Wavelet transform-based mode decomposition for EEG signals under general anesthesia.

ABSTRACT:

Background

Mode decomposition methods are used to extract the characteristic intrinsic mode function (IMF) from various multidimensional time series signals. We analyzed an electroencephalogram (EEG) dataset for sevoflurane anesthesia using two wavelet transform-based mode decomposition methods, comprising the empirical wavelet transform (EWT) and wavelet mode decomposition (WMD) methods, and compared the results with those from the previously reported variational mode decomposition (VMD) method.

Methods

To acquire the EEG data, we used the software application EEG Analyzer, which enabled the recording of raw EEG signals via the serial interface of a bispectral index (BIS) monitor. We also created EEG mode decomposition software to perform empirical mode decomposition

SUBMITTER: Yamochi S 

PROVIDER: S-EPMC11572389 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature