title: EEG signal processing in anesthesia-using wavelet-based informational tools.
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.
authors.affiliation: Coll. of Biomed. Eng. & Sci. Instrum., Zhejiang Univ., Hangzhou.
authors.forename: Zhiqian
authors.initials: Z
authors.lastname: Ye
authors.forename: Fuying
authors.initials: F
authors.lastname: Tian
authors.forename: Jianfeng
authors.initials: J
authors.lastname: Weng