A new algorithm for rhythm discrimination in cardioverter defibrillators based on the initial voltage changes of the ventricular electrogram

Aims: Ventricular activation onset is faster in supraventricular beats than in ventricular rhythms. The aim of this study was to evaluate a criterion to differentiate supraventricular (SVT) from ventricular tachycardia (VT) based on the analysis of the initial voltage changes in ICD-stored morphology electrograms. Methods. Far field ICD-stored EGMs were obtained from 68 VT and 38 SVT episodes in 16 patients. The first EGM peak was detected, three consecutive time epochs were defined within the preceding 80 ms window and the voltage changes with respect to a sinus template were analysed during each time period and combined into a single parameter for rhythm discrimination. Results. The algorithm was tested in an independent validation group of 442 VT and 97 SVT spontaneous episodes obtained from 22 patients with a dual chamber ICD. The area under the receiver-operator characteristics (ROC) curve indicated that the arrhythmia separability with this method was 0.95 (tolerance interval: 0.85-0.99) and 0.98 (0.87-0.99) for the control and validation groups respectively. A specificity of 0.91 was obtained at 95% sensitivity in the validation group. Conclusion. The analysis of voltage changes during the initial ventricular activation process is feasible using the far field stored electrograms of an ICD system and yields a high sensitivity and specificity for arrhythmia discrimination

Generalization and Regularization for Inverse Cardiac Estimators

Electrocardiographic Imaging (ECGI) aims to estimate the intracardiac potentials noninvasively, hence allowing the clinicians to better visualize and understand many arrhythmia mechanisms. Most of the estimators of epicardial potentials use a signal model based on an estimated spatial transfer matrix together with Tikhonov regularization techniques, which works well specially in simulations, but it can give limited accuracy in some real data. Based on the quasielectrostatic potential superposition principle, we propose a simple signal model that supports the implementation of principled out-of-sample algorithms for several of the most widely used regularization criteria in ECGI problems, hence improving the generalization capabilities of several of the current estimation methods. Experiments on simple cases (cylindrical and Gaussian shapes scrutinizing fast and slow changes, respectively) and on real data (examples of torso tank measurements available from Utah University, and an animal torso and epicardium measurements available from Maastricht University, both in the EDGAR public repository) show that the superposition-based out-of-sample tuning of regularization parameters promotes stabilized estimation errors of the unknown source potentials, while slightly increasing the re-estimation error on the measured data, as natural in non-overfitted solutions. The superposition signal model can be used for designing adequate out-of-sample tuning of Tikhonov regularization techniques, and it can be taken into account when using other regularization techniques in current commercial systems and research toolboxes on ECG

Manifold analysis of the P-wave changes induced by pulmonary vein isolation during cryoballoon procedure

Background/Aim: In atrial fibrillation (AF) ablation procedures, it is desirable to know whether a proper disconnection of the pulmonary veins (PVs) was achieved. We hypothesize that information about their isolation could be provided by analyzing changes in P-wave after ablation. Thus, we present a method to detect PV disconnection using P-wave signal analysis. Methods: Conventional P-wave feature extraction was compared to an automatic feature extraction procedure based on creating low-dimensional latent spaces for cardiac signals with the Uniform Manifold Approximation and Projection (UMAP) method. A database of patients (19 controls and 16 AF individuals who underwent a PV ablation procedure) was collected. Standard 12-lead ECG was recorded, and P-waves were segmented and averaged to extract conventional features (duration, amplitude, and area) and their manifold representations provided by UMAP on a 3-dimensional latent space. A virtual patient was used to validate these results further and study the spatial distribution of the extracted characteristics over the whole torso surface. Results: Both methods showed differences between P-wave before and after ablation. Conventional methods were more prone to noise, P-wave delineation errors, and inter-patient variability. P-wave differences were observed in the standard leads recordings. However, higher differences appeared in the torso region over the precordial leads. Recordings near the left scapula also yielded noticeable differences. Conclusions: P-wave analysis based on UMAP parameters detects PV disconnection after ablation in AF patients and is more robust than heuristic parameterization. Moreover, additional leads different from the standard 12-lead ECG should be used to detect PV isolation and possible future reconnections better

Differences in the yield of the implantable loop recorder between secondary and tertiary centers

Background: The implantable loop recorder (ILR) is a useful tool for diagnosis of syncope or palpitations. Its easy use and safety have extended its use to secondary hospitals (those without an Electrophysiology Lab). The aim of the study was to compare results between secondary and tertiary hospitals. Methods: National prospective and multicenter registry of patients with an ILR inserted for clinical reasons. Data were collected in an online database. The follow-up ended when the first diagnostic clinical event occurred, or 1 year after implantation. Data were analyzed according to the center of reference; hospitals with Electrophysiology Lab were considered Tertiary Hospi­tals, while those hospitals without a lab were considered Secondary Hospitals. Results: Seven hundred and forty-three patients (413 [55.6%] men; 65 ± 16 year-old): 655 (88.2%) from Tertiary Centers (TC) and 88 (11.8%) from Secondary Centers (SC). No differences in clinical characteristics between both groups were found. The electrophysi­ologic study and the tilt table test were conducted more frequently in Tertiary Centers. Fol­low-up was conducted for 680 (91.5%) patients: 91% in TC and 94% in SC. There was a higher rate of final diagnosis among SC patients (55.4% vs. 30.8%; p < 0.001). Tertiary Hospital patients showed a trend towards a higher rate of neurally mediated events (20% vs. 4%), while bradyarrhythmias were more frequent in SC (74% vs. 60%; p = 0.055). The rate of deaths and adverse events was similar in both populations. Conclusions: Patients with an ILR in SC and TC have differences in terms of the use of complementary tests, but not in clinical characteristics. There was a higher rate of diagnosis in Secondary Hospital patients.

Short-term reproducibility of parameters characterizing atrial fibrillatory waves

Objective: To study reproducibility of f-wave parameters in terms of inter- and intrapatient variation. Approach: Five parameters are investigated: dominant atrial frequency (DAF), f-wave amplitude, phase dispersion, spectral organization, and spatiotemporal variability. For each parameter, the variance ratio R, defined as the ratio between inter- and intrapatient variance, is computed; a larger R corresponds to better stability and reproducibility. The study population consists of 20 high-quality ECGs recorded from patients with atrial fibrillation (11/9 paroxysmal/persistent). Main results: The well-established parameters DAF and f-wave amplitude were associated with considerably larger R-values (13.1 and 21.0, respectively) than phase dispersion (2.4), spectral organization (2.4), andspatiotemporal variability (2.7). The use of an adaptive harmonic frequency tracker to estimate the DAF resulted in a larger R (13.1) than did block-based maximum likelihood estimation (6.3). Significance: This study demonstrates a noticeable difference in reproducibility among f-wave parameters, a resultwhich should be taken into account when performing f-wave analysis

A new approach to the intracardiac inverse problem using Laplacian distance kernel

Abstract Background The inverse problem in electrophysiology consists of the accurate estimation of the intracardiac electrical sources from a reduced set of electrodes at short distances and from outside the heart. This estimation can provide an image with relevant knowledge on arrhythmia mechanisms for the clinical practice. Methods based on truncated singular value decomposition (TSVD) and regularized least squares require a matrix inversion, which limits their resolution due to the unavoidable low-pass filter effect of the Tikhonov regularization techniques. Methods We propose to use, for the first time, a Mercer’s kernel given by the Laplacian of the distance in the quasielectrostatic field equations, hence providing a Support Vector Regression (SVR) formulation by following the principles of the Dual Signal Model (DSM) principles for creating kernel algorithms. Results Simulations in one- and two-dimensional models show the performance of our Laplacian distance kernel technique versus several conventional methods. Firstly, the one-dimensional model is adjusted for yielding recorded electrograms, similar to the ones that are usually observed in electrophysiological studies, and suitable strategy is designed for the free-parameter search. Secondly, simulations both in one- and two-dimensional models show larger noise sensitivity in the estimated transfer matrix than in the observation measurements, and DSM−SVR is shown to be more robust to noisy transfer matrix than TSVD. Conclusion These results suggest that our proposed DSM−SVR with Laplacian distance kernel can be an efficient alternative to improve the resolution in current and emerging intracardiac imaging systems

A Flexible 12-Lead/Holter Device with Compression Capabilities for Low-Bandwidth Mobile-ECG Telemedicine Applications

In recent years, a number of proposals for electrocardiogram (ECG) monitoring based on mobile systems have been delivered. We propose here an STM32F-microcontroller-based ECG mobile system providing both long-term (several weeks) Holter monitoring and 12-lead ECG recording, according to the clinical standard requirements for these kinds of recordings, which in addition can yield further digital compression at stages close to the acquisition. The system can be especially useful in rural areas of developing countries, where the lack of specialized medical personnel justifies the introduction of telecardiology services, and the limitations of coverage and bandwidth of cellular networks require the use of efficient signal compression systems. The prototype was implemented using a small architecture, with a 16-bits-per-sample resolution. We also used a low-noise instrumentation amplifier TI ADS1198, which has a multiplexer and an analog-to-digital converter (16 bits and 8 channels) connected to the STM32F processor, the architecture of which incorporates a digital signal processing unit and a floating-point unit. On the one hand, the system portability allows the user to take the prototype in her/his pocket and to perform an ECG examination, either in 12-lead controlled conditions or in Holter monitoring, according to the required clinical scenario. An app in the smartphone is responsible for giving the users a friendly interface to set up the system. On the other hand, electronic health recording of the patients are registered in a web application, which in turn allows them to connect to the Internet from their cellphones, and the ECG signals are then sent though a web server for subsequent and ubiquitous analysis by doctors at any convenient terminal device. In order to determine the quality of the received signals, system testing was performed in the three following scenarios: (1) The prototype was connected to the patient and the signals were subsequently stored; (2) the prototype was connected to the patient and the data were subsequently transferred to the cellphone; (3) the prototype was connected to the patient, and the data were transferred to the cellphone and to the web via the Internet. An additional benchmarking test with expert clinicians showed the clinical quality provided by the system. The proposed ECG system is the first step and paves the way toward mobile cardiac monitors in terms of compatibility with the electrocardiographic practice, including the long-term monitoring, the usability with 12 leads, and the possibility of incorporating signal compression at the early stages of the ECG acquisition

Changes in f-wave characteristics during cryoballoon catheter ablation

OBJECTIVE: Changes in ECG-derived parameters are studied in atrial fibrillation (AF) patients undergoing cryoballoon catheter ablation.APPROACH: Parameters characterizing f-wave frequency, morphology by phase dispersion, and amplitude are estimated using a model-based statistical approach. These parameters are studied before, during, and after ablation, as well as for AF type (paroxysmal/persistent). Seventy-seven (49/28 paroxysmal/persistent) AF patients undergoing de novo catheter ablation are included in the study, out of which 31 (16/15 paroxysmal/persistent) were in AF during the whole procedure. A signal quality index (SQI) is used to identify analyzable segments.MAIN RESULTS: f-wave frequency decreased significantly during ablation (p = 0.001), in particular after ablation of the inferior right pulmonary vein (p < 0.05). Frequency and phase dispersion differed significantly between paroxysmal and persistent AF (p = 0.001 and p < 0.05, respectively).SIGNIFICANCE: This study demonstrates that a decrease in f-wave frequency can be distinguished during catheter ablation. The use of an SQI ensures reliable analysis and produces results significantly different from those obtained without an SQI

On the robustness of multiscale indices for long-term monitoring in cardiac signals

The identification of patients with increased risk of Sudden Cardiac Death (SCD) has been widely studied during recent decades, and several quantitative measurements have been proposed from the analysis of the electrocardiogram (ECG) stored in 1-day Holter recordings. Indices based on nonlinear dynamics of Heart Rate Variability (HRV) have shown to convey predictive information in terms of factors related with the cardiac regulation by the autonomous nervous system, and among them, multiscale methods aim to provide more complete descriptions than single-scale based measures. However, there is limited knowledge on the suitability of nonlinear measurements to characterize the cardiac dynamics in current long-term monitoring scenarios of several days. Here, we scrutinized the long-term robustness properties of three nonlinear methods for HRV characterization, namely, the Multiscale Entropy (MSE), the Multiscale Time Irreversibility (MTI), and the Multifractal Spectrum (MFS). These indices were selected because all of them have been theoretically designed to take into account the multiple time scales inherent in healthy and pathological cardiac dynamics, and they have been analyzed so far when monitoring up to 24 h of ECG signals, corresponding to about 20 time scales. We analyzed them in 7-day Holter recordings from two data sets, namely, patients with Atrial Fibrillation and with Congestive Heart Failure, by reaching up to 100 time scales. In addition, a new comparison procedure is proposed to statistically compare the poblational multiscale representations in different patient or processing conditions, in terms of the non-parametric estimation of confidence intervals for the averaged median differences. Our results show that variance reduction is actually obtained in the multiscale estimators. The MSE (MTI) exhibited the lowest (largest) bias and variance at large scales, whereas all the methods exhibited a consistent description of the large-scale processes in terms of multiscale index robustness. In all the methods, the used algorithms could turn to give some inconsistency in the multiscale profile, which was checked not to be due to the presence of artifacts, but rather with unclear origin. The reduction in standard error for several-day recordings compared to one-day recordings was more evident in MSE, whereas bias was more patently present in MFS. Our results pave the way of these techniques towards their use, with improved algorithmic implementations and nonparametric statistical tests, in long-term cardiac Holter monitoring scenarios

An Interoperable System toward Cardiac Risk Stratification from ECG Monitoring

Many indices have been proposed for cardiovascular risk stratification from electrocardiogram signal processing, still with limited use in clinical practice. We created a system integrating the clinical definition of cardiac risk subdomains from ECGs and the use of diverse signal processing techniques. Three subdomains were defined from the joint analysis of the technical and clinical viewpoints. One subdomain was devoted to demographic and clinical data. The other two subdomains were intended to obtain widely defined risk indices from ECG monitoring: a simple-domain (heart rate turbulence (HRT)), and a complex-domain (heart rate variability (HRV)). Data provided by the three subdomains allowed for the generation of alerts with different intensity and nature, as well as for the grouping and scrutinization of patients according to the established processing and risk-thresholding criteria. The implemented system was tested by connecting data from real-world in-hospital electronic health records and ECG monitoring by considering standards for syntactic (HL7 messages) and semantic interoperability (archetypes based on CEN/ISO EN13606 and SNOMED-CT). The system was able to provide risk indices and to generate alerts in the health records to support decision-making. Overall, the system allows for the agile interaction of research and clinical practice in the Holter-ECG-based cardiac risk domain