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

Spyridon Kontaxis1, Alba Martin2, Andrius Petrenas3, Vaidotas Marozas4, Raquel Bail√≥n5, Pablo Laguna6, Leif Sornmo7
1Biomedical Research Networking Centre on Bioengineering, Biomaterials and Nanomedicine, 2Biomedical Signal Interpretation and Computational Simulation Group (BSICoS), Universidad de Zaragoza, 3Department of Electronics Engineering, Biomedical Engineering Institute, Kaunas University of Technology, 4Kaunas University of Technology, 5I3A, IIS, Universidad de Zaragoza, CIBER-BBN, 6Zaragoza University, 7Lund University


The present study addresses the problem of respira- tory 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., V4, V5, V6, exhibit the best performance due to lower f-wave amplitudes, 3. lower errors in leads with sim- ilar f-wave amplitude are due to a more pronounced respi- ratory influence, and 4. the respiratory influence is higher in V2, V3, and V4 compared to other precordial leads.