LVSP and LBBP Result in Similar or Improved LV Synchrony and Hemodynamics Compared to BVP.

BACKGROUND: The effect of left ventricular septal myocardial pacing (LVSP) and left bundle branch pacing (LBBP) on ventricular synchrony and left ventricular (LV) hemodynamic status is poorly understood. OBJECTIVES: The aim of this study was to investigate the impact of LVSP and LBBP vs biventricular pacing (BVP) on ventricular electrical synchrony and hemodynamic status in cardiac resynchronization therapy patients. METHODS: In cardiac resynchronization therapy candidates with LV conduction disease, ventricular synchrony was assessed by measuring QRS duration (QRSd) and using ultra-high-frequency electrocardiography. LV electrical dyssynchrony was assessed as the difference between the first activation in leads V1 to V8 to the last from leads V4 to V8. LV hemodynamic status was estimated using invasive systolic blood pressure measurement during multiple transitions between LBBP, LVSP, and BVP. RESULTS: A total of 35 patients with a mean LV ejection fraction of 29% and a mean QRSd of 168 ± 24 ms were included. Thirteen had ischemic cardiomyopathy. QRSd during BVP, LVSP, and LBBP was the same, but LBBP provided shorter LV electrical dyssynchrony than BVP (-10 ms; 95% CI: -16 to -4 ms; P = 0.001); the difference between LVSP and BVP was not significant (-5 ms; 95% CI: -12 to 1 ms; P = 0.10). LBBP was associated with higher systolic blood pressure than BVP (4%; 95% CI: 2% to 5%; P < 0.001), whereas LVSP was not (1%; 95% CI: 0% to 2%; P = 0.10). Hemodynamic differences during LBBP and LVSP vs BVP were more pronounced in nonischemic than ischemic patients. CONCLUSIONS: Ultra-high-frequency electrocardiography allowed the documentation of differences in LV synchrony between LBBP, LVSP, and BVP, which were not observed by measuring QRSd. LVSP provided the same LV synchrony and hemodynamic status as BVP, while LBBP was better than BVP in both.

Ultra-high-frequency ECG volumetric and negative derivative epicardial ventricular electrical activation pattern.

From precordial ECG leads, the conventional determination of the negative derivative of the QRS complex (ND-ECG) assesses epicardial activation. Recently we showed that ultra-high-frequency electrocardiography (UHF-ECG) determines the activation of a larger volume of the ventricular wall. We aimed to combine these two methods to investigate the potential of volumetric and epicardial ventricular activation assessment and thereby determine the transmural activation sequence. We retrospectively analyzed 390 ECG records divided into three groups-healthy subjects with normal ECG, left bundle branch block (LBBB), and right bundle branch block (RBBB) patients. Then we created UHF-ECG and ND-ECG-derived depolarization maps and computed interventricular electrical dyssynchrony. Characteristic spatio-temporal differences were found between the volumetric UHF-ECG activation patterns and epicardial ND-ECG in the Normal, LBBB, and RBBB groups, despite the overall high correlations between both methods. Interventricular electrical dyssynchrony values assessed by the ND-ECG were consistently larger than values computed by the UHF-ECG method. Noninvasively obtained UHF-ECG and ND-ECG analyses describe different ventricular dyssynchrony and the general course of ventricular depolarization. Combining both methods based on standard 12-lead ECG electrode positions allows for a more detailed analysis of volumetric and epicardial ventricular electrical activation, including the assessment of the depolarization wave direction propagation in ventricles.

Left bundle branch area pacing results in more physiological ventricular activation than biventricular pacing in patients with left bundle branch block heart failure.

Biventricular pacing (Biv) and left bundle branch area pacing (LBBAP) are methods of cardiac resynchronization therapy (CRT). Currently, little is known about how they differ in terms of ventricular activation. This study compared ventricular activation patterns in left bundle branch block (LBBB) heart failure patients using an ultra-high-frequency electrocardiography (UHF-ECG). This was a retrospective analysis including 80 CRT patients from two centres. UHF-ECG data were obtained during LBBB, LBBAP, and Biv. Left bundle branch area pacing patients were divided into non-selective left bundle branch pacing (NSLBBP) or left ventricular septal pacing (LVSP) and into groups with V6 R-wave peak times (V6RWPT) < 90 ms and ≥ 90 ms. Calculated parameters were: e-DYS (time difference between the first and last activation in V1-V8 leads) and Vdmean (average of V1-V8 local depolarization durations). In LBBB patients (n = 80) indicated for CRT, spontaneous rhythms were compared with Biv (39) and LBBAP rhythms (64). Although both Biv and LBBAP significantly reduced QRS duration (QRSd) compared with LBBB (from 172 to 148 and 152 ms, respectively, both P < 0.001), the difference between them was not significant (P = 0.2). Left bundle branch area pacing led to shorter e-DYS (24 ms) than Biv (33 ms; P = 0.008) and shorter Vdmean (53 vs. 59 ms; P = 0.003). No differences in QRSd, e-DYS, or Vdmean were found between NSLBBP, LVSP, and LBBAP with paced V6RWPTs < 90 and ≥ 90 ms. Both Biv CRT and LBBAP significantly reduce ventricular dyssynchrony in CRT patients with LBBB. Left bundle branch area pacing is associated with more physiological ventricular activation.

Bipolar anodal septal pacing with direct LBB capture preserves physiological ventricular activation better than unipolar left bundle branch pacing.

Background: Left bundle branch pacing (LBBP) produces delayed, unphysiological activation of the right ventricle. Using ultra-high-frequency electrocardiography (UHF-ECG), we explored how bipolar anodal septal pacing with direct LBB capture (aLBBP) affects the resultant ventricular depolarization pattern. Methods: In patients with bradycardia, His bundle pacing (HBP), unipolar nonselective LBBP (nsLBBP), aLBBP, and right ventricular septal pacing (RVSP) were performed. Timing of local ventricular activation, in leads V1-V8, was displayed using UHF-ECG, and electrical dyssynchrony (e-DYS) was calculated as the difference between the first and last activation. Durations of local depolarizations were determined as the width of the UHF-QRS complex at 50% of its amplitude. Results: aLBBP was feasible in 63 of 75 consecutive patients with successful nsLBBP. aLBBP significantly improved ventricular dyssynchrony (mean -9 ms; 95% CI (-12;-6) vs. -24 ms (-27;-21), ), p < 0.001) and shortened local depolarization durations in V1-V4 (mean differences -7 ms to -5 ms (-11;-1), p < 0.05) compared to nsLBBP. aLBBP resulted in e-DYS -9 ms (-12; -6) vs. e-DYS 10 ms (7;14), p < 0.001 during HBP. Local depolarization durations in V1-V2 during aLBBP were longer than HBP (differences 5-9 ms (1;14), p < 0.05, with local depolarization duration in V1 during aLBBP being the same as during RVSP (difference 2 ms (-2;6), p = 0.52). Conclusion: Although aLBBP improved ventricular synchrony and depolarization duration of the septum and RV compared to unipolar nsLBBP, the resultant ventricular depolarization was still less physiological than during HBP.

A new database with annotations of P waves in ECGs with various types of arrhythmias.

Objective.The aim of this study is to create a database for the development, evaluation and objective comparison of algorithms for P wave detection in ECG signals.BrnoUniversity ofTechnology ECG SignalDatabase with Annotations ofP-Wave (BUT PDB) is an ECG signal database with marked peaks of P waves annotated by ECG experts. Currently, there are only a few databases of pathological ECG signals with P-wave annotations, and some are incorrect.Approach.The pathological ECG signals used in this work were selected from three existing databases of ECG signals: MIT-BIH Arrhythmia Database, MIT-BIH Supraventricular Arrhythmia Database and Long Term AF Database. The P-wave positions were manually annotated by two ECG experts in all selected signals.Main results.The final BUT PDB composed of selected signals consists of 50 two-minute, two-lead pathological ECG signal records with annotated P waves. Each record also contains a description of the diagnosis (pathology) present in the selected part of the record and information about positions and types of QRS complexes.Significance.The BUT PDB is created for developing new, more accurate and robust methods for P wave detection. These algorithms will be used in medical practice and will help cardiologists to evaluate ECG records, establish diagnoses and save time.

Ventricular Dyssynchrony and Pacing-induced Cardiomyopathy in Patients with Pacemakers, the Utility of Ultra-high-frequency ECG and Other Dyssynchrony Assessment Tools.

The majority of patients tolerate right ventricular pacing well; however, some patients manifest signs of heart failure after pacemaker implantation and develop pacing-induced cardiomyopathy. This is a consequence of non-physiological ventricular activation bypassing the conduction system. Ventricular dyssynchrony was identified as one of the main factors responsible for pacing-induced cardiomyopathy development. Currently, methods that would allow rapid and reliable ventricular dyssynchrony assessment, ideally during the implant procedure, are lacking. Paced QRS duration is an imperfect marker of dyssynchrony, and methods based on body surface mapping, electrocardiographic imaging or echocardiography are laborious and time-consuming, and can be difficult to use during the implantation procedure. However, the ventricular activation sequence can be readily displayed from the chest leads using an ultra-high-frequency ECG. It can be performed during the implantation procedure to visualise ventricular depolarisation and resultant ventricular dyssynchrony during pacing. This information can assist the electrophysiologist in selecting a pacing location that avoids dyssynchronous ventricular activation.

QRS detection and classification in Holter ECG data in one inference step.

While various QRS detection and classification methods were developed in the past, the Holter ECG data acquired during daily activities by wearable devices represent new challenges such as increased noise and artefacts due to patient movements. Here, we present a deep-learning model to detect and classify QRS complexes in single-lead Holter ECG. We introduce a novel approach, delivering QRS detection and classification in one inference step. We used a private dataset (12,111 Holter ECG recordings, length of 30 s) for training, validation, and testing the method. Twelve public databases were used to further test method performance. We built a software tool to rapidly annotate QRS complexes in a private dataset, and we annotated 619,681 QRS complexes. The standardised and down-sampled ECG signal forms a 30-s long input for the deep-learning model. The model consists of five ResNet blocks and a gated recurrent unit layer. The model's output is a 30-s long 4-channel probability vector (no-QRS, normal QRS, premature ventricular contraction, premature atrial contraction). Output probabilities are post-processed to receive predicted QRS annotation marks. For the QRS detection task, the proposed method achieved the F1 score of 0.99 on the private test set. An overall mean F1 cross-database score through twelve external public databases was 0.96 ± 0.06. In terms of QRS classification, the presented method showed micro and macro F1 scores of 0.96 and 0.74 on the private test set, respectively. Cross-database results using four external public datasets showed micro and macro F1 scores of 0.95 ± 0.03 and 0.73 ± 0.06, respectively. Presented results showed that QRS detection and classification could be reliably computed in one inference step. The cross-database tests showed higher overall QRS detection performance than any of compared methods.

Reliable P wave detection in pathological ECG signals.

Accurate automated detection of P waves in ECG allows to provide fast correct diagnosis of various cardiac arrhythmias and select suitable strategy for patients' treatment. However, P waves detection is a still challenging task, especially in long-term ECGs with manifested cardiac pathologies. Software tools used in medical practice usually fail to detect P waves under pathological conditions. Most of recently published approaches have not been tested on such the signals at all. Here we introduce a novel method for accurate and reliable P wave detection, which is success in both normal and pathological cases. Our method uses phasor transform of ECG and innovative decision rules in order to improve P waves detection in pathological signals. The rules are based on a deep knowledge of heart manifestation during various arrhythmias, such as atrial fibrillation, premature ventricular contraction, etc. By involving the rules into the decision process, we are able to find the P wave in the correct location or, alternatively, not to search for it at all. In contrast to another studies, we use three, highly variable annotated ECG databases, which contain both normal and pathological records, to objectively validate our algorithm. The results for physiological records are Se = 98.56% and PP = 99.82% for MIT-BIH Arrhythmia Database (MITDP, with MITDB P-Wave Annotations) and Se = 99.23% and PP = 99.12% for QT database. These results are comparable with other published methods. For pathological signals, the proposed method reaches Se = 96.40% and PP = 91.56% for MITDB and Se = 93.07% and PP = 88.60% for Brno University of Technology ECG Signal Database with Annotations of P wave (BUT PDB). In these signals, the proposed detector greatly outperforms other methods and, thus, represents a huge step towards effective use of fully automated ECG analysis in a real medical practice.

Classification of ECG using ensemble of residual CNNs with or without attention mechanism.

Objective. This paper introduces a winning solution (team ISIBrno-AIMT) to the official round of PhysioNet Challenge 2021. The main goal of the challenge was a classification of ECG recordings into 26 multi-label pathological classes with a variable number of leads (e.g. 12, 6, 4, 3, 2). The main objective of this study is to verify whether the multi-head-attention mechanism influences the model performance.Approach. We introduced an ECG classification method based on the ResNet architecture with a multi-head attention mechanism for the official round of the challenge. However, empirical findings collected during model development suggested that the multi-head attention layer might not significantly impact the final classification performance. For this reason, during the follow-up round, we removed a multi-head attention layer to test the influence on model performance. Like the official round, the model is optimized using a mixture of loss functions, i.e. binary cross-entropy, custom challenge score loss function, and custom sparsity loss function. Probability thresholds for each classification class are estimated using the evolutionary optimization method. The final architecture consists of three submodels forming a majority voting classification ensemble.Main results. The modified model without the multi-head attention layer increased the overall challenge score to 0.59 compared to the 0.58 from the official round.Significance. Our findings from the follow-up submission support the fact that the multi-head attention layer in the proposed architecture does not significantly affect the classification performance.

Left Ventricular Myocardial Septal Pacing in Close Proximity to LBB Does Not Prolong the Duration of the Left Ventricular Lateral Wall Depolarization Compared to LBB Pacing.

Background: Three different ventricular capture types are observed during left bundle branch pacing (LBBp). They are selective LBB pacing (sLBBp), non-selective LBB pacing (nsLBBp), and myocardial left septal pacing transiting from nsLBBp while decreasing the pacing output (LVSP). Study aimed to compare differences in ventricular depolarization between these captures using ultra-high-frequency electrocardiography (UHF-ECG). Methods: Using decremental pacing voltage output, we identified and studied nsLBBp, sLBBp, and LVSP in patients with bradycardia. Timing of ventricular activations in precordial leads was displayed using UHF-ECGs, and electrical dyssynchrony (e-DYS) was calculated as the difference between the first and last activation. The durations of local depolarizations (Vd) were determined as the width of the UHF-QRS complex at 50% of its amplitude. Results: In 57 consecutive patients, data were collected during nsLBBp (n = 57), LVSP (n = 34), and sLBBp (n = 23). Interventricular dyssynchrony (e-DYS) was significantly lower during LVSP -16 ms (-21; -11), than nsLBBp -24 ms (-28; -20) and sLBBp -31 ms (-36; -25). LVSP had the same V1d-V8d as nsLBBp and sLBBp except for V3d, which during LVSP was shorter than sLBBp; the mean difference -9 ms (-16; -1), p = 0.01. LVSP caused less interventricular dyssynchrony and the same or better local depolarization durations than nsLBBp and sLBBp irrespective of QRS morphology during spontaneous rhythm or paced QRS axis. Conclusions: In patients with bradycardia, LVSP in close proximity to LBB resulted in better interventricular synchrony than nsLBBp and sLBBp and did not significantly prolong depolarization of the left ventricular lateral wall.

Brno University of Technology Smartphone PPG Database (BUT PPG): Annotated Dataset for PPG Quality Assessment and Heart Rate Estimation.

To the best of our knowledge, there is no annotated database of PPG signals recorded by smartphone publicly available. This article introduces Brno University of Technology Smartphone PPG Database (BUT PPG) which is an original database created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology, for the purpose of evaluating photoplethysmographic (PPG) signal quality and estimation of heart rate (HR). The data comprises 48 10-second recordings of PPGs and associated electrocardiographic (ECG) signals used for determination of reference HR. The data were collected from 12 subjects (6 female, 6 male) aged between 21 and 61. PPG data were collected by smartphone Xiaomi Mi9 with sampling frequency of 30 Hz. Reference ECG signals were recorded using a mobile ECG recorder (Bittium Faros 360) with a sampling frequency of 1,000 Hz. Each PPG signal includes annotation of quality created manually by biomedical experts and reference HR. PPG signal quality is indicated binary: 1 indicates good quality for HR estimation, 0 indicates signals where HR cannot be detected reliably, and thus, these signals are unsuitable for further analysis. As the only available database containing PPG signals recorded by smartphone, BUT PPG is a unique tool for the development of smart, user-friendly, cheap, on-the-spot, self-home-monitoring of heart rate with the potential of widespread using.

Di-4-ANEPPS Modulates Electrical Activity and Progress of Myocardial Ischemia in Rabbit Isolated Heart.

AIMS: Although voltage-sensitive dye di-4-ANEPPS is a common tool for mapping cardiac electrical activity, reported effects on electrophysiological parameters are rather. The main goals of the study were to reveal effects of the dye on rabbit isolated heart and to verify, whether rabbit isolated heart stained with di-4-ANEPPS is a suitable tool for myocardial ischemia investigation. METHODS AND RESULTS: Study involved experiments on stained (n = 9) and non-stained (n = 11) Langendorff perfused rabbit isolated hearts. Electrophysiological effects of the dye were evaluated by analysis of various electrogram (EG) parameters using common paired and unpaired statistical tests. It was shown that staining the hearts with di-4-ANEPPS leads to only short-term sporadic prolongation of impulse conduction through atria and atrioventricular node. On the other hand, significant irreversible slowing of heart rate and ventricular conduction were found in stained hearts as compared to controls. In patch clamp experiments, significant inhibition of sodium current density was observed in differentiated NG108-15 cells stained by the dye. Although no significant differences in mean number of ventricular premature beats were found between the stained and the non-stained hearts in ischemia as well as in reperfusion, all abovementioned results indicate increased arrhythmogenicity. In isolated hearts during ischemia, prominent ischemic patterns appeared in the stained hearts with 3-4 min delay as compared to the non-stained ones. Moreover, the ischemic changes did not achieve the same magnitude as in controls even after 10 min of ischemia. It resulted in poor performance of ischemia detection by proposed EG parameters, as was quantified by receiver operating characteristics analysis. CONCLUSION: Our results demonstrate significant direct irreversible effect of di-4-ANEPPS on spontaneous heart rate and ventricular impulse conduction in rabbit isolated heart model. Particularly, this should be considered when di-4-ANEPPS is used in ischemia studies in rabbit. Delayed attenuated response of such hearts to ischemia might lead to misinterpretation of obtained results.

Pathologies affect the performance of ECG signals compression.

The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of compression algorithms. This study evaluates whether the pathologies present in ECG signals affect the efficiency and quality of compression. Single-cycle fractal-based compression algorithm and compression algorithm based on combination of wavelet transform and set partitioning in hierarchical trees are used to compress 125 15-leads ECG signals from CSE database. Rhythm and morphology of these signals are newly annotated as physiological or pathological. The compression performance results are statistically evaluated. Using both compression algorithms, physiological signals are compressed with better quality than pathological signals according to 8 and 9 out of 12 quality metrics, respectively. Moreover, it was statistically proven that pathological signals were compressed with lower efficiency than physiological signals. Signals with physiological rhythm and physiological morphology were compressed with the best quality. The worst results reported the group of signals with pathological rhythm and pathological morphology. This study is the first one which deals with effects of ECG pathologies on the performance of compression algorithms. Signal-by-signal rhythm and morphology annotations (physiological/pathological) for the CSE database are newly published.

Left bundle branch pacing compared to left ventricular septal myocardial pacing increases interventricular dyssynchrony but accelerates left ventricular lateral wall depolarization.

BACKGROUND: Nonselective His-bundle pacing (nsHBp), nonselective left bundle branch pacing (nsLBBp), and left ventricular septal myocardial pacing (LVSP) are recognized as physiological pacing techniques. OBJECTIVE: The purpose of this study was to compare differences in ventricular depolarization between these techniques using ultra-high-frequency electrocardiography (UHF-ECG). METHODS: In patients with bradycardia, nsHBp, nsLBBp (confirmed concomitant left bundle branch [LBB] and myocardial capture), and LVSP (pacing in left ventricular [LV] septal position without proven LBB capture) were performed. Timings of ventricular activations in precordial leads were displayed using UHF-ECG, and electrical dyssynchrony (e-DYS) was calculated as the difference between the first and last activation. Duration of local depolarization (Vd) was determined as width of the UHF-QRS complex at 50% of its amplitude. RESULTS: In 68 patients, data were collected during nsLBBp (35), LVSP (96), and nsHBp (55). nsLBBp resulted in larger e-DYS than did LVSP and nsHBp [- 24 ms (-28;-19) vs -12 ms (-16;-9) vs 10 ms (7;14), respectively; P <.001]. nsLBBp produced similar values of Vd in leads V5-V8 (36-43 ms vs 38-43 ms; P = NS in all leads) but longer Vd in leads V1-V4 (47-59 ms vs 41-44 ms; P <.05) as nsHBp. LVSP caused prolonged Vd in leads V1-V8 compared to nsHBp and longer Vd in leads V5-V8 compared to nsLBBp (44-51 ms vs 36-43 ms; P <.05) regardless of R-wave peak time in lead V5 or QRS morphology in lead V1 present during LVSP. CONCLUSION: nslbbp preserves physiological LV depolarization but increases interventricular electrical dyssynchrony. LV lateral wall depolarization during LVSP is prolonged, but interventricular synchrony is preserved.

Ventricular activation pattern assessment during right ventricular pacing: Ultra-high-frequency ECG study.

BACKGROUND: Right ventricular (RV) pacing causes delayed activation of remote ventricular segments. We used the ultra-high-frequency ECG (UHF-ECG) to describe ventricular depolarization when pacing different RV locations. METHODS: In 51 patients, temporary pacing was performed at the RV septum (mSp); further subclassified as right ventricular inflow tract (RVIT) and right ventricular outflow tract (RVOT) for septal inflow and outflow positions (below or above the plane of His bundle in right anterior oblique), apex, anterior lateral wall, and at the basal RV septum with nonselective His bundle or RBB capture (nsHBorRBBp). The timings of UHF-ECG electrical activations were quantified as left ventricular lateral wall delay (LVLWd; V8 activation delay) and RV lateral wall delay (RVLWd; V1 activation delay). RESULTS: The LVLWd was shortest for nsHBorRBBp (11 ms [95% confidence interval = 5-17]), followed by the RVIT (19 ms [11-26]) and the RVOT (33 ms [27-40]; p < .01 between all of them), although the QRSd for the latter two were the same (153 ms (148-158) vs. 153 ms (148-158); p = .99). RV apical capture not only had a longer LVLWd (34 ms (26-43) compared to mSp (27 ms (20-34), p < .05), but its RVLWd (17 ms (9-25) was also the longest compared to other RV pacing sites (mean values for nsHBorRBBp, mSp, anterior and lateral wall captures being below 6 ms), p < .001 compared to each of them. CONCLUSION: RVIT pacing produces better ventricular synchrony compared to other RV pacing locations with myocardial capture. However, UHF-ECG ventricular dysynchrony seen during RVIT pacing is increased compared to concomitant capture of basal septal myocytes and His bundle or proximal right bundle branch.

Comparing Ventricular Synchrony in Left Bundle Branch and Left Ventricular Septal Pacing in Pacemaker Patients.

BACKGROUND: Left bundle branch area pacing (LBBAP) has recently been introduced as a novel physiological pacing strategy. Within LBBAP, distinction is made between left bundle branch pacing (LBBP) and left ventricular septal pacing (LVSP, no left bundle capture). OBJECTIVE: To investigate acute electrophysiological effects of LBBP and LVSP as compared to intrinsic ventricular conduction. METHODS: Fifty patients with normal cardiac function and pacemaker indication for bradycardia underwent LBBAP. Electrocardiography (ECG) characteristics were evaluated during pacing at various depths within the septum: starting at the right ventricular (RV) side of the septum: the last position with QS morphology, the first position with r' morphology, LVSP and-in patients where left bundle branch (LBB) capture was achieved-LBBP. From the ECG's QRS duration and QRS morphology in lead V1, the stimulus- left ventricular activation time left ventricular activation time (LVAT) interval were measured. After conversion of the ECG into vectorcardiogram (VCG) (Kors conversion matrix), QRS area and QRS vector in transverse plane (Azimuth) were determined. RESULTS: QRS area significantly decreased from 82 ± 29 µVs during RV septal pacing (RVSP) to 46 ± 12 µVs during LVSP. In the subgroup where LBB capture was achieved (n = 31), QRS area significantly decreased from 46 ± 17 µVs during LVSP to 38 ± 15 µVs during LBBP, while LVAT was not significantly different between LVSP and LBBP. In patients with normal ventricular activation and narrow QRS, QRS area during LBBP was not significantly different from that during intrinsic activation (37 ± 16 vs. 35 ± 19 µVs, respectively). The Azimuth significantly changed from RVSP (-46 ± 33°) to LVSP (19 ± 16°) and LBBP (-22 ± 14°). The Azimuth during both LVSP and LBBP were not significantly different from normal ventricular activation. QRS area and LVAT correlated moderately (Spearman's R = 0.58). CONCLUSIONS: ECG and VCG indices demonstrate that both LVSP and LBBP improve ventricular dyssynchrony considerably as compared to RVSP, to values close to normal ventricular activation. LBBP seems to result in a small, but significant, improvement in ventricular synchrony as compared to LVSP.

Real-Time Quality Assessment of Long-Term ECG Signals Recorded by Wearables in Free-Living Conditions.

OBJECTIVE: Nowadays, methods for ECG quality assessment are mostly designed to binary distinguish between good/bad quality of the whole signal. Such classification is not suitable to long-term data collected by wearable devices. In this paper, a novel approach to estimate long-term ECG signal quality is proposed. METHODS: The real-time quality estimation is performed in a local time window by calculation of continuous signal-to-noise ratio (SNR) curve. The layout of the data quality segments is determined by analysis of SNR waveform. It is distinguished between three levels of ECG signal quality: signal suitable for full wave ECG analysis, signal suitable only for QRS detection, and signal unsuitable for further processing. RESULTS: The SNR limits for reliable QRS detection and full ECG waveform analysis are 5 and 18 dB respectively. The method was developed and tested using synthetic data and validated on real data from wearable device. CONCLUSION: The proposed solution is a robust, accurate and computationally efficient algorithm for annotation of ECG signal quality that will facilitate the subsequent tailored analysis of ECG signals recorded in free-living conditions. SIGNIFICANCE: The field of long-term ECG signals self-monitoring by wearable devices is swiftly developing. The analysis of massive amount of collected data is time consuming. It is advantageous to characterize data quality in advance and thereby limit consequent analysis to useable signals.

Fully automated QRS area measurement for predicting response to cardiac resynchronization therapy.

BACKGROUND: Cardiac resynchronization therapy (CRT) is an established treatment in patients with heart failure and conduction abnormalities. However, a significant number of patients do not respond to CRT. Currently employed criteria for selection of patients for this therapy (QRS duration and morphology) have several shortcomings. QRS area was recently shown to provide superior association with CRT response. However, its assessment was not fully automated and required the presence of an expert. OBJECTIVE: Our objective was to develop a fully automated method for the assessment of vector-cardiographic (VCG) QRS area from electrocardiographic (ECG) signals. METHODS: Pre-implantation ECG recordings (N = 864, 695 left-bundle-branch block, 589 men) in PDF files were converted to allow signal processing. QRS complexes were found and clustered into morphological groups. Signals were converted from 12­lead ECG to 3­lead VCG and an average QRS complex was built. QRS area was computed from individual areas in the X, Y and Z leads. Practical usability was evaluated using Kaplan-Meier plots and 5-year follow-up data. RESULTS: The automatically calculated QRS area values were 123 ±â€¯48 µV.s (mean values and SD), while the manually determined QRS area values were 116 ±â€¯51 ms; the correlation coefficient between the two was r = 0.97. The automated and manual methods showed the same ability to stratify the population (hazard ratios 2.09 vs 2.03, respectively). CONCLUSION: The presented approach allows the fully automatic and objective assessment of QRS area values. SIGNIFICANCE: Until this study, assessing QRS area values required an expert, which means both additional costs and a risk of subjectivity. The presented approach eliminates these disadvantages and is publicly available as part of free signal-processing software.

Both selective and nonselective His bundle, but not myocardial, pacing preserve ventricular electrical synchrony assessed by ultra-high-frequency ECG.

BACKGROUND: Right ventricular myocardial pacing leads to nonphysiological activation of heart ventricles. Contrary to this, His bundle pacing preserves their fast activation. Ultra-high-frequency electrocardiography (UHF-ECG) is a novel tool for ventricular depolarization assessment. OBJECTIVE: The purpose of this study was to describe UHF-ECG depolarization patterns during myocardial and His bundle pacing. METHODS: Forty-six patients undergoing His bundle pacing to treat bradycardia and spontaneous QRS complexes without bundle branch block were included. UHF-ECG recordings were performed during spontaneous rhythm, pure myocardial para-Hisian capture, and His bundle capture. QRS duration, QRS area, depolarization time in specific leads, and the UHF-ECG-derived ventricular dyssynchrony index were calculated. RESULTS: One hundred thirty-three UHF-ECG recordings were performed in 46 patients (44 spontaneous rhythm, 28 selective His bundle, 43 nonselective His bundle, and 18 myocardial capture). The mean QRS duration was 117 ms for spontaneous rhythm, 118 ms for selective, 135 ms for nonselective, and 166 ms for myocardial capture (P < .001 for nonselective and myocardial capture compared to each of the other types of ventricular activation). The calculated dyssynchrony index was shortest during spontaneous rhythm (12 ms; P = .02 compared to selective and P = .09 compared to nonselective), and it did not differ between selective and nonselective His bundle capture (16 vs 15 ms; P > .99) and was longest during myocardial capture of the para-Hisian area (37 ms; P < .001 compared to each of the other types of ventricular activation). CONCLUSION: In patients without bundle branch block, both types of His bundle, but not myocardial, capture preserve ventricular electrical synchrony as measured using UHF-ECG.

Novel ultra-high-frequency electrocardiogram tool for the description of the ventricular depolarization pattern before and during cardiac resynchronization.

INTRODUCTION: The present study introduces a new ultra-high-frequency 14-lead electrocardiogram technique (UHF-ECG) for mapping ventricular depolarization patterns and calculation of novel dyssynchrony parameters that may improve the selection of patients and application of cardiac resynchronization therapy (CRT). METHODS: Components of the ECG in sixteen frequency bands within the 150 to 1000 Hz range were used to create ventricular depolarization maps. The maximum time difference between the UHF QRS complex centers of mass of leads V1 to V8 was defined as ventricular electrical dyssynchrony (e-DYS), and the duration at 50% of peak voltage amplitude in each lead was defined as the duration of local depolarization (Vd). Proof of principle measurements was performed in seven patients with left (left bundle branch block) and four patients with right bundle branch block (right bundle branch block) before and during CRT using biventricular and His-bundle pacing. RESULTS: The acquired activation maps reflect the activation sequence under the tested conditions. e-DYS decreased considerably more than QRS duration, during both biventricular pacing (-50% vs -8%) and His-bundle pacing (-77% vs -13%). While biventricular pacing slightly increased Vd, His-bundle pacing reduced Vd significantly (+11% vs -36%), indicating the contribution of the fast conduction system. Optimization of biventricular pacing by adjusting VV-interval showed a decrease of e-DYS from 102 to 36 ms with only a small Vd increase and QRS duration decrease. CONCLUSIONS: The UHF-ECG technique provides novel information about electrical activation of the ventricles from a standard ECG electrode setup, potentially improving the selection of patients for CRT and application of CRT.