Model-Based Evaluation of Methods for Respiratory Sinus Arrhythmia Estimation

Objective: Respiratory sinus arrhythmia (RSA) refers to heart rate oscillations synchronous with respiration, and it is one of the major representations cardiorespiratory coupling. Its strength has been suggested as a biomarker monitor different conditions, diseases. Some approaches have proposed quantify RSA, but unclear which performs best in specific scenarios. The main objective this study compare seven state-of-the-art methods for RSA quantification using data generated model simulate, control RSA. These are also compared, evaluated on real-life application, their ability capture changes coupling during sleep. Methods: A simulation used create dataset variability, respiratory signals controlled estimation approaches. To objectively applications, regression models trained simulated map estimates same measurement scale. Results, conclusion: based cross entropy, time-frequency coherence, subspace projections showed performance data. In addition, these captured expected trends sleep similarly. Significance: An comparison presented guide future analyses. Also, can be existing, newly estimates. It freely accessible online.