Key result
The power-law exponent modulated multiscale entropy (pMSE) method correctly assigned higher complexity values to healthy physiologic time series compared to those from patients with atrial fibrillation or congestive heart failure.
Why the study?
Existing multiscale entropy methods misassign increased complexity to physiologic signals mixed with white noise and require visual examination of scale dependence, which is sometimes unfeasible.
The proposed pMSE method provides a more direct and accurate measure of physiologic time series complexity than traditional MSE, particularly in handling noise and distinguishing pathologic states like AF and CHF.
pMSE may refine complexity assessment in AF and HF; leaves open prospective clinical validation before practice change.
Quantifying the complexity of physiologic time series has long attracted interest from researchers. The multiscale entropy (MSE) algorithm is a prevailing method to quantify the complexity of signals in a variety of research fields. However, the MSE method assigns increased complexity to the mixed signal of a physiologic time series added with white noise, although the mixed signal should become less complex due to the broken correlation. In addition, the MSE method needs users to visually examine its scale dependence (shape) to better characterize the complexity of a physiologic process, which is sometimes not feasible. In this paper, we proposed a new method, namely the power-law exponent modulated multiscale entropy (pMSE), as a complexity measure for physiologic time series. We tested the pMSE method on simulated data and real-world physiologic interbeat interval time series and demonstrated that it could solve the above two difficulties of the MSE method. We expect that the proposed pMSE method or its future variants could serve as a useful complement to the MSE method for the complexity analysis of physiologic time series.
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Han et al. (2020) studied Congestive Heart Failure, Atrial Fibrillation (n=45). Power-law exponent modulated multiscale entropy (pMSE) vs. Multiscale entropy (MSE) was evaluated on Complexity value assignment. The power-law exponent modulated multiscale entropy (pMSE) method correctly assigned higher complexity values to healthy physiologic time series compared to those from patients with atrial fibrillation or congestive heart failure.
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