Vectorcardiographic loop alignment and morphologic beat-to-beat variability

Unsupervised denoising of the non-invasive fetal electrocardiogram with sparse domain Kalman filtering and vectorcardiographic loop alignment

Objective.Even though the electrocardiogram (ECG) has potential to be used as a monitoring or diagnostic tool for fetuses, the use of non-invasive fetal ECG is complicated by relatively high amounts of noise and fetal movement during the measurement. Moreover, machine learning-based solutions to this problem struggle with the lack of clean reference data, which is difficult to obtain. To solve these problems, this work aims to incorporate fetal rotation correction with ECG denoising into a single unsupervised end-to-end trainable method.Approach.This method uses the vectorcardiogram (VCG), a three-dimensional representation of the ECG, as an input and extends the previously introduced Kalman-LISTA method with a Kalman filter for the estimation of fetal rotation, applying denoising to the rotation-corrected VCG.Main results.The resulting method was shown to outperform denoising auto-encoders by more than 3 dB while achieving a rotation tracking error of less than 33∘. Furthermore, the method was shown to be robust to a difference in signal to noise ratio between electrocardiographic leads and different rotational velocities.Significance.This work presents a novel method for the denoising of non-invasive abdominal fetal ECG, which may be trained unsupervised and simultaneously incorporates fetal rotation correction. This method might prove clinically valuable due the denoised fetal ECG, but also due to the method's objective measure for fetal rotation, which in turn might have potential for early detection of fetal complications.

Present results and methods of vectorcardiographic diagnostics of ischemic heart disease

This article presents an overview of existing approaches to perform vectorcardiographic (VCG) diagnostics of ischemic heart disease (IHD). Individual methodologies are divided into categories to create a comprehensive and clear overview of electrical cardiac activity measurement, signal pre-processing, features extraction and classification procedures. An emphasis is placed on methods describing the electrical heart space (EHS) by several features extraction techniques based on spatiotemporal characteristics or signal modelling and signal transformations. Performance of individual methodologies are compared depending on classification of extent of ischemia, acute forms - myocardial infarction (MI) and myocardial scars localization. Based on a comparison of imaging methods, the advantages of VCG over the standard 12-leads ECG such as providing a 3D orthogonal leads imaging, better performance, and appropriate computer processing are highlighted. The issues of electrical cardiac activity measurements on body surface, the lack of VKG databases supported by a more accurate imaging method, possibility of comparison with the physiology of individual cases are outlined as potential reserves for future research.

Representative QRS loop of the VCG record evaluation

Introduction: This study proposes an algorithm for preprocessing VCG records to obtain a representative QRS loop. Methods: The proposed algorithm uses the following methods: Digital filtering to remove noise from the signal, wavelet-based detection of ECG fiducial points and isoelectric PQ intervals, spatial alignment of QRS loops, QRS time synchronization using root mean square error minimization and ectopic QRS elimination. The representative QRS loop is calculated as the average of all QRS loops in the VCG record. The algorithm is evaluated on 161 VCG records from a database of 58 healthy control subjects, 69 patients with myocardial infarction, and 34 patients with bundle branch block. The morphologic intra-individual beat-to-beat variability rate is calculated for each VCG record. Results and Discussion: The maximum relative deviation is 12.2% for healthy control subjects, 19.3% for patients with myocardial infarction, and 17.2% for patients with bundle branch block. The performance of the algorithm is assessed by measuring the morphologic variability before and after QRS time synchronization and ectopic QRS elimination. The variability is reduced by a factor of 0.36 for healthy control subjects, 0.38 for patients with myocardial infarction, and 0.41 for patients with bundle branch block. The proposed algorithm can be used to generate a representative QRS loop for each VCG record. This representative QRS loop can be used to visualize, compare, and further process VCG records for automatic VCG record classification.

Convolutional Neural Network for Individual Identification Using Phase Space Reconstruction of Electrocardiogram

Electrocardiogram (ECG) biometric provides an authentication to identify an individual on the basis of specific cardiac potential measured from a living body. Convolutional neural networks (CNN) outperform traditional ECG biometrics because convolutions can produce discernible features from ECG through machine learning. Phase space reconstruction (PSR), using a time delay technique, is one of the transformations from ECG to a feature map, without the need of exact R-peak alignment. However, the effects of time delay and grid partition on identification performance have not been investigated. In this study, we developed a PSR-based CNN for ECG biometric authentication and examined the aforementioned effects. Based on a population of 115 subjects selected from the PTB Diagnostic ECG Database, a higher identification accuracy was achieved when the time delay was set from 20 to 28 ms, since it produced a well phase-space expansion of P, QRS, and T waves. A higher accuracy was also achieved when a high-density grid partition was used, since it produced a fine-detail phase-space trajectory. The use of a scaled-down network for PSR over a low-density grid with 32 × 32 partitions achieved a comparable accuracy with using a large-scale network for PSR over 256 × 256 partitions, but it had the benefit of reductions in network size and training time by 10 and 5 folds, respectively.

Signal Quality Assessment of a Novel ECG Electrode for Motion Artifact Reduction

BACKGROUND

The presence of noise is problematic in the analysis and interpretation of the ECG, especially in ambulatory monitoring. Restricting the analysis to high-quality signal segments only comes with the risk of excluding significant arrhythmia episodes. Therefore, the development of novel electrode technology, robust to noise, continues to be warranted.

METHODS

The signal quality of a novel wet ECG electrode (Piotrode) is assessed and compared to a commercially available, commonly used electrode (Ambu). The assessment involves indices of QRS detection and atrial fibrillation detection performance, as well as signal quality indices (ensemble standard deviation and time-frequency repeatability), computed from ECGs recorded simultaneously from 20 healthy subjects performing everyday activities.

RESULTS

The QRS detection performance using the Piotrode was considerably better than when using the Ambu, especially for running but also for lighter activities. The two signal quality indices demonstrated similar trends: the gap in quality became increasingly larger as the subjects became increasingly more active.

CONCLUSIONS

The novel wet ECG electrode produces signals with less motion artifacts, thereby offering the potential to reduce the review burden, and accordingly the cost, associated with ambulatory monitoring.

Characterization of Changes in P-Wave VCG Loops Following Pulmonary-Vein Isolation

Atrial fibrillation is the most common type of cardiac arrhythmia in clinical practice. Currently, catheter ablation for pulmonary-vein isolation is a well-established treatment for maintaining sinus rhythm when antiarrhythmic drugs do not succeed. Unfortunately, arrhythmia recurrence after catheter ablation remains common, with estimated rates of up to 45%. A better understanding of factors leading to atrial-fibrillation recurrence is needed. Hence, the aim of this study is to characterize changes in the atrial propagation pattern following pulmonary-vein isolation, and investigate the relation between such characteristics and atrial-fibrillation recurrence. Fifty patients with paroxysmal atrial fibrillation who had undergone catheter ablation were included in this study. Time-segment and vectorcardiogram-loop-morphology analyses were applied to characterize P waves extracted from 1 min long 12-lead electrocardiogram segments before and after the procedure, respectively. Results showed that P-wave vectorcardiogram loops were significantly less round and more planar, P waves and PR intervals were significantly shorter, and heart rate was significantly higher after the procedure. Differences were larger for patients who did not have arrhythmia recurrences at 2 years of follow-up; for these patients, the pre- and postprocedure P waves could be identified with 84% accuracy.

Non-invasive characterisation of macroreentrant atrial tachycardia types from a vectorcardiographic approach with the slow conduction region as a cornerstone

BACKGROUND AND OBJECTIVES

Macroreentrant atrial tachyarrhythmias (MRATs) can be caused by different reentrant circuits. The treatment for each MRAT type may require ablation at different sites, either at the right or left atria. Unfortunately, the reentrant circuit that drives the arrhythmia cannot be ascertained previous to the electrophysiological intervention.

METHODS

A noninvasive approach based on the comparison of atrial vectorcardiogram (VCG) loops is proposed. An archetype for each group was created, which served as a reference to measure the similarity between loops. Methods were tested in a variety of simulations and real data obtained from the most common right (peritricuspid) and left (perimitral) macroreentrant circuits, each divided into clockwise and counterclockwise subgroups. Adenosine was administered to patients to induce transient AV block, allowing the recording of the atrial signal without the interference of ventricular signals. From the vectorcardiogram, we measured intrapatient loop consistence, similarity of the pathway to archetypes, characterisation of slow velocity regions and pathway complexity.

RESULTS

Results show a considerably higher similarity with the loop of its corresponding archetype, in both simulations and real data. We found the capacity of the vectorcardiogram to reflect a slow velocity region, consistent with the mechanisms of MRAT, and the role that it plays in the characterisation of the reentrant circuit. The intra-patient loop consistence was over 0.85 for all clinical cases while the similarity of the pathway to archetypes was found to be 0.85 ± 0.03, 0.95 ± 0.03, 0.87 ± 0.04 and 0.91 ± 0.02 for the different MRAT types (and p<0.02 for 3 of the 4 groups), and pathway complexity also allowed to discriminate among cases (with p<0.05).

CONCLUSIONS

We conclude that the presented methodology allows us to differentiate between the most common forms of right and left MRATs and predict the existence and location of a slow conduction zone. This approach may be useful in planning ablation procedures in advance.

ECG-Derived Respiratory Rate in Atrial Fibrillation

OBJECTIVE

The present study addresses the problem of estimating the respiratory rate from the morphological ECG variations in the presence of atrial fibrillatory waves (f-waves). The significance of performing f-wave suppression before respiratory rate estimation is investigated.

METHODS

The performance of a novel approach to ECG-derived respiration, named "slope range" (SR) and designed particularly for operation in atrial fibrillation (AF), is compared to that of two well-known methods based on either R-wave angle (RA) or QRS loop rotation angle (LA). A novel rule is proposed for spectral peak selection in respiratory rate estimation. The suppression of f-waves is accomplished using signal- and noise-dependent QRS weighted averaging. The performance evaluation embraces real as well as simulated ECG signals acquired from patients with persistent AF; the estimation error of the respiratory rate is determined for both types of signals.

RESULTS

Using real ECG signals and reference respiratory signals, rate estimation without f-wave suppression resulted in a median error of 0.015 ± 0.021 Hz and 0.019 ± 0.025 Hz for SR and RA, respectively, whereas LA with f-wave suppression resulted in 0.034 ± 0.039 Hz. Using simulated signals, the results also demonstrate that f-wave suppression is superfluous for SR and RA, whereas it is essential for LA.

CONCLUSION

The results show that SR offers the best performance as well as computational simplicity since f-wave suppression is not needed.

SIGNIFICANCE

The respiratory rate can be robustly estimated from the ECG in the presence of AF.

Fetal ECG extraction from time-varying and low-rank noninvasive maternal abdominal recordings

OBJECTIVE

Noninvasive fetal electrocardiography is emerging as a low-cost and high-accuracy technology for fetal cardiac monitoring. Signal processing techniques have been used over the past fifty years in this domain. The current major challenges of this domain, addressed in this study are (1) fetal electrocardiogram (fECG) extraction from few numbers of maternal abdominal channels in low signal-to-noise ratios; (2) online fECG extraction; (3) automatic and online signal quality assessment and channel selection; and (4) accurate and robust fetal R-peak detection and ECG parameter extraction.

APPROACH

Based on the theory of cyclostationarity, auxiliary maternal ECG channel(s) are synthetically constructed and augmented with the input channels. The augmented data are used to develop a robust multichannel source separation algorithm for online/offline fECG extraction, from as few as a single channel, and an accurate fetal R-peak detector using a two-pass matched filter. Several robust signal quality indexes (SQI) and a voting strategy are also proposed for automatic fetal signal quality assessment.

MAIN RESULTS

It is shown that the fECG and the fetal R-peaks can be accurately extracted from standard online available datasets, for which classical source separation methods (requiring many channels) had previously failed. The signal quality indexes fully automate the extraction and channel selection procedure. Finally, the proposed R-peak detector is highly robust to background noise and residual maternal R-peak components.

SIGNIFICANCE

The proposed methods for fECG extraction, R-peak detection and automatic channel selection are evaluated (visually and numerically), on two online available datasets and compared with recently developed algorithms. The proposed algorithm is statistically shown to outperform the benchmarks in terms of average and standard deviation.

Fetal motion estimation from noninvasive cardiac signal recordings

Fetal motility is a widely accepted indicator of the well-being of a fetus. In previous research, it has be shown that fetal motion (FM) is coherent with fetal heart rate accelerations and an indicator for active/rest cycles of the fetus. The most common approach for FM and fetal heart rate (FHR) assessment is by Doppler ultrasound (DUS). While DUS is the most common approach for studying the mechanical activities of the heart, noninvasive fetal electrocardiogram (ECG) and magnetocardiogram (MCG) recording and processing techniques have been considered as a possible competitor (or complement) for the DUS. In this study, a fully automatic and robust framework is proposed for the extraction, ranking and alignment of fetal QRS-complexes from noninvasive fetal ECG/MCG. Using notions from subspace tracking, two measures, namely the actogram and rotatogram, are defined for fetal motion tracking. The method is applied to four fetal ECG/MCG databases, including twin MCG recordings. By defining a novel measure of causality, it is shown that there is significant coherency and causal relationship between the actogram/rotatogram and FHR accelerations/decelerations. Using this measure, it is shown that in many cases, the actogram and rotatogram precede the FHR variations, which supports the idea of motion-induced FHR accelerations/decelerations for these cases and raises attention for the non-motion-induced FHR variations, which can be associated to the fetal central nervous system developments. The results of this study can lead to novel perspectives of the fetal sympathetic and parasympathetic brain systems and future requirements of fetal cardiac monitoring.

Heart morphology differences induced by intrauterine growth restriction and preterm birth measured on the ECG at preadolescent age

Intrauterine Growth Restriction (IUGR) and premature birth are associated with higher risk of cardiovascular diseases throughout adulthood. The aim of this study was to evaluate the influence of these factors in ventricular electrical remodeling in preadolescents. Electrocardiography was performed in a cohort of 33-IUGR, 32-preterm with appropriate weight and 60 controls. Depolarization and repolarization processes were studied by means of the surface ECG, including loops and angles corresponding to QRS and T-waves. The angles between the dominant vector of QRS and the frontal plane XY were different among the study groups: controls [20.03°(10.11°-28.64°)], preterm [25.48°(19.79°-33.56°)], and IUGR [27.77°(16.59°-33.23°)]. When compared to controls, IUGR subjects also presented wider angles between the difference of QRS and T-wave dominant vectors and the XY-plane [5.28°±12.15° vs 0.49°±14.15°, p<0.05] while preterm ones showed smaller frontal QRS-T angle [4.68°(2.20°-12.89°) vs 6.57°(2.72°-11.31°), p<0.05]. Thus, electrical remodeling is present in IUGR and preterm preadolescents, and might predispose them to cardiovascular diseases in adulthood. Follow-up studies are warranted.

A review of beat-to-beat vectorcardiographic (VCG) parameters for analyzing repolarization variability in ECG signals

Elevated ventricular repolarization lability is believed to be linked to the risk of ventricular tachycardia/ventricular fibrillation. However, ventricular repolarization is a complex electrical phenomenon, and abnormalities in ventricular repolarization are not completely understood. To evaluate repolarization lability, vectorcardiography (VCG) is an alternative approach where the electrocardiographic (ECG) signal can be considered as possessing both magnitude and direction. Recent research has shown that VCG is advantageous over ECG signal analysis for identification of repolarization abnormality. One of the key reasons is that the VCG approach does not rely on exact identification of the T-wave offset, which improves the reproducibility of the VCG technique. However, beat-to-beat variability in VCG is an emerging area for the investigation of repolarization abnormality though not yet fully realized. Therefore, the purpose of this review is to explore the techniques, findings, and efficacy of beat-to-beat VCG parameters for analyzing repolarization lability, which may have potential utility for further study.

Analysis of speed, curvature, planarity and frequency characteristics of heart vector movement to evaluate the electrophysiological substrate associated with ventricular tachycardia

BACKGROUND

We developed a novel method of assessing ventricular conduction using the surface ECG.

METHODS

Orthogonal ECGs of 81 healthy controls (age 39.0±14.2 y; 51.8% males; 94% white), were compared with iDower-transformed 12-lead ECGs (both 1000Hz), recorded in 8 patients with infarct-cardiomyopathy and sustained monomorphic ventricular tachycardia (VT) (age 68.0±7.8y, 37.5% male, mean LVEF 29±12%). Normalized speed at 10 QRS segments was calculated as the distance traveled by the heart vector along the QRS loop in three-dimensional space, divided by 1/10th of the QRS duration. Curvature was calculated as the magnitude of the derivative of the QRS loop tangent vector divided by speed. Planarity was calculated as the mean of the dihedral angles between 2 consecutive planes for all planes generated for the median beat. Orbital frequency (a scalar measure of rotation rate of the QRS vector) was calculated as a product of speed and curvature.

RESULTS

Mixed regression analysis showed that speed was slower [6.6 (95%CI 4.4-8.9) vs. 24.6 (95%CI 11.5-37.7)µV/ms; P<0.0001]; orbital frequency was smaller [1.4 (95%CI 1.2-1.6) vs. 6.8 (95%CI 5.4-8.1)ms(-1); P<0.0001], and planarity was larger by 3.6° (95%CI 1.4°-5.8; P=0.002) in VT cases than in healthy controls. ROC AUC for orbital frequency was 0.940 (95%CI 0.935-0.944) across all frequencies and QRS segments. ROC AUC for planarity at 70-249Hz was 0.995 (95%CI 0.985-1.00). ROC AUC for speed at 70-79Hz was 0.979 (95%CI 0.969-0.989).

CONCLUSION

This novel method reveals characteristic features of an abnormal electrophysiological substrate associated with VT.

Feasibility Study of a New Method for Low-Complexity Fetal Movement Detection From Abdominal ECG Recordings

Fetal movement counting can provide valuable information on the fetal health, as a strong decrease in the number of movements can be seen as a precursor to fetal death. Typically, assessment of fetal health by fetal movement counting relies on the maternal perception of fetal activity. The percentage of detected movements is strongly subject dependent and with undivided attention of the mother varies between 37% and 88%. Various methods to assist in fetal movement detection exist based on a wide spectrum of measurement techniques. However, these are unsuitable for ambulatory or long-term observation. In this paper, a novel low-complexity method for fetal movement detection is presented based on amplitude and shape changes in the abdominally recorded fetal ECG. This method was compared to a state-of-the-art method from the literature. Using ultrasound-based movement annotations as ground truth, the presented method outperforms the state-of-the-art abdominal-ECG based method, with a sensitivity, specificity, and accuracy of 56%, 68%, and 63%, respectively. Additionally, a significant reduction in algorithm complexity is achieved, possibly enabling continuous ambulatory fetal movement detection and early detection of reduced fetal motility.

Beat-to-beat spatiotemporal variability in the T vector is associated with sudden cardiac death in participants without left ventricular hypertrophy: the Atherosclerosis Risk in Communities (ARIC) Study

Background

Despite advances in prevention and treatment of cardiovascular disease, sudden cardiac death (SCD) remains a clinical challenge. Risk stratification in the general population is needed.

Methods and Results

Beat‐to‐beat spatiotemporal variability in the T vector was measured as the mean angle between consecutive T‐wave vectors (mean TT′ angle) on standard 12‐lead ECGs in 14 024 participants in the Atherosclerosis Risk in Communities (ARIC) study. Subjects with left ventricular hypertrophy, atrial arrhythmias, frequent ectopy, ventricular pacing, or QRS duration ≥120 ms were excluded. The mean spatial TT′ angle was 5.21±3.55°. During a median of 14 years of follow‐up, 235 SCDs occurred (1.24 per 1000 person‐years). After adjustment for demographics, coronary heart disease risk factors, and known ECG markers for SCD, mean TT′ angle was independently associated with SCD (hazard ratio 1.089; 95% CI 1.044 to 1.137; P<0.0001). A mean TT′ angle >90th percentile (>9.57°) was associated with a 2‐fold increase in the hazard for SCD (hazard ratio 2.01; 95% CI 1.28 to 3.16; P=0.002). In a subgroup of patients with T‐vector amplitude ≥0.2 mV, the association with SCD was almost twice as strong (hazard ratio 3.92; 95% CI 1.91 to 8.05; P<0.0001). A significant interaction between mean TT′ angle and age was found: TT′ angle was associated with SCD in participants aged <55 years (hazard ratio 1.096; 95% CI 0.043 to 1.152; P<0.0001) but not in participants aged ≥55 years (P_interaction=0.009).

Conclusions

In a large, prospective, community‐based cohort of left ventricular hypertrophy–free participants, increased beat‐to‐beat spatiotemporal variability in the T vector, as assessed by increasing TT′ angle, was associated with SCD.

A novel low-complexity post-processing algorithm for precise QRS localization

Precise localization of QRS complexes is an essential step in the analysis of small transient changes in instant heart rate and before signal averaging in QRS morphological analysis. Most localization algorithms reported in literature are either not robust to artifacts, depend on the sampling rate of the ECG recordings or are too computationally expensive for real-time applications, especially in low-power embedded devices. This paper proposes a localization algorithm based on the intersection of tangents fitted to the slopes of R waves detected by any QRS detector. Despite having a lower complexity, this algorithm achieves comparable trigger jitter to more complex localization methods without requiring the data to first be upsampled. It also achieves high localization precision regardless of which QRS detector is used as input. It is robust to clipping artifacts and to noise, achieving an average localization error below 2 ms and a trigger jitter below 1 ms on recordings where no additional artifacts were added, and below 8 ms for recordings where the signal was severely degraded. Finally, it increases the accuracy of template-based false positive rejection, allowing nearly all mock false positives added to a set of QRS detections to be removed at the cost of a very small decrease in sensitivity. The localization algorithm proposed is particularly well-suited for implementation in embedded, low-power devices for real-time applications.

Vectorcardiographic loop alignment for fetal movement detection using the expectation-maximization algorithm and support vector machines

Reduced fetal movement is an important parameter to assess fetal distress. Currently, no suitable methods are available that can objectively assess fetal movement during pregnancy. Fetal vectorcardiographic (VCG) loop alignment could be such a method. In general, the goal of VCG loop alignment is to correct for motion-induced changes in the VCGs of (multiple) consecutive heartbeats. However, the parameters used for loop alignment also provide information to assess fetal movement. Unfortunately, current methods for VCG loop alignment are not robust against low-quality VCG signals. In this paper, a more robust method for VCG loop alignment is developed that includes a priori information on the loop alignment, yielding a maximum a posteriori loop alignment. Classification, based on movement parameters extracted from the alignment, is subsequently performed using support vector machines, resulting in correct classification of (absence of) fetal movement in about 75% of cases. After additional validation and optimization, this method can possibly be employed for continuous fetal movement monitoring.

Acute myocardial ischemia monitoring before and during angioplasty by a novel vectorcardiographic parameter set

BACKGROUND

This work evaluates the vectorcardiographic dynamic changes in ischemic patients before and during Percutaneous Transluminal Coronary Angioplasty (PTCA).

METHODS

Four QRS-loop parameters were computed in 51 ischemic and 52 healthy subjects with the objective of assessing the vectorcardiographic differences between both groups: maximum vector magnitude (QRS(mVM)), planar area (QRS(PA)), maximum distance between centroid and loop (QRS(mDCL)) and perimeter (QRS(P)).The conventional ST-change vector magnitude (STC(VM)), QRS-vector difference (QRS(VD)) and spatial ventricular gradient (SVG) were also calculated.

RESULTS

Statistical minute-by-minute PTCA comparison against a healthy population showed that ischemic patients monitoring is greatly enhanced when all the QRS-loop parameters, in combination with the standard STC(VM), QRS(VD) and SVG indexes, are used in the classification. Sensitivity and Specificity, in turn, reached rather high values, 95.4% and 95.2%, respectively.

CONCLUSIONS

These new vectorcardiographic set of complementary QRS-loop parameters, when combined with the classics STC(VM), QRS(VD) and SVG indexes, increase sensitivity and specificity for acute ischemia monitoring.

Novel Bayesian vectorcardiographic loop alignment for improved monitoring of ECG and fetal movement

The continuous analysis of electrocardiographic (ECG) signals is complicated by morphological variability in the ECG due to movement of the heart. By aligning vectorcardiographic loops, movement-induced ECG variations can be partly corrected for. Existing methods for loop alignment can account for loop rotation, scaling, and time delays, but they lack the possibility to include a priori information on any of these transformations, and they are unreliable in case of low-quality signals, such as fetal ECG signals. The inclusion of a priori information might aid in the robustness of loop alignment and is, hence, proposed in this paper. We provide a generic Bayesian framework to derive our loop alignment method. In this framework, existing methods can be readily derived as well, as a simplification of our method. The loop alignment is evaluated by comparing its performance in loop alignment to two existing methods, for both adult and fetal ECG recordings. For the adult ECG recordings, a quantitative performance assessment shows that the developed method outperforms the existing method in terms of robustness. For the fetal ECG recordings, it is demonstrated that the developed method can be used to correct ECG signals for movement-induced morphology changes (enabling diagnostics) and that the method is capable of classifying recorded ECG signals to periods of fetal movement or rest ( 0.01). This information on fetal movement can also serve as a valuable diagnostic tool.

Novel set of vectorcardiographic parameters for the identification of ischemic patients

New signal processing techniques have enabled the use of the vectorcardiogram (VCG) for the detection of cardiac ischemia. Thus, we studied this signal during ventricular depolarization in 80 ischemic patients, before undergoing angioplasty, and 52 healthy subjects with the objective of evaluating the vectorcardiographic difference between both groups so leading to their subsequent classification. For that matter, seven QRS-loop parameters were analyzed, i.e.: (a) Maximum Vector Magnitude; (b) Volume; (c) Planar Area; (d) Maximum Distance between Centroid and Loop; (e) Angle between XY and Optimum Plane; (f) Perimeter and, (g) Area-Perimeter Ratio. For comparison, the conventional ST-Vector Magnitude (ST(VM)) was also calculated. Results indicate that several vectorcardiographic parameters show significant differences between healthy and ischemic subjects. The identification of ischemic patients via discriminant analysis using ST(VM) produced 73.2% Sensitivity (Sens) and 73.9% Specificity (Spec). In our study, the QRS-loop parameter with the best global performance was Volume, which achieved Sens=64.5% and Spec=74.6%. However, when all QRS-loop parameters and ST(VM) were combined, we obtained Sens=88.5% and Spec=92.1%. In conclusion, QRS loop parameters can be accepted as a complement to conventional ST(VM) analysis in the identification of ischemic patients.

Respiration effect on wavelet-based ECG T-wave end delineation strategies

The main purpose of this paper is to study the influence of the mechanical effect of respiration over the T-wave end delineation. We compared the performance of an automatic delineation system based on the wavelet transform (WT), considering single lead (SL), global delineation locations obtained from SL annotations (SLR), and multilead (ML) approaches. The linear relation between the variations on T-wave end locations obtained with each of the methods and the mechanical effect of respiration was quantified using spectral coherence and ARARX modeling both in simulated signals and in real data. We also explored the evolution of the vectorcardiographic spatial loop using the projection on the main direction of the WT in the region close to the T-wave end ( T(e)) and its relation with respiration. The dispersion of the additional T-wave end location error due to respiration was reduced by 15% using SLR with respect to SL, while ML allows for a reduction of around 40%. The percentage of that error correlated with respiration was in average 99% using SL while 82% and 72% using SLR and ML, respectively. Thus, results suggest that ML is the most adequate strategy for T-wave delineation, allowing the reduction of the instability of T-wave end location caused by respiration.

Analysis of QRS loop in the Vectorcardiogram of patients with Chagas' disease

In the present work, we have studied the QRS loop in the Vectorcardiogram (VCG) of 95 chronic chagasic patients classified in different groups (I, II and III) according to their degree of myocardial damage. For comparison, the VCGs of 11 healthy subjects used as control group (Group O) were also examined. The QRS loop was obtained for each patient from the XYZ orthogonal leads of their High-Resolution Electrocardiogram (HRECG) records. In order to analyze the variations of QRS loop in each detected beat, it has been proposed in this study the following vectorcardiographic parameters a) Maximum magnitude of the cardiac depolarization vector, b) Volume, c) Area of QRS loop, d) Ratio between the Area and Perimeter, e) Ratio between the major and minor axes of the QRS loop and f) QRS loop Energy. It has been found that one or more indexes exhibited statistical differences (p < 0.05) between groups 0-II, O-III, I-II, I-III and II-III. We concluded that the proposed method could be use as complementary diagnosis technique to evaluate the degree of myocardial damage in chronic chagasic patients.

Analysis of QRS loop changes in the beat-to-beat Vectocardiogram of ischemic patients undergoing PTCA

In the present work, we have studied dynamic changes of QRS loop in the Vectocardiogram (VCG) of 80 patients that underwent Percutaneous Transluminal Coronary Angioplasty (PTCA). The VCG was obtained for each patient using the XYZ orthogonal leads of their electrocardiographic (ECG) records acquired before, during and after PTCA procedure. In order to analyze the variations of VCG, it has been proposed in this study the following parameters a) Maximum module of the cardiac depolarization vector, b) Volume, c) and Area of vectocardiographic loop corresponding to the QRS complex of each beat, d) Maximum distance between Centroid and the Loop, e) Angle between the XY plane and the Optimum Plane, f) Relation between the Area and Perimeter. The results obtained indicate that the parameters proposed show significant statistics differences (p-value<0.05) before, during (with some exceptions at the first minute of balloon inflation) and after PTCA. We conclude that the variations observed in the proposed parameters correctly represent not only the morphological changes in the depolarization VCG but also they reflect the modifications in the levels of cardiac ischemia induced by PTCA.

ECG fingerprints of obstructed breathing in sleep apnea patients

This article aims to identify the potential indicators of obstructive apnea (OA) in the ECG, based on the traces of QRS area from multiple ECG leads. We compare the difference in these traces' phase relation found during and after each OA episode to the difference between the first and second half of the OA and between split halves of epochs of normal respiration (NR).

Body movement activity recognition for ambulatory cardiac monitoring

Wearable electrocardiogram (W-ECG) recorders are increasingly in use by people suffering from cardiac abnormalities who also choose to lead an active lifestyle. The challenge presently is that the ECG signal is influenced by motion artifacts induced by body movement activity (BMA) of the wearer. The usual practice is to develop effective filtering algorithms which will eliminate artifacts. Instead, our goal is to detect the motion artifacts and classify the type of BMA from the ECG signal itself. We have recorded the ECG signals during specified BMAs, e.g., sitting still, walking, movements of arms and climbing stairs, etc. with a single-lead system. The collected ECG signal during BMA is presumed to be an additive mix of signals due to cardiac activities, motion artifacts and sensor noise. A particular class of BMA is characterized by applying eigen decomposition on the corresponding ECG data. The classification accuracies range from 70% to 98% for various class combinations of BMAs depending on their uniqueness based on this technique. The above classification is also useful for analysis of P and T waves in the presence of BMA.

A robust method for ECG-based estimation of the respiratory frequency during stress testing

A robust method is presented for electrocardiogram (ECG)-based estimation of the respiratory frequency during stress testing. Such ECGs contain highly nonstationary noise and exhibit changes in QRS morphology which, when combined with the dynamic nature of the respiratory frequency, make most existing methods break down. The present method exploits the oscillatory pattern of the rotation angles of the heart's electrical axis as induced by respiration. The series of rotation angles, obtained from least-squares loop alignment, is subject to power spectral analysis and estimation of the respiratory frequency. Robust techniques are introduced to handle the nonstationary properties of exercise ECGs. The method is evaluated by means of both simulated signals, and ECG/airflow signals recorded from 14 volunteers and 20 patients during stress testing. The resulting respiratory frequency estimation error is, for simulated signals, equal to 0.5% +/- 0.2%, mean +/- SD (0.002 +/- 0.001 Hz), whereas the error between respiratory frequencies of the ECG-derived method and the airflow signals is 5.9% +/- 4% (0.022 +/- 0.016Hz). The results suggest that the method is highly suitable for analysis of noisy ECG signals recorded during stress testing.

Estimation of the respiratory frequency using spatial information in the VCG

A new method for extracting respiratory signals from the ECG/VCG is presented. The method is based on the alignment of an observed VCG loop to a reference loop with respect to the transformations of rotation and time synchronisation. The resulting series of estimated rotation angles reflects respiratory-induced changes in the electrical axis of the heart. The respiratory frequency is estimated by power spectral analysis of the derived respiration signal. The value of respiratory modulation of the heart rate is considered by analysing the cross power spectrum of the signals related to rotation angles and heart rate. For comparison, a respiratory signal derived from the QRS area of two different leads is implemented. The performance of the methods is validated on a database with simultaneously recorded VCG and respiratory signals acquired from 20 healthy subjects. The agreement between the respiratory frequencies obtained from the derived and the respiratory signals is presented. The angle-based respiratory signal is found to produce the best agreement with a gross median error of only 4.2%.

ECG-based detection of body position changes in ischemia monitoring

The purpose of this paper is to analyze and detect changes in body position (BPC) during electrocardiogram (ECG) recording. These changes are often manifested as shifts in the electrical axis and may be misclassified as ischemic changes during ambulatory monitoring. We investigate two ECG signal processing methods for detecting BPCs. Different schemes for feature extraction are used (spatial and scalar), while preprocessing, trend postprocessing and detection are identical. The spatial approach is based on VCG loop rotation angles and the scalar approach is based on the Karhunen-Loève transform (KLT) coefficients. The methods are evaluated on two different databases: a database with annotated BPCs and the STAFF III database with recordings from rest and during angioplasty-induced ischemia but not including BPCs. The angle-based detector results in performance values of detection probability PD = 95%, false alarm probability PF = 3% in the BPC database and false alarm rate in the STAFF III database in control ECGs during rest RF(c) = 2 h(-1) (episodes per hour) and in ischemia recordings during angioplasty RF(a) = 7 h(-1), whereas the KLT-based detector produces values of PD = 89%, PF = 3%, RF(c) = 4 h(-1), and RF(a) = 11 h(-1), respectively. Including information on noise level in the detection process to reduce the number of false alarms, performance values of PD approximately equal to 90%, PF approximately equal to 1%, RF(c) approximately equal to 1 h(-1) and RF(a) approximately equal to 2 h(-1) are obtained with both methods. It is concluded that reliable detection of BPCs may be achieved using the ECG signal and should work in parallel to ischemia detectors.

Detection of body position changes using the surface electrocardiogram

A method for detecting body position changes that uses the surface vectorcardiogram (VCG) is presented. Such changes are often manifested as sudden shifts in the electrical axis of the heart and can erroneously be interpreted as acute ischaemic events. Axis shifts were detected by analysing the rotation angles obtained from the alignment of successive VCG loops to a reference loop. Following the rejection of angles originating from noise events, the detection of body position changes was performed on the angle series using a Bayesian approach. On a database of ECG recordings from normal subjects performing a predefined sequence of body position changes, a detection rate of 92% and a false alarm rate of 7% was achieved.

Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation

A new method for QRST cancellation is presented for the analysis of atrial fibrillation in the surface electrocardiogram (ECG). The method is based on a spatiotemporal signal model which accounts for dynamic changes in QRS morphology caused, e.g., by variations in the electrical axis of the heart. Using simulated atrial fibrillation signals added to normal ECGs, the results show that the spatiotemporal method performs considerably better than does straightforward average beat subtraction (ABS). In comparison to the ABS method, the average QRST-related error was reduced to 58 percent. The results obtained from ECGs with atrial fibrillation agreed very well with those from simulated fibrillation signals.

Sampling rate and the estimation of ensemble variability for repetitive signals

The measurement of ensemble variability in time-aligned event signals is studied in relation to sampling rate requirements. The theoretical analysis is based on statistical modelling of time misalignment in which the time resolution is limited by the length of the sampling interval. For different signal-to-noise ratios (SNRs), the sampling rate is derived which limits the misalignment effect to less than 10% of the noise effect. Each signal is assumed to be corrupted by additive noise. Using a normal QRS complex with a high SNR (approximately equal to 30 dB), a sampling rate of approximately 3 kHz is needed for accurate ensemble variability measurements. This result is surprising since it implies that the Nyquist rate is far too low for accurate variability measurements. The theoretical results are supplemented with results obtained from an ECG database of 94 subjects for which the ensemble variability is computed at different sampling rates using signal interpolation. The ensemble variability is substantially reduced (40%) when increasing the rate from 1 to 3 kHz, thus corroborating the results suggested by the theoretical analysis.

Vectorcardiographic loop alignment and the measurement of morphologic beat-to-beat variability in noisy signals

The measurement of subtle morphologic beat-to-beat variability in the electrocardiogram (ECG)/vectorcardiogram (VCG) is complicated by the presence of noise which is caused by, e.g., respiration and muscular activity. A method was recently presented which reduces the influence of such noise by performing spatial and temporal alignment of VCG loops. The alignment is performed in terms of scaling, rotation and time synchronization of the loops. Using an ECG simulation model based on propagation of action potentials in cardiac tissue, the ability of the method to separate morphologic variability of physiological origin from respiratory activity was studied. Morphologic variability was created by introducing a random variation in action potential propagation between different compartments. The results indicate that the separation of these two activities can be done accurately at low to moderate noise levels (less than 10 microV). At high noise levels, the estimation of the rotation angles was found to break down in an abrupt manner. It was also shown that the breakdown noise level is strongly dependent on loop morphology; a planar loop corresponds to a lower breakdown noise level than does a nonplanar loop.

Beat-to-beat QRS variability in the 12-lead ECG and the detection of coronary artery disease

The aim of this article was to study beat-to-beat QRS variability in patients with ischemia and old myocardial infarction using the 12-lead resting electrocardiogram (ECG). The variability analysis was based on beats that have been synchronized in time with an iterative alignment technique. The QRS variability was measured in patients submitted for myocardial scintigraphy. Those with a normal myocardial scintigraphy (called NO, n = 34, mean age 57 years, 23 women) were compared with a group with both myocardial infarction and exercise-induced ischemia (called ISCINF, n = 27, mean age 57 years, 5 women). The mean QRS variability was somewhat smaller in lead I in ISCINF than in NO, and there was no statistically significant difference in QRS variability among the groups in leads II, III, and V1-V6. Using a multivariate approach, the joint variability in leads I, II, II, and V1-V6 was used for calculating receiver operating characteristics based on a leave-one-out procedure. The sensitivity for detecting coronary artery disease was 75% at a specificity of 50%. It is concluded that beat-to-beat QRS variability in the 12-lead ECG does not discriminate between the presence and absence of coronary artery disease sufficiently well for clinical purposes.