DocumentCode
1572364
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
fYear
2006
Firstpage
4127
Lastpage
4129
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/IEMBS.2005.1615371
Filename
1615371
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