A novel mobile transtelephonic system with synthesized 12-lead ECG

The problem of synthesizing the standard 12-lead electrocardiogram (ECG) from the signals recorded using three special ECG leads is studied in detail. The implementation of that concept into the design of a new mobile ECG transtelephonic system is presented. The system has two separate units: a stationary diagnostic-calibration center and a mobile ECG device with integrated electrodes. The patient records by himself three special leads with the mobile ECG recorder and sends data via cellular phone to the personal computer in the diagnostic center where standard 12-lead ECG is numerically reconstructed on the base of the patient transformation matrix previously calculated into the calibration process. The experimental study shows high accuracy of the reconstructed ECG.     

A new 3-D display method for 12-lead ECG

A new three-dimensional (3-D) 12-lead electrocardiogram (ECG) display method is presented which employs a 3-D rectangular coordinate system to display the 12-lead cardiac electric signals in two 3-D graphs. The 3-D graph consists of a temporal axis representing the time domain of the cardiac signals, a spatial axis representing the lead positions, and an amplitude axis representing the voltages of the cardiac signals. The six horizontal plane leads and the other six frontal plane leads were displayed in two 3-D graphs, respectively. The voltages of the cardiac signals were represented in rainbow-like colors. Cubic interpolation was employed to insert interconnecting points between neighboring leads on each plane and to smooth the surface of the 3-D ECG graphs. The 3-D ECG graphs of a normal subject, a patient with myocardial infarction, and a patient with left bundle branch block were presented in this paper. This new display method could not only be used as a complementary display method to the 12-lead ECG, but also provide physicians with an overall integral view about the spatial distribution of the cardiac signals.     

Analysis of abnormal signals within the QRS complex of thehigh-resolution electrocardiogram

Presents a new, quantitative approach to measuring abnormal intra-QRS signals, using the high-resolution electrocardiogram (HRECG). These signals are conventionally known as QRS “notches and slurs.” They are measured qualitatively and form the basis for the ECG identification of myocardial infarction. The HRECG is used for detection of ventricular late potentials (LP), which are linked with the presence of a reentry substrate for ventricular tachycardia (VT) after a myocardial infarction. LP's are defined as signals from areas of delayed conduction which outlast the normal QRS period. The authors' objective is to quantify very low-level abnormal signals that may not outlast the normal QRS period. In this work, abnormal intra-QRS potentials (AIQP) were characterized by removing the predictable, smooth part of the QRS from the original waveform. This was represented as the impulse response of an ARX parametric model, with model order selected empirically from a training data set. AIQP were estimated using the residual of the modeling procedure. Critical AIQP parameters to separate VT and non-VT subjects were obtained using discriminant functions. Results suggest that AIQP indexes are a new predictive index of the HRECG for VT. The concept of abnormal intra-QRS potentials permits the characterization of pathophysiological signals contained wholly within the normal QRS period, but related to arrhythmogenesis. The new method may have other applications, such as detection of myocardial ischemia and improved ECG identification of the site of myocardial infarction, particularly in the absence of Q waves     

Limited Lead Selection for Estimation of Body Surface Potential Maps in Electrocardiography

Body surface potential mapping has shown promise as a technique to improve the resolution and accuracy of diagnostic electrocardiography, but the cost and effort required to obtain maps have made wide spread use impractical. As a step toward a practical system, the problems of redundancy and uniqueness of electrocardiographic signal information contained in large numbers of leads were investigated. An algorithm for optimal selection of a limited number of leads was developed. Data obtained from 132 human subjects including some with normal electrocardiograms (ECG) as well as some with abnormal ECGs, were used in the study. Estimation of body surface potentials from limited leads was evaluated using three criteria, including rms error, mean correlation coefficient between limited lead and total lead maps, and error to signal power ratio. Using 30 leads the average rms error was 32 ?V, average correlation coefficient was .983 and noise to signal power was 3.5% in the presence of 20 ?V rms noise. Another finding was that optimal sites are not unique, i.e., different sets of optimal sites may be found which perform equally well. This result has practical implications for the design of lead systems for estimating maps on the critically ill and on patients undergoing stress tests.     

In silico investigation of electrically silent acute cardiac ischemia in the human ventricles

Acute cardiac ischemia, which is caused by the occlusion of a coronary artery, often leads to lethal ventricular arrhythmias or heart failure. The early diagnosis of this pathology is based on changes of the electrocardiogram (ECG), i.e., mainly shifts of the ST segment. However, the underlying mechanisms responsible for these shifts are not completely understood. Furthermore, clinical observations indicate that some acute ischemia cases can hardly be detected using standard 12-lead ECG only. Therefore, multiscale computer simulations of cardiac ischemia using realistic models of human ventricles were carried out in this work. For this purpose, the transmembrane voltage distributions in the heart and the corresponding body surface potentials were computed with varying transmural extent of the ischemic region at different ischemia stages. Some of the simulated ischemia cases were " electrically silent," i.e., they could hardly be identified in the 12-lead ECG.     

Improved performance of bayesian solutions for inverse electrocardiography using multiple information sources

The usual goal in inverse electrocardiography (ECG) is to reconstruct cardiac electrical sources from body surface potentials and a mathematical model that relates the sources to the measurements. Due to attenuation and smoothing that occurs in the thorax, the inverse ECG problem is ill-posed and imposition of a priori constraints is needed to combat this ill-posedness. When the problem is posed in terms of reconstructing heart surface potentials, solutions have not yet achieved clinical utility; limitations include the limited availability of good a priori information about the solution and the lack of a "good" error metric. We describe an approach that combines body surface measurements and standard forward models with two additional information sources: statistical prior information about epicardial potential distributions and sparse simultaneous measurements of epicardial potentials made with multielectrode coronary venous catheters. We employ a Bayesian methodology which offers a general way to incorporate these information sources and additionally provides statistical performance analysis tools. In a simulation study, we first compare solutions using one or more of these information sources. Then, we study the effects of varying the number of sparse epicardial potential measurements on reconstruction accuracy. To evaluate accuracy, we used the Bayesian error covariance as well as traditional error metrics such as relative error. Our results show that including even sparsely sampled information from coronary venous catheters can substantially improve the reconstruction of epicardial potential distributions and that a Bayesian framework provides a feasible approach to using this information. Moreover, computing the Bayesian error standard deviations offers a means to indicate confidence in the results even in the absence of validation data.     

Cancellation of ventricular activity in the ECG: evaluation of novel and existing methods

Due to the much higher amplitude of the electrical activity of the ventricles in the surface electrocardiogram (ECG), its cancellation is crucial for the analysis and characterization of atrial fibrillation. In this paper, two different methods are proposed for this cancellation. The first one is an average beat subtraction type of method. Two sets of templates are created: one set for the ventricular depolarization waves and one for the ventricular repolarization waves. Next, spatial optimization (rotation and amplitude scaling) is applied to the QRS templates. The second method is a single beat method that cancels the ventricular involvement in each cardiac cycle in an independent manner. The estimation and cancellation of the ventricular repolarization is based on the concept of dominant T and U waves. Subsequently, the atrial activities during the ventricular depolarization intervals are estimated by a weighted sum of sinusoids observed in the cleaned up segments. ECG signals generated by a biophysical model as well as clinical ECG signals are used to evaluate the performance of the proposed methods in comparison to two standard ABS-based methods.     

A wavelet-based ECG delineator: evaluation on standard databases

In this paper, we developed and evaluated a robust single-lead electrocardiogram (ECG) delineation system based on the wavelet transform (WT). In a first step, QRS complexes are detected. Then, each QRS is delineated by detecting and identifying the peaks of the individual waves, as well as the complex onset and end. Finally, the determination of P and T wave peaks, onsets and ends is performed. We evaluated the algorithm on several manually annotated databases, such as MIT-BIH Arrhythmia, QT, European ST-T and CSE databases, developed for validation purposes. The QRS detector obtained a sensitivity of Se = 99.66% and a positive predictivity of P+ = 99.56% over the first lead of the validation databases (more than 980,000 beats), while for the well-known MIT-BIH Arrhythmia Database, Se and P+ over 99.8% were attained. As for the delineation of the ECG waves, the mean and standard deviation of the differences between the automatic and manual annotations were computed. The mean error obtained with the WT approach was found not to exceed one sampling interval, while the standard deviations were around the accepted tolerances between expert physicians, outperforming the results of other well known algorithms, especially in determining the end of T wave.     

Atrial activity extraction for atrial fibrillation analysis using blind source separation

This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA and VA present non-Gaussian distributions; and 3) the generation of the surface ECG potentials from the cardioelectric sources can be regarded as a narrow-band linear propagation process. To empirically endorse these claims, an ICA algorithm is applied to recordings from seven patients with persistent AF. We demonstrate that the AA source can be identified using a kurtosis-based reordering of the separated signals followed by spectral analysis of the sub-Gaussian sources. In contrast to traditional methods, the proposed BSS-based approach is able to obtain a unified AA signal by exploiting the atrial information present in every ECG lead, which results in an increased robustness with respect to electrode selection and placement.     

Effect of Cardiac Motion on Solution of the Electrocardiography Inverse Problem

Previous studies of the ECG inverse problem often assumed that the heart was static during the cardiac cycle; consequently, a time-dependent geometrical error was thought to be unavoidably introduced. In this paper, cardiac motion is included in solutions to the electrocardiographic inverse problem. Cardiac dynamics are simulated based on a previously developed biventricular model that coupled the electrical and mechanical properties of the heart, and simulated the ventricular wall motion and deformation. In the forward computation, the heart surface source model method is employed to calculate the epicardial potentials from the action potentials, and then, the simulated epicardial potentials are used to calculate body surface potentials. With the inclusion of cardiac motion, the calculated body surface potentials are more reasonable than those in the case of static assumption. In the epicardial potential-based inverse studies, the Tikhonov regularization method is used to handle ill-posedness of the ECG inverse problem. The simulation results demonstrate that the solutions obtained from both the static ECG inverse problem and the dynamic ECG inverse problem approaches are approximately the same during the QRS complex period, due to the minimal deformation of the heart in this period. However, with the most obvious deformation occurring during the ST-T segment, the static assumption of heart always generates something akin to geometry noise in the ECG inverse problem causing the inverse solutions to have large errors. This study suggests that the inclusion of cardiac motion in solving the ECG inverse problem can lead to more accurate and acceptable inverse solutions.      

Changes in body-surface electrocardiograms from geometric remodeling with obesity

Both diabetes and obesity cause cardiac dysfunction. To separate consequences of geometric changes due to obesity from electrophysiological ones, we investigated how changes in cardiac and torso geometry affected body-surface ECGs. For this study, we modified the realistic heart and torso models of the simulation package ECGSIM. ECGs were calculated from action potentials on the heart surface using our bidomain forward-problem solution. These ECGs were studied using spectral- and principal-component analyses and isopotential and energy maps. We found relative errors over the body-surface during the QT interval of 12%, 14%, and 68% for hypertrophy of the heart, extension of the abdomen, and heart displacement with obesity, respectively. The major change to the standard 12-lead set also occurred with heart displacement. The mean relative error over the QT interval in the precordial leads was 78% with heart displacement. These results demonstrate the limitations of using standard lead sets to characterize electrocardiographic changes in obese subjects and point to the need for more inclusive measures, such as body-surface mapping and inverse electrocardiography, to describe electrical remodeling in the presence of habitus changes due to obesity.     

P-wave morphology assessment by a gaussian functions-based model in atrial fibrillation patients

Aim of this study was to present a P-wave model, based on a linear combination of Gaussian functions, to quantify morphological aspects of P-wave in patients prone to atrial fibrillation (AF). Five-minute ECG recordings were performed in 25 patients with permanent dual chamber pacemakers. Patients were divided into high-risk and low-risk groups, including patients with and without AF episodes in the last 6 mo preceding the study, respectively. ECG signals were acquired using a 32-lead mapping system for high-resolution biopotential measurement (ActiveTwo, Biosemi, The Netherlands, sample frequency 2 kHz, 24-bit resolution). Up to 8 Gaussian models have been computed for each averaged P-wave extracted from every lead. The P-wave morphology was evaluated by extracting seven parameters. Classical time-domain parameters, based on P-wave duration estimation, have been also estimated. We found that the P-wave morphology can be effectively modeled by a linear combination of Gaussian functions. In addition, the combination of time-domain and morphological parameters extracted from the Gaussian function-based model of the P-wave improves the identification of patients having different risks of developing AF.     

A Real-Time QRS Detection Algorithm

We have developed a real-time algorithm for detection of the QRS complexes of ECG signals. It reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width. A special digital bandpass filter reduces false detections caused by the various types of interference present in ECG signals. This filtering permits use of low thresholds, thereby increasing detection sensitivity. The algorithm automatically adjusts thresholds and parameters periodically to adapt to such ECG changes as QRS morphology and heart rate. For the standard 24 h MIT/BIH arrhythmia database, this algorithm correctly detects 99.3 percent of the QRS complexes.     

Ventricular late potentials characterization in time-frequencydomain by means of a wavelet transform

The main transforms of Cohen's class allow signal representation simultaneously in time and frequency domains. Wavelet transforms make it possible to link the temporal window width to the analyzing frequency and leads to a “modified wavelet transform” which improves resolution both in time and frequency. A simulation study illustrates the artifacts of every time-frequency representation on pure sinusoids and gives performance evaluation of the different methods when searching a sinusoid embedded in a QRS complex. Analyses of real signals from healthy and pathological subjects confirm the simulation results and complete the characterization of ventricular late potentials yet detected by signal averaging     

ECG data compression with time-warped polynomials

Presents a new adaptive compression method for ECGs. The method represents each R-R interval by an optimally time-warped polynomial. It achieves a high-quality approximation at less than 250 bits/s. The author shows that the corresponding rates for other transform based schemes (the DCT and the DLT) are always higher. Also, the new method is less sensitive to errors in QRS detection and it removes more (white) noise from the signal. The reconstruction errors are distributed more uniformly in the new scheme and the peak error is usually lower. The reconstruction method is also useful for adaptive filtering of noisy ECG signals     

Evaluation of Esophageal Electrodes for Recording His?Purkinje Activity Based Upon Signal Variance

Signal averaging the ECG to observe low level signals generated by His?Purkinje system (HPS) has many disadvantages and has not been widely used. This is partly due to the inability to distinguish between atrial and HPS potentials within the PR segment. To more clearly observe the onset of the HPS activity, several leads with an esophageal electrode were studied and compared to a bipolar surface lead. Signal variance was calculated to estimate the noise levels present in all lead systems. The bipolar surface lead consistently provided reproducible HPS waveforms with accurate estimates of noise levels. The leads with an esophageal electrode (bipolar or esophago?thoracic) failed to show reproducible HPS waveforms and had higher noise levels than the bipolar surface lead as measured by signal variance. The cause of these problems is the motion of the electrode within the esophagus, as visualized fluoroscopically. While the novel lead systems were not adequate for recording HPS waveforms, the analytic methods for evaluating signal averaged recordings from various lead systems provided a basis for optimizing this approach for quantifying low level cardiac signals.     

A New Technique for Monitoring Heart Signals?Part II: Orthogonal Lead Extraction

In Part I, instrumentation design is given for recording ECG signals from a home bathtub setup. In Part II, it is asserted that these bathtub signals are the projections of the heart dipole vector. This assertion is tested and the corresponding coefficients of the projection matrix are computed by monitoring the bathtub ECG signals for a subject as well as his orthogonal X, Y, Z leads on a PDP-9 computer. The least-squares estimation technique is used to determine the projection matrix. To compensate for the magnitude and phase distortion of the bathtub ECG signals, suitable digital as well as analog compensators are designed. A comparison of orthogonal leads extracted from bathtub leads and similar leads obtained from the HP1520A vectorcardiograph is given for five different subjects. It is shown that the average standard deviation obtained for these five subjects is 12.6 percent.     

A pseudodifferential amplifier for bioelectric events with DC-offset compensation using two-wired amplifying electrodes

Most wired active electrodes reported so far have a gain of one and require at least three wires. This leads to stiff cables, large connectors and additional noise for the amplifier. The theoretical advantages of amplifying the signal on the electrodes right from the source has often been described, however, rarely implemented. This is because a difference in the gain of the electrodes due to component tolerances strongly limits the achievable common mode rejection ratio (CMRR). In this paper, we introduce an amplifier for bioelectric events where the major part of the amplification (40 dB) is achieved on the electrodes to minimize pick-up noise. The electrodes require only two wires of which one can be used for shielding, thus enabling smaller connecters and smoother cables. Saturation of the electrodes is prevented by a dc-offset cancelation scheme with an active range of +/- 250 mV. This error feedback simultaneously allows to measure the low frequency components down to dc. This enables the measurement of slow varying signals, e.g., the change of alertness or the depolarization before an epileptic seizure normally not visible in a standard electroencephalogram (EEG). The amplifier stage provides the necessary supply current for the electrodes and generates the error signal for the feedback loop. The amplifier generates a pseudodifferential signal where the amplified bioelectric event is present on one lead, but the common mode signal is present on both leads. Based on the pseudodifferential signal we were able to develop a new method to compensate for a difference in the gain of the active electrodes which is purely software based. The amplifier system is then characterized and the input referred noise as well as the CMRR are measured. For the prototype circuit the CMRR evaluated to 78 dB (without the driven-right-leg circuit). The applicability of the system is further demonstrated by the recording of an ECG.     

Heart-surface reconstruction and ECG electrodes localization using fluoroscopy, epipolar geometry and stereovision: application to noninvasive imaging of cardiac electrical activity

To date there is no imaging modality for cardiac arrhythmias which remain the leading cause of sudden death in the United States (> 300000/yr.). Electrocardiographic imaging (ECGI), a noninvasive modality that images cardiac arrhythmias from body surface potentials, requires the geometrical relationship between the heart surface and the positions of body surface ECG electrodes. A photographic method was validated in a mannequin and used to determine the three-dimensional coordinates of body surface ECG electrodes to within 1 mm of their actual positions. Since fluoroscopy is available in the cardiac electrophysiology (EP) laboratory where diagnosis and treatment of cardiac arrhythmias is conducted, a fluoroscopic method to determine the heart surface geometry was developed based on projective geometry, epipolar geometry, point reconstruction, b-spline interpolation and visualization. Fluoroscopy-reconstructed hearts in a phantom and a human subject were validated using high-resolution computed tomography (CT) imaging. The mean absolute distance error for the fluoroscopy-reconstructed heart relative to the CT heart was 4 mm (phantom) and 10 mm (human). In the human, ECGI images of normal cardiac electrical activity on the fluoroscopy-reconstructed heart showed close correlation with those obtained on the CT heart. Results demonstrate the feasibility of this approach for clinical noninvasive imaging of cardiac arrhythmias in the interventional EP laboratory.     

Estimation accuracy of P wave and QRS complex occurrence times in the ECG: The accuracy for simplified theoretical and computer simulated waveforms

One of the main points of interest in the study of the dynamic behaviour of ECG time intervals is the accuracy with which characteristic moments can be estimated in the various waveform segments such as the P wave or QRS complex. In this study, the error involved in such estimation is regarded as due to the superposition of various types of disturbances (noise, hum and fluctuations in amplitude and symmetry) on a supposedly ideal ECG waveform. The effect of these disturbances on estimation accuracy is investigated for three estimation methods (peak estimation, double level estimation and matched filter estimation) by two different approaches; one based on use of a highly simplified theoretical model permitting the derivation of mathematical expressions for the estimation error, and one involving computer-aided simulation of ECG waveforms, based on real ECG data, with various types of disturbances on the basis of recorded ECG data. Both approaches indicate that noise and hum make the main contribution to estimation error, and that matched filter estimation is likely to give best estimation accuracy for both P waves and QRS complexes.