Multiscale entropy analysis of biological signals: a fundamental bi-scaling law - Gao, Jianbo; Hu, Jing; Liu, Feiyan; Cao, Yinhe (Frontiers in Computational Neuroscience, 2015)
Multiscale entropy (MSE) analysis is an interesting method for analyzing biological signals. So far, however, few analytic results for MSE have been reported. This has severely limited our basic understanding of MSE. To overcome this limitation, and more importantly, to guide more fruitful applications of MSE in various areas of life sciences, we derive, for time series with long memory, a fundamental bi-scaling law, one for the scale in the phase space, the other for the block size used for smoothing. We illustrate the usefulness of the approach by examining heart rate variability (HRV) data for the purpose of distinguishing healthy subjects from patients with congestive heart failure, a life-threatening condition. 1