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Estimating Depth of Anesthesia with Sparsity Measure of EEG Data in Wavelet Domain

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3 Author(s)
Duan Li ; Inst. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao, China ; Zhenhu Liang ; Xiaoli Li

Monitoring the effect of anesthetic drug on the central nervous system is challenging in the surgery. Several methods based on the electroencephalogram (EEG) have been proposed to estimate the depth of anesthesia (DOA). In this paper, a novel method is proposed to estimate the DOA with the sparsity measure of EEG data. The performance of the new DOA measure is assessed by pharmacokinetic/pharmacodynamic (PKPD) modeling and prediction probability analysis. The test of 17 cases shows this measure may efficiently track the effect of the sevoflurane on the brain activity.

Published in:

2009 2nd International Conference on Biomedical Engineering and Informatics

Date of Conference:

17-19 Oct. 2009