Fast Algorithm for Vectorcardiogram and Interbeat Intervals Analysis: Application for Premature Ventricular Contractions Classification

In this study we investigated the adequacy of two non-orthogonal ECG leads from Holter recordings to provide reliable vectorcardiogram (VCG) parameters. The VCG loop was constructed using the QRS samples in a fixed-size window around the fiducial point. We developed an algorithm for fast approximation of the VCG loop, estimation of its area and calculation of relative VCG characteristics, which are expected to be minimally dependent on the patient individuality and the ECG recording conditions. Moreover, in order to obtain independent from the heart rate temporal QRS characteristics, we introduced a parameter for estimation of the differences of the interbeat RR intervals. The statistical assessment of the proposed VCG and RR interval parameters showed distinguishing distributions for N and PVC beats. The reliability for PVC detection of the extracted parameter set was estimated independently with two classification methods - a stepwise discriminant analysis and a decision-tree-like classification algorithm, using the publicly available MIT-BIH arrhythmia database. The accuracy achieved with the stepwise discriminant analysis presented sensitivity of 91% and specificity of 95.6%, while the decision-tree-like technique assured sensitivity of 93.3% and specificity of 94.6%. We suggested possibilities for accuracy improvement with adequate electrodes placement of the Holter leads, supplementary analysis of the type of the predominant beats in the reference VCG matrix and smaller step for VCG loop approximation

Detection of Electrode Interchange in Precordial and Orthogonal ECG Leads

Abstrac

Assessment of the Efficacy of Pulsed Biphasic Defibrillation Shocks for Treatment of Out-of-hospital Cardiac Arrest

This study evaluates the efficacy of a Pulsed Biphasic Waveform (PBW) for treatment of out-of-hospital cardiac arrest (OHCA) patients in ventricular fibrillation (VF). Large database (2001-2006), collected with automated external defibrillators (AED), (FRED®, Schiller Medical SAS, France), is processed.In Study1 we compared the defibrillation efficacy of two energy stacks (90-130-180 J) vs. (130-130-180 J) in 248 OHCA VF patients. The analysis of the first shock PBW efficacy proves that energies as low as 90 J are able to terminate VF in a large proportion of OHCA patients (77% at 5 s and 69% at 30 s). Although the results show a trend towards the benefit of higher energy PBW with 130 J (86% at 5 s, 73% at 30 s), the difference in shock efficacy does not reach statistical significance. Both PBW energy stacks (90-130-180 J) and (130-130-180 J) achieve equal success rates of defibrillation. Analysis of the post-shock rhythm after the first shock is also provided.For Study2 of 21 patients with PBW shocks (130-130-180 J), we assessed some attending OHCA circumstances: call-to-shock delay (median 16min, range 11-41 min), phone advices of CPR (67%). About 50% of the patients were admitted alive to hospital, and 19% were discharged from hospital. After the first shock, patients admitted to hospital are more often presenting organized rhythm (OR) (27% to 55%) than patients not admitted (0% to 10%), with significant difference at 15 s and 30 s. Post-shock VFs appear significantly rare until 15s for patients admitted to hospital (0% to 9%) than for patients not admitted to hospital (40% to 50%). Return of OR (ROOR) and efficacy to defibrillate VF at 5 s and 15 s with first shock are important markers to predict patient admission to hospital

Magnetic stimulation for non-homogeneous biological structures

BACKGROUND: Magnetic stimulation has gained relatively wide application in studying nervous system structures. This technology has the advantage of reduced excitation of sensory nerve endings, and hence results in quasi-painless action. It has become clinically accepted modality for brain stimulation. However, theoretical and practical solutions for assessment of induced current distribution need more detailed and accurate consideration. Some possible analyses are proposed for distribution of the current induced from excitation current contours of different shape and disposition. Relatively non-difficult solutions are shown, applicable for two- and three-dimensional analysis. METHODS: The boundary conditions for field analysis by the internal Dirichlet problem are introduced, based on the vector potential field excited by external current coils. The feedback from the induced eddy currents is neglected. Finite element modeling is applied for obtaining the electromagnetic fields distribution in a non-homogeneous domain. RESULTS: The distributions were obtained in a non-homogeneous structure comprised of homogeneous layers. A tendency was found of the induced currents to follow paths in lower resistivity layers, deviating from the expected theoretical course for a homogeneous domain. Current density concentrations occur at the boundary between layers, suggesting the possibility for focusing on, or predicting of, a zone of stimulation. CONCLUSION: The theoretical basis and simplified approach for generation of 3D FEM networks for magnetic stimulation analysis are presented, applicable in non-homogeneous and non-linear media. The inconveniences of introducing external excitation currents are avoided. Thus, the possibilities are improved for analysis of distributions induced by time-varying currents from contours of various geometry and position with respect to the medium

Estimation of current density distribution under electrodes for external defibrillation

BACKGROUND: Transthoracic defibrillation is the most common life-saving technique for the restoration of the heart rhythm of cardiac arrest victims. The procedure requires adequate application of large electrodes on the patient chest, to ensure low-resistance electrical contact. The current density distribution under the electrodes is non-uniform, leading to muscle contraction and pain, or risks of burning. The recent introduction of automatic external defibrillators and even wearable defibrillators, presents new demanding requirements for the structure of electrodes. METHOD AND RESULTS: Using the pseudo-elliptic differential equation of Laplace type with appropriate boundary conditions and applying finite element method modeling, electrodes of various shapes and structure were studied. The non-uniformity of the current density distribution was shown to be moderately improved by adding a low resistivity layer between the metal and tissue and by a ring around the electrode perimeter. The inclusion of openings in long-term wearable electrodes additionally disturbs the current density profile. However, a number of small-size perforations may result in acceptable current density distribution. CONCLUSION: The current density distribution non-uniformity of circular electrodes is about 30% less than that of square-shaped electrodes. The use of an interface layer of intermediate resistivity, comparable to that of the underlying tissues, and a high-resistivity perimeter ring, can further improve the distribution. The inclusion of skin aeration openings disturbs the current paths, but an appropriate selection of number and size provides a reasonable compromise

Common-Mode Driven Synchronous Filtering of the Powerline Interference in ECG

Powerline interference (PLI) is a major disturbing factor in ground-free biopotential acquisition systems. PLI produces both common-mode and differential input voltages. The first is suppressed by a high common-mode rejection ratio of bioamplifiers. However, the differential PLI component evoked by the imbalance of electrode impedances is amplified together with the diagnostic differential biosignal. Therefore, PLI filtering is always demanded and commonly managed by analog or digital band-rejection filters. In electrocardiography (ECG), PLI filters are not ideal, inducing QRS and ST distortions as a transient reaction to steep slopes, or PLI remains when its amplitude varies and PLI frequency deviates from the notch. This study aims to minimize the filter errors in wide deviation ranges of PLI amplitudes and frequencies, introducing a novel biopotential readout circuit with a software PLI demodulator–remodulator concept for synchronous processing of both differential-mode and common-mode signals. A closed-loop digital synchronous filtering (SF) algorithm is designed to subtract a PLI estimation from the differential-mode input in real time. The PLI estimation branch connected to the SF output includes four stages: (i) prefilter and QRS limiter; (ii) quadrature demodulator of the output PLI using a common-mode driven reference; (iii) two servo loops for low-pass filtering and the integration of in-phase and quadrature errors; (iv) quadrature remodulator for synthesis of the estimated PLI using the common-mode signal as a carrier frequency. A simulation study of artificially generated PLI sinusoids with frequency deviations (48–52 Hz, slew rate 0.01–0.1 Hz/s) and amplitude deviations (root mean square (r.m.s.) 50–1000 μV, slew rate 10–200 μV/s) is conducted for the optimization of SF servo loop settings with artificial signals from the CTS-ECG calibration database (10 s, 1 lead) as well as for the SF algorithm test with 40 low-noise recordings from the Physionet PTB Diagnostic ECG database (10 s, 12 leads) and CTS-ECG analytical database (10 s, 8 leads). The statistical study for the PLI frequencies (48–52 Hz, slew rate ≤ 0.1 Hz/s) and amplitudes (≤1000 μV r.m.s., slew rate ≤ 40 μV/s) show that maximal SF errors do not exceed 15 μV for any record and any lead, which satisfies the standard requirements for a peak ringing noise of < 25 μV. The signal-to-noise ratio improvement reaches 57–60 dB. SF is shown to be robust against phase shifts between differential- and common-mode PLI. Although validated for ECG signals, the presented SF algorithm is generalizable to different biopotential acquisition settings via surface electrodes (electroencephalogram, electromyogram, electrooculogram, etc.) and can benefit many diagnostic and therapeutic medical devices

Atrioventricular Synchronization for Detection of Atrial Fibrillation and Flutter in One to Twelve ECG Leads Using a Dense Neural Network Classifier

This study investigates the use of atrioventricular (AV) synchronization as an important diagnostic criterion for atrial fibrillation and flutter (AF) using one to twelve ECG leads. Heart rate, lead-specific AV conduction time, and P-/f-wave amplitude were evaluated by three representative ECG metrics (mean value, standard deviation), namely RR-interval (RRi-mean, RRi-std), PQ-interval (PQi-mean, PQI-std), and PQ-amplitude (PQa-mean, PQa-std), in 71,545 standard 12-lead ECG records from the six largest PhysioNet CinC Challenge 2021 databases. Two rhythm classes were considered (AF, non-AF), randomly assigning records into training (70%), validation (20%), and test (10%) datasets. In a grid search of 19, 55, and 83 dense neural network (DenseNet) architectures and five independent training runs, we optimized models for one-lead, six-lead (chest or limb), and twelve-lead input features. Lead-set performance and SHapley Additive exPlanations (SHAP) input feature importance were evaluated on the test set. Optimal DenseNet architectures with the number of neurons in sequential [1st, 2nd, 3rd] hidden layers were assessed for sensitivity and specificity: DenseNet [16,16,0] with primary leads (I or II) had 87.9–88.3 and 90.5–91.5%; DenseNet [32,32,32] with six limb leads had 90.7 and 94.2%; DenseNet [32,32,4] with six chest leads had 92.1 and 93.2%; and DenseNet [128,8,8] with all 12 leads had 91.8 and 95.8%, indicating sensitivity and specificity values, respectively. Mean SHAP values on the entire test set highlighted the importance of RRi-mean (100%), RR-std (84%), and atrial synchronization (40–60%) for the PQa-mean (aVR, I), PQi-std (V2, aVF, II), and PQi-mean (aVL, aVR). Our focus on finding the strongest AV synchronization predictors of AF in 12-lead ECGs would lead to a comprehensive understanding of the decision-making process in advanced neural network classifiers. DenseNet self-learned to rely on a few ECG behavioral characteristics: first, characteristics usually associated with AF conduction such as rapid heart rate, enhanced heart rate variability, and large PQ-interval deviation in V2 and inferior leads (aVF, II); second, characteristics related to a typical P-wave pattern in sinus rhythm, which is best distinguished from AF by the earliest negative P-peak deflection of the right atrium in the lead (aVR) and late positive left atrial deflection in lateral leads (I, aVL). Our results on lead-selection and feature-selection practices for AF detection should be considered for one- to twelve-lead ECG signal processing settings, particularly those measuring heart rate, AV conduction times, and P-/f-wave amplitudes. Performances are limited to the AF diagnostic potential of these three metrics. SHAP value importance can be used in combination with a human expert’s ECG interpretation to change the focus from a broad observation of 12-lead ECG morphology to focusing on the few AV synchronization findings strongly predictive of AF or non-AF arrhythmias. Our results are representative of AV synchronization findings across a broad taxonomy of cardiac arrhythmias in large 12-lead ECG databases

Common-Mode Driven Synchronous Filtering of the Powerline Interference in ECG

Powerline interference (PLI) is a major disturbing factor in ground-free biopotential acquisition systems. PLI produces both common-mode and differential input voltages. The first is suppressed by a high common-mode rejection ratio of bioamplifiers. However, the differential PLI component evoked by the imbalance of electrode impedances is amplified together with the diagnostic differential biosignal. Therefore, PLI filtering is always demanded and commonly managed by analog or digital band-rejection filters. In electrocardiography (ECG), PLI filters are not ideal, inducing QRS and ST distortions as a transient reaction to steep slopes, or PLI remains when its amplitude varies and PLI frequency deviates from the notch. This study aims to minimize the filter errors in wide deviation ranges of PLI amplitudes and frequencies, introducing a novel biopotential readout circuit with a software PLI demodulator–remodulator concept for synchronous processing of both differential-mode and common-mode signals. A closed-loop digital synchronous filtering (SF) algorithm is designed to subtract a PLI estimation from the differential-mode input in real time. The PLI estimation branch connected to the SF output includes four stages: (i) prefilter and QRS limiter; (ii) quadrature demodulator of the output PLI using a common-mode driven reference; (iii) two servo loops for low-pass filtering and the integration of in-phase and quadrature errors; (iv) quadrature remodulator for synthesis of the estimated PLI using the common-mode signal as a carrier frequency. A simulation study of artificially generated PLI sinusoids with frequency deviations (48–52 Hz, slew rate 0.01–0.1 Hz/s) and amplitude deviations (root mean square (r.m.s.) 50–1000 μV, slew rate 10–200 μV/s) is conducted for the optimization of SF servo loop settings with artificial signals from the CTS-ECG calibration database (10 s, 1 lead) as well as for the SF algorithm test with 40 low-noise recordings from the Physionet PTB Diagnostic ECG database (10 s, 12 leads) and CTS-ECG analytical database (10 s, 8 leads). The statistical study for the PLI frequencies (48–52 Hz, slew rate ≤ 0.1 Hz/s) and amplitudes (≤1000 μV r.m.s., slew rate ≤ 40 μV/s) show that maximal SF errors do not exceed 15 μV for any record and any lead, which satisfies the standard requirements for a peak ringing noise of < 25 μV. The signal-to-noise ratio improvement reaches 57–60 dB. SF is shown to be robust against phase shifts between differential- and common-mode PLI. Although validated for ECG signals, the presented SF algorithm is generalizable to different biopotential acquisition settings via surface electrodes (electroencephalogram, electromyogram, electrooculogram, etc.) and can benefit many diagnostic and therapeutic medical devices

Recognition of Supraventricular Arrhythmias in Holter ECG Recordings by ECHOView Color Map: A Case Series Study

Ambulatory 24–72 h Holter ECG monitoring is recommended for patients with suspected arrhythmias, which are often transitory and might remain unseen in resting standard 12-lead ECG. Holter manufacturers provide software diagnostic tools to assist clinicians in evaluating these large amounts of data. Nevertheless, the identification of short arrhythmia events and differentiation of the arrhythmia type might be a problem in limited Holter ECG leads. This observational clinical study aims to explore a novel and weakly investigated ECG modality integrated into a commercial diagnostic tool ECHOView (medilog DARWIN 2, Schiller AG, Switzerland), while used for the interpretation of long-term Holter-ECG records by a cardiologist. The ECHOView transformation maps the beat waveform amplitude to a color-coded bar. One ECHOView page integrates stacked color bars of about 1740 sequential beats aligned by R-peak in a window (R ± 750 ms). The collected 3-lead Holter ECG recordings from 86 patients had a valid duration of 21 h 20 min (19 h 30 min–22 h 45 min), median (quartile range). The ECG rhythm was reviewed with 3491 (3192–3723) standard-grid ECG pages and a substantially few number of 51 (44–59) ECHOView pages that validated the ECHOView compression ratio of 67 (59–74) times. Comments on the ECG rhythm and ECHOView characteristic patterns are provided for 14 examples representative of the most common rhythm disorders seen in our population, including supraventricular arrhythmias (supraventricular extrasystoles, paroxysmal supraventricular arrhythmia, sinus tachycardia, supraventricular tachycardia, atrial fibrillation, and flutter) and ventricular arrhythmias (ventricular extrasystoles, non-sustained ventricular tachycardia). In summary, the ECHOView color map transforms the ECG modality into a novel diagnostic image of the patient’s rhythm that is comprehensively interpreted by a cardiologist. ECHOView has the potential to facilitate the manual overview of Holter ECG recordings, to visually identify short-term arrhythmia episodes, and to refine the diagnosis, especially in high-rate arrhythmias