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

Weaning is the process of withdrawing mechanical ventilation at the Intensive Care Units. The problem is that around 20% of weaned patients were not actually ready for discontinuation. Studies suggest that vagal dysfunction is lower in patients successfully weaned. Therefore, the Baroreflex Sensitivity (BRS) and Heart Rate Variability (HRV) are estimated to see if they can provide additional information to improve the prediction of weaning outcomes. 9 successfully weaned patients (S-group) and 6 unsuccessfully weaned (F-group) were monitored in the last hour prior to the Spontaneous Breathing Trial. The BRS is estimated through spectral analysis, to obtain the α parameter in the low and high frequency bands, and through the capacity, C, estimated by the Bivariate Phase Rectified Signal Average (BPRSA) method. The current clinic parameters of weaning readiness do not show statistical differences. However, the capacity to changes of the BRS, C, estimated via BPRSA, exhibits significant differences between the two groups. Negative values of C, and with higher absolute values, were obtained for the S-group. Temporal indices of HRV also show differences, but not significant. These results suggest that BRS should be further explored for predicting weaning outcomes.