Investigating Respiratory Rate Estimation during Paroxysmal Atrial Fibrillation Using an Improved ECG Simulation Model

Kontaxis, Spyridon; Martin-Yebra, Alba; Petrenas, Andrius; Marozas, Vaidotas, et al. (2020). Investigating Respiratory Rate Estimation during Paroxysmal Atrial Fibrillation Using an Improved ECG Simulation Model 2020 Computing in Cardiology, CinC 2020, 2020-September,. 2020 Computing in Cardiology, CinC 2020. Rimini, Italy: IEEE Computer Society
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DOI:
Conference Proceeding/Paper | Published | English
Authors:
Kontaxis, Spyridon ; Martin-Yebra, Alba ; Petrenas, Andrius ; Marozas, Vaidotas , et al.
Department:
Department of Biomedical Engineering
Department of Biomedical Engineering
Abstract:

The present study addresses the problem of respiratory rate estimation from ECG-derived respiration (EDR) signals during paroxysmal atrial fibrillation (AF). Novel signal-to-noise ratios between various components of the ECG including the influence of respiration, measured by QRS ensemble variance, the amplitude of fibrillatory waves (f-waves), and the QRS amplitude are introduced to characterize EDR performance. Using an improved ECG simulation model accounting for morphological variation induced by respiration, the results show that 1. the error in estimating the respiratory rate increases as a function of the time spent in AF, 2. the leads farthest away from the atria, i.e., V_{4}, V_{5}, V_{6}, exhibit the best performance due to lower f-wave amplitudes, 3. lower errors in leads with similar f-wave amplitude are due to a more pronounced respiratory influence, and 4. the respiratory influence is higher in V_{2}, V_{3}, and V_{4} compared to other precordial leads.

ISBN:
9781728173825
ISSN:
2325-8861
LUP-ID:
e4c1f9a5-47f3-46ce-b825-6559dc9f2d24 | Link: https://lup.lub.lu.se/record/e4c1f9a5-47f3-46ce-b825-6559dc9f2d24 | Statistics

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