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 a real-life application, 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.
|Number of pages||12|
|Journal||IEEE Transactions on Biomedical Engineering|
|Early online date||1 Oct 2020|
|Publication status||Published - Jun 2021|
- Cardiorespiratory coupling
- Computational modeling
- Heart rate variability
- Heart Rate Variability
- Respiratory Sinus Arrhythmia
- heart rate variability
- respiratory sinus arrhythmia
FingerprintDive into the research topics of 'Model-Based Evaluation of Methods for Respiratory Sinus Arrhythmia Estimation'. Together they form a unique fingerprint.
Merel M. van Gilst (Content manager) & M.B. (Beatrijs) van der Hout-van der Jagt (Content manager)
Impact: Research Topic/Theme (at group level)