Title :
EEG signal processing in anesthesia-using wavelet-based informational tools
Author :
Ye, Zhiqian ; Tian, Fuying ; Weng, Jianfeng
Author_Institution :
Coll. of Biomed. Eng. & Sci. Instrum., Zhejiang Univ., Hangzhou
Abstract :
A new tool of wavelet entropy (WE) is applied to characterize the dynamical properties of EEGs for purpose of evaluating the depth of anesthesia (DOA). 31 cases are analysed with WE, and the result shows the WE measure for EEGs can distinguish awake and asleep state in anesthesia with a high accuracy of 95%. Compared with C(n) complexity, the WE demonstrates the same good performance, and needs shorter data length for analysis. These remind that WE is a potential quantifier of DOA
Keywords :
electroencephalography; entropy; medical signal processing; sleep; wavelet transforms; EEG signal processing; anesthesia; asleep state; awake state; wavelet entropy; wavelet-based informational tools; Anesthesia; Biomedical engineering; Biomedical signal processing; Discrete wavelet transforms; Electroencephalography; Entropy; Frequency domain analysis; Signal analysis; Signal processing; Wavelet analysis; Wavelet analysis; depth of anesthesia; electroencephalogram (EEG); wavelet entropy;
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
DOI :
10.1109/IEMBS.2005.1615371
