Multi-Frequency Entropy for Quantifying Complex Dynamics and Its Application on EEG Data.

ABSTRACT: Multivariate entropy algorithms have proven effective in the complexity dynamic analysis of electroencephalography (EEG) signals, with researchers commonly configuring the variables as multi-channel time series. However, the complex quantification of brain dynamics from a multi-frequency perspective has not been extensively explored, despite existing evidence suggesting interactions among brain rhythms at different frequencies. In this study, we proposed a novel algorithm, termed multi-frequency entropy (mFreEn), enhancing the capabilities of existing multivariate entropy algorithms and facilitating the complexity study of interactions among brain rhythms of different frequency bands. Firstly, utilizing simulated data, we evaluated the mFreEn's sensitivity to various noise signals, frequen

SUBMITTER: Niu Y 

PROVIDER: S-EPMC11431093 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature