Multichannel ECG Recordings Research Articles

Estimation of PQ distance dispersion for atrial fibrillation detection

Background and objective: Atrial fibrillation (AF) is the most common cardiac arrhythmia in the world. It is associated with significantly increased morbidity and mortality. Diagnosis of the disease can be based on the analysis of the electrical atrial activity, on quantification of the heart rate irregularity or on a mixture of the both approaches. Since the amplitude of the atrial waves is small, their analysis can lead to false results. On the other hand, the heart rate based analysis usually leads to many unnecessary warnings. Therefore, our goal is to develop a new method for effective AF detection based on the analysis of the electrical atrial waves.Methods: The proposed method employs the fact that there is a lack of repeatable P waves preceding QRS complexes during AF. We apply the operation of spatio-temporal filtering (STF) to magnify and detect the prominent spatio-temporal patterns (STP) within the P waves in multi-channel ECG recordings. Later we measure their distances (PQ) to the succeeding QRS complexes, and we estimate dispersion of the obtained PQ series. For signals with normal sinus rhythm, this dispersion is usually very low, and contrary, for AF it is much raised. This allows for effective discrimination of this cardiologic disorder.Results: Tested on an ECG database consisting of AF cases, normal rhythm cases and cases with normal rhythm restored by the use of cardioversion, the method proposed allowed for AF detection with the accuracy of 98.75% on the basis of both 8–channel and 2–channel signals of 12 s length. When the signals length was decreased to 6 s, the accuracy varied in the range of 95%−97.5% depending on the number of channels and the dispersion measure applied.Conclusions: Our approach allows for high accuracy of atrial fibrillation detection using the analysis of electrical atrial activity. The method can be applied to an early detection of the desease and can advantageously be used to decrease the number of false warnings in systems based on the analysis of the heart rate.

Noninvasive epi-endocardial electrocardiographic imaging of ventricular septal pacing

Noninvasive epi-endocardial ElectroCardioGraphic Imaging (ECGI) allows reconstruction of electrograms and high-resolution visualization of various isoparametric maps based on multichannel ECG recordings and tomography. We aimed to verify the ECGI accuracy during septal ventricular pacing in patients with pre-implanted pacemakers using the new ECGI algorithm.Methods. Ten patients underwent epi-endocardial ECGI mapping (Amycard 01C EP Lab, Amycard LLC, Russia - EP Solutions SA, Switzerland). The iterative Equal Single Layer algorithm (ESL-iterative) and a new Fast Route algorithm in combination with the vector approach (FRA-V) were used to reconstruct isopotential and correlation similarity maps. Geodesic distance between noninvasively reconstructed early activation zone and RV reference pacing sites were measured to evaluate the ECGI accuracy.Results. The mean (SD) geodesic distance between noninvasively identified sites and reference pacing sites was 22 (15) mm for the ESL-iterative and 12 (7) for FRA-V algorithms, median (25-75% IQR) - 23 (8-29) mm and 10 (8-14) mm, respectively. The accuracy of ECGI mapping based on the FRA-V algorithm was significantly better than ESL-iterative algorithm (p=0,01). A detailed visual analysis of correlation similarity and isopotential maps showed significantly more accurate localization of early activation zones using the new FRA-V algorithm.Conclusions. Our study showed the feasibility and accuracy of a novel epi-endocardial ECGI mapping approach to identify early activation zones during septal ventricular pacing using the new FRA-V algorithm. The FRA-V algorithm is significantly better for epi-endocardial ECGI mapping and shows a significant advantage of this technique compared to other non-invasive methods of topical diagnostics. Moreover, simultaneous beat-to-beat mapping of entire ventricular septum allows using this technique for pre-ablation evaluation of unstable and polymorphic ventricular arrhythmia exit sites.

Noninvasive epi-endocardial electrocardiographic imaging of ventricular septal pacing

Noninvasive epi-endocardial ElectroCardioGraphic Imaging (ECGI) allows reconstruction of electrograms and high-resolution visualization of various isoparametric maps based on multichannel ECG recordings and tomography. This study shows results of ECGI accuracy verification based on septal ventricular pacing in patients with pre-implanted pacemakers using new algorithm for solving the inverse problem of electrocardiography.Methods. 10 patients in this study underwent epi-endocardial ECGI mapping (Amycard 01C EP Lab, Amycard LLC, Russia - EP Solutions SA, Switzerland). An iterative Equal Single Layer algorithm (ESL-iterative) and new Fast Route algorithm in combination with vector approach (FRA-V) were used to reconstruct isopotential and correlation similarity maps. Geodesic distance between noninvasively reconstructed early activate zone and RV reference pacing site were measured to evaluate ECGI accuracy.Results. The mean (SD) geodesic distance between noninvasively reconstructed and reference pacing site was 22 (15) mm for ESL-iterative and 12 (7) for FRA-V algorithm, median (25-75% IQR) - 23 (8-29) mm and 10 (8-14) mm respectively. Accuracy of ECGI mapping based on FRA-V algorithm was significantly better than ESL-iterative algorithm (p=0,01). Detailed visual analysis of correlation similarity and isopotential maps showed significantly more accurate localization of early activation zones using new FRA-V algorithm.Conclusions. These results showed a possibility of novel epi-endocardial ECGI mapping to detect early activation zone during septal ventricular pacing with sufficient accuracy (median 10 mm) using new FRA-V algorithm. Therefore, FRA-V algorithm is significantly better for epi-endocardial ECGI mapping and shows a significant advantage of this technique compared to other non-invasive methods of topical diagnostics. Moreover, simultaneous beat-to-beat mapping of entire ventricular septum allows using of this technique for preoperative topical diagnosis of complex unstable and polymorphic ventricular arrhythmias.

Improved Clinical Risk Stratification in Patients with Long QT Syndrome? Novel Insights from Multi-Channel ECGs

BackgroundWe investigated whether multichannel ECG-recordings are useful to risk-stratify patients with congenital long-QT syndrome (LQTS) for risk of sudden cardiac death under optimized medical treatment.MethodsIn 34 LQTS-patients (11 male; age 31±13 years, QTc 478±51ms; LQT1 n = 8, LQT2 n = 15) we performed a standard 12-channel ECG and a 120-channel body surface potential mapping. The occurrence of clinical events (CE; syncope, torsade de pointes (TdP), sudden cardiac arrest (SCA)) was documented and correlated with different ECG-parameters in all lead positions.ResultsSeven patients developed TdP, four survived SCA and 12 experienced syncope. 12/34 had at least one CE. CE was associated with a longer QTc-interval (519±43ms vs. 458±42ms; p = 0.001), a lower T-wave integral (TWI) on the left upper chest (-1.2±74.4mV*ms vs. 63.0±29.7mV*ms; p = 0.001), a lower range of T-wave amplitude (TWA) in the region of chest lead V8 (0.10±0.08mV vs. 0.18±0.07mV; p = 0.008) and a longer T-peak-T-end time (TpTe) in lead V1 (98±23ms vs. 78±26ms; p = 0.04). Receiver-operating-characteristic (ROC) analyses revealed a sensitivity of 96% and a specificity of 75% (area under curve (AUC) 0.89±0.06, p = 0.001) at a cut-off value of 26.8mV*ms for prediction of CE by TWI, a sensitivity of 86% and a specificity of 83% at a cut-off value of 0.11mV (AUC 0.83±0.09, p = 0.002) for prediction of CE by TWA and a sensitivity of 83% and a specificity of 73% at a cut-off value of 87ms (AUC 0.80±0.07, p = 0.005) for prediction of CE by TpTe.ConclusionsOccurrence of CE in LQTS-patients seems to be associated with a prolonged, low-amplitude T-wave.

Artifact Reduction in Multichannel ECG Recordings Acquired with Textile Electrodes

Article Artifact Reduction in Multichannel ECG Recordings Acquired with Textile Electrodes was published on August 30, 2012 in the journal Biomedical Engineering / Biomedizinische Technik (volume 57, issue SI-1-Track-F).

Clasification Of Arrhythmic ECG Data Using Machine Learning Techniques

In this paper we proposed a automated Artificial Neural Network (ANN) based classification system for cardiac arrhythmia using multi-channel ECG recordings. In this study, we are mainly interested in producing high confident arrhythmia classification results to be applicable in diagnostic decision support systems. Neural network model with back propagation algorithm is used to classify arrhythmia cases into normal and abnormal classes. Networks models are trained and tested for MIT-BIH arrhythmia. The different structures of ANN have been trained by mixture of arrhythmic and non arrhythmic data patient. The classification performance is evaluated using measures; sensitivity, specificity, classification accuracy, mean squared error (MSE), receiver operating characteristics (ROC) and area under curve (AUC). Our experimental results gives 96.77% accuracy on MIT-BIH database and 96.21% on database prepared by including NSR database also.

Performance evaluation of nonparametric ICA algorithm for fetal ECG extraction

Fetal electrocardiograms (FECG) contain important indications about the health and condition of the fetus. In this respect, it is crucial to apply a robust algorithm to ECG data for extraction of the FECG signal. Most of the independent component analysis (ICA) algorithms used for this purpose rely on simple statistical models. Such algorithms can fail to separate desired signals when the assumed statistical model is inaccurate. Statistical models can be estimated accurately using kernel density estimation methods. Therefore, the kernel density estimation method was used in this paper for building an ICA algorithm (nonparametric ICA: NpICA) and the algorithm was applied to abdominal recordings to separate the FECG signals, which had not been implemented before. Checking of the separation quality of the NpICA algorithm was applied to synthetic ECG signals and real multichannel ECG recordings obtained from a pregnant woman's skin. The test results showed that the NpICA algorithm outperformed other known ICA algorithms such as FastICA and JADE. The superior performance of the NpICA algorithm was especially evident in recordings with high signal length. This indicates that the NpICA method is more robust than other classical ICA algorithms for FECG extraction.

Bayesian Approach to Patient-Tailored Vectorcardiography

For assessment of specific cardiac pathologies, vectorcardiography is generally considered superior with respect to electrocardiography. Existing vectorcardiography methods operate by calculating the vectorcardiogram (VCG) as a fixed linear combination of ECG signals. These methods, with the inverse Dower matrix method the current standard, are therefore not flexible with respect to different body compositions and geometries. Hence, they cannot be applied with accuracy on patients that do not conform to the fixed standard. Typical examples of such patients are obese patients or fetuses. For the latter category, when recording the fetal ECG from the maternal abdomen the distance of the fetal heart with respect to the electrodes is unknown. Consequently, also the signal attenuation/transformation per electrode is not known. In this paper, a Bayesian method is developed that estimates the VCG and, to some extent, also the signal attenuation in multichannel ECG recordings from either the adult 12-lead ECG or the maternal abdomen. This is done by determining for which VCG and signal attenuation the joint probability over both these variables is maximal given the observed ECG signals. The underlying joint probability distribution is determined by assuming the ECG signals to originate from scaled VCG projections and additive noise. With this method, a VCG, tailored to each specific patient, is determined. The method is compared to the inverse Dower matrix method by applying both methods on standard 12-lead ECG recordings and evaluating the performance in predicting ECG signals from the determined VCG. In addition, to model nonstandard patients, the 12-lead ECG signals are randomly scaled and, once more, the performance in predicting ECG signals from the VCG is compared between both methods. Finally, both methods are also compared on fetal ECG signals that are obtained from the maternal abdomen. For patients conforming to the standard, both methods perform similarly, with the developed method performing marginally better. For scaled ECG signals and fetal ECG signals, the developed method significantly outperforms the inverse Dower matrix method.

Extraction of fetal electrocardiogram using H ∞ adaptive algorithms

The fetal electrocardiogram (fECG) contains important information regarding the health of the fetus. However, the fECG obtained noninvasively from the abdominal surface electrical recordings of a pregnant woman are dominated by strong interference from the maternal electrocardiogram (mECG). In this paper, based on the H(infinity) principle, two adaptive algorithms are proposed for the extraction of fECG from the trans-abdominal recordings of pregnant women. The motivation behind the application of H(infinity) techniques is the fact that they are robust with respect to model uncertainties and lack of statistical information regarding noise. The proposed algorithms are applied to simulated as well as real multichannel ECG recordings and their performances are compared to that of the well-known least-mean-square (LMS) adaptive algorithm. It is found that the proposed H(infinity) based algorithms perform superior to the LMS algorithm in extracting the fECG signal.

Beat-to-beat repolarisation variability in body surface electrocardiograms.

The repolarisation variability in body surface electrocardiograms has been evaluated by beat-to-beat QT interval variability. Interpolated R-peak time and template T-wave matching algorithms were used to determine the characteristic time points of the R-wave and T-wave, respectively. The T-wave time can be determined accurately and robustly by searching for the best match between a template T-wave and measured T-waves. The authors studied 5 min multichannel ECG recordings (35 channels) measured in 20 healthy subjects. A QT variability of 2.24 +/- 0.79 ms was obtained (1.15 +/- 0.30 ms, if linear detrend was used), which is significantly lower than that reported in several other studies. To explore this discrepancy, the sensitivity of the template matching algorithm to periodic and random noise on the ECG was estimated by a simulation study. The results showed that the repolarisation variability depended on selection of the appropriate lead, the signal-to-noise ratio and the effectiveness of baseline correction. Lead II of a standard 12-lead ECG is a reasonable choice for QT variability analysis; however, precordial leads V3-V6 could be better with regard to the amplitude of the T-wave. Poor signal-to-noise ratios can lead to unrealistic values for repolarisation variability.

Software design for analysis of multichannel intracardial and body surface electrocardiograms

Analysis of multichannel ECG recordings (body surface maps (BSMs) and intracardial maps) requires special software. We created a software package and a user interface on top of a commercial data analysis package ( matlab) by a combination of high-level and low-level programming. Our software was created to satisfy the needs of a diverse group of researchers. It can handle a large variety of recording configurations. It allows for interactive usage through a fast and robust user interface, and batch processing for the analysis of large amounts of data. The package is user-extensible, includes routines for both common and experimental data processing tasks, and works on several computer platforms. The source code is made intelligible using software for structured documentation and is available to the users. The package is currently used by more than ten research groups analysing ECG data worldwide.

Noninvasive fetal electrocardiogram extraction: blind separation versus adaptive noise cancellation

The problem of the fetal electrocardiogram (FECG) extraction from maternal skin electrode measurements can be modeled from the perspective of blind source separation (BSS). Since no comparison between BSS techniques and other signal processing methods has been made, we compare a BSS procedure based on higher-order statistics and Widrow's multireference adaptive noise cancelling approach. As a best-case scenario for this latter method, optimal Wiener-Hopf solutions are considered. Both procedures are applied to real multichannel ECG recordings obtained from a pregnant woman. The experimental outcomes demonstrate the more robust performance of the blind technique and, in turn, verify the validity of the BSS model in this important biomedical application.

Characteristics of multichannel ECG recordings during human ventricular tachyarrhythmias.

Ventricular tachyarrhythmias are a leading cause of mortality. Although ventricular tachycardia (VT) is well understood, ventricular fibrillation (VF) remains an important clinical problem because fundamental information about the mechanisms of this arrhythmia in human hearts is still in short supply. While a number of therapeutic options are available for terminating or treating VT, the best hope for a patient experiencing VF is prompt defibrillation. This article examines approaches to analyzing multichannel data recorded during routine electrophysiology studies for the purpose of obtaining quantitative information about human tachyarrhythmias.

High-quality recording of bioelectric events

In the first part of the review the various mechanisms that could be the cause of interference in bioelectric recordings are considered. It is demonstrated that the performance of a good amplifier can be seriously degraded in its functioning if the whole measurement situation is not taken into account. Several techniques used to reduce interference, of which guarding and driven right leg circuits are the most important, are analysed. In the second part of the review some examples of the application of the theory in practical situations are presented. The instrumentation amplifier circuit normally used in bioelectric recordings is improved for measurements under difficult circumstances. Another application is a low-cost 64-channel amplifier for multichannel ECG recordings. The third application is a device that can be added to bioelectric measurement systems and will provide a major reduction in interference.