17.19; 95% confidence interval, 2

Asymptomatic Intradialytic Supraventricular Arrhythmias and Adverse Outcomes in Patients on Hemodialysis.

PubMed

Verde, Eduardo; Pérez de Prado, Armando; López-Gómez, Juan M; Quiroga, Borja; Goicoechea, Marian; García-Prieto, Ana; Torres, Esther; Reque, Javier; Luño, José

2016-12-07

Supraventricular arrhythmias are associated with high morbidity and mortality. Nevertheless, this condition has received little attention in patients on hemodialysis. The objective of this study was to analyze the incidence of intradialysis supraventricular arrhythmia and its long-term prognostic value. We designed an observational and prospective study in a cohort of patients on hemodialysis with a 10-year follow-up period. All patients were recruited for study participation and were not recruited for clinical indications. The study population comprised 77 patients (42 men and 35 women; mean age =58±15 years old) with sinus rhythm monitored using a Holter electrocardiogram over six consecutive hemodialysis sessions at recruitment. Hypertension was present in 68.8% of patients, and diabetes was present in 29.9% of patients. Supraventricular arrhythmias were recorded in 38 patients (49.3%); all of these were short, asymptomatic, and self-limiting. Age (hazard ratio, 1.04 per year; 95% confidence interval, 1.00 to 1.08) and right atrial enlargement (hazard ratio, 4.29; 95% confidence interval, 1.30 to 14.09) were associated with supraventricular arrhythmia in the multivariate analysis. During a median follow-up of 40 months, 57 patients died, and cardiovascular disease was the main cause of death (52.6%). The variables associated with all-cause mortality in the Cox model were age (hazard ratio, 1.04 per year; 95% confidence interval, 1.00 to 1.08), C-reactive protein (hazard ratio, 1.04 per 1 mg/L; 95% confidence interval, 1.00 to 1.08), and supraventricular arrhythmia (hazard ratio, 3.21; 95% confidence interval, 1.29 to 7.96). Patients with supraventricular arrhythmia also had a higher risk of nonfatal cardiovascular events (hazard ratio, 4.32; 95% confidence interval, 2.11 to 8.83) and symptomatic atrial fibrillation during follow-up (hazard ratio, 17.19; 95% confidence interval, 2.03 to 145.15). The incidence of intradialysis supraventricular arrhythmia was high

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

PubMed

Garster, Noelle C; Henrikson, Charles A

2017-07-01

Premature ventricular complexes (PVCs) are an underrecognized cause of cardiomyopathy. Standard 12-lead electrocardiogram (ECG) has potential to direct attention toward at-risk patients. We performed a single-center, retrospective chart review of 1,240 patients who completed ECG and Holter monitoring at Oregon Health and Science University Hospital between January 1, 2011 and December 31, 2013 to investigate the relationship of PVC frequency on ECG with burden on Holter. Primary outcome measures included PVC quantity on ECG, mean PVC quantity on Holter, and percentage of total beats on Holter recorded as PVCs. High PVC burden was defined as ≥10% of total beats. Weighted mean percentages of total beats on Holter monitor recorded as PVCs were calculated for 0, 1, 2, and ≥3 PVCs on ECG and found to be 1.4% (n = 1,128), 3.5% (n = 32), 4.3% (n = 25), and 16.6% (n = 55), respectively, which represent statistically significant differences (P < 0.001). The positive predictive value of at least three PVCs on ECG for ≥10% PVC Holter burden was 58%. Negative predictive value for 0 PVCs on ECG was 98%. The sensitivity and specificity of ECG to identify high PVC burden on Holter was 72% and 93.6%, respectively, when utilizing a positive ECG result as one PVC or more, and 44% and 98.9%, respectively, with ≥3 PVCs on ECG. The positive likelihood ratio corresponding to ≥3 PVCs on ECG was 40. These findings demonstrate that the number of PVCs on ECG can be utilized for quick bedside estimation of high PVC burden. © 2017 Wiley Periodicals, Inc.

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

PubMed

Da Poian, Giulia; Rozell, Christopher J; Bernardini, Riccardo; Rinaldo, Roberto; Clifford, Gari D

2017-09-14

Compressive Sensing (CS) has recently been applied as a low complexity compression framework for long-term monitoring of electrocardiogram signals using Wireless Body Sensor Networks. Long-term recording of ECG signals can be useful for diagnostic purposes and to monitor the evolution of several widespread diseases. In particular, beat to beat intervals provide important clinical information, and these can be derived from the ECG signal by computing the distance between QRS complexes (R-peaks). Numerous methods for R-peak detection are available for uncompressed ECG. However, in case of compressed sensed data, signal reconstruction can be performed with relatively complex optimisation algorithms, which may require significant energy consumption. This article addresses the problem of hearth rate estimation from compressive sensing electrocardiogram (ECG) recordings, avoiding the reconstruction of the entire signal. We consider a framework where the ECG signals are represented under the form of CS linear measurements. The QRS locations are estimated in the compressed domain by computing the correlation of the compressed ECG and a known QRS template. Experiments on actual ECG signals show that our novel solution is competitive with methods applied to the reconstructed signals. Avoiding the reconstruction procedure, the proposed method proves to be very convenient for real-time, low-power applications.