Modeling an Activation of Heart Ventricular Segments

Modeling an Activation of Heart Ventricular Segments

Paper in proceedings (conference paper)

Background: Here, we present a 2D activation model evaluating the activation of specific myocardium segments (MS). Activation times of specific MS can help to identify conduction disturbances which may result in more targeted treatment of patients. Methods: 12-lead ECG signal was measured with a 5kHz sampling frequency. A total of 10 left bundle branch block (LBBB) and 5 right bundle branch block (RBBB) recordings were analyzed. The analysis includes the following steps: 1) QRS complexes detection and morphology clustering, 2) averaging of 150-1000 Hz envelopes of QRS complexes with dominant morphology, 3) a genetic algorithm (GA) produces artificial envelopes from (initially random) timing of MS activation. The task for GA is to produce envelopes the most similar to measured; then final timing reflects real activation of MS. Results: Presented model determined activation of left ventricular (LV) segments before right ventricular (RV) segments in all RBBB patients (mean 61.4 ± 13.7 ms) and activation of RV segments before the LV segments in all LBBB patients (mean 87.8 ± 15.8 ms). Computed activation of MS corresponds to the expected activation. Conclusion: We introduced a new method determining activation times of MS; this is achieved non-invasively using only ultra-high-frequency precordial ECG signal.

Background: Here, we present a 2D activation model evaluating the activation of specific myocardium segments (MS). Activation times of specific MS can help to identify conduction disturbances which may result in more targeted treatment of patients. Methods: 12-lead ECG signal was measured with a 5kHz sampling frequency. A total of 10 left bundle branch block (LBBB) and 5 right bundle branch block (RBBB) recordings were analyzed. The analysis includes the following steps: 1) QRS complexes detection and morphology clustering, 2) averaging of 150-1000 Hz envelopes of QRS complexes with dominant morphology, 3) a genetic algorithm (GA) produces artificial envelopes from (initially random) timing of MS activation. The task for GA is to produce envelopes the most similar to measured; then final timing reflects real activation of MS. Results: Presented model determined activation of left ventricular (LV) segments before right ventricular (RV) segments in all RBBB patients (mean 61.4 ± 13.7 ms) and activation of RV segments before the LV segments in all LBBB patients (mean 87.8 ± 15.8 ms). Computed activation of MS corresponds to the expected activation. Conclusion: We introduced a new method determining activation times of MS; this is achieved non-invasively using only ultra-high-frequency precordial ECG signal.

high-frequency ECG, right bundle branch block, left bundle branch block, genetic algorithm, heart segment activation

high-frequency ECG, right bundle branch block, left bundle branch block, genetic algorithm, heart segment activation

SMÍŠEK, R.; JURÁK, P.; HALÁMEK, J.; PLEŠINGER, F.; VIŠČOR, I.; MATEJKOVÁ, M.; LEINVEBER, P.

2020

30.09.2019

Computing in Cardiology 2019

46

0276-6574

Computers in Cardiology

United States of America

1

4

4

http://www.cinc.org/archives/2019/pdf/CinC2019-177.pdf