Hi,

I am writing my thesis in psychology on heart rate variability in a clinical context. I am familiar with time-domain and frequency-domain measures but I decided to include an non-linear analysis through entropy measures since it has been showing promising results in other publications.

I have started to understand approximate and sample entropy and I wanted to use SampEn since it is already implemented in the R package that I use (RHRV) but through recent publications I have learned that there are shortcomings of it

And there is quite a rabbithole going to multiscale entropy and its many many iterations (RMSE,CMSE,RCMSE,IMSE,MSEn,RMSE mu, RMSE sigma,...) as well as fuzzy entropy or dispersion entropy

I am very overwhelmed with all these developments and a unsure which measure would be smart to choose. The "older" indices have more literature linking them to clinical outcomes; the more modern versions claim they fix specific problems and are in general more robust

Also preferably the measure I would choose should have an implementation in R in some package because it would kind of exceed my time constraints (especially since entropy is not the focus of the thesis, just an additionall way of quantifying HRV)

Does anyone have any suggestions or experiences?

References:

Byun, S., Kim, A. Y., Jang, E. H., Kim, S., Choi, K. W., Yu, H. Y., & Jeon, H. J. (2019). Entropy analysis of heart rate variability and its application to recognize major depressive disorder: A pilot study. Technology and health care : official journal of the European Society for Engineering and Medicine, 27(S1), 407–424. https://doi.org/10.3233/THC-199037

Humeau-Heurtier, A. (2015) The Multiscale Entropy Algorithm and Its Variants: A Review. Entropy, 17, 3110-3123.
https://doi.org/10.3390/e17053110

Pham, T., Lau, Z. J., Chen, S. H. A., & Makowski, D. (2021). Heart Rate Variability in Psychology: A Review of HRV Indices and an Analysis Tutorial. Sensors (Basel, Switzerland), 21(12), 3998. https://doi.org/10.3390/s21123998