Title :
Estimating Depth of Anesthesia with Sparsity Measure of EEG Data in Wavelet Domain
Author :
Duan Li ; Liang, Zhenhu ; Xiaoli Li
Author_Institution :
Inst. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao, China
Abstract :
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.
Keywords :
drugs; electroencephalography; medical signal processing; prediction theory; probability; wavelet transforms; EEG; anesthetic drug; brain activity; central nervous system; depth of anesthesia; electroencephalogram; pharmacodynamic modeling; pharmacokinetic modeling; prediction probability analysis; sevoflurane; sparsity measure; wavelet transform; Anesthesia; Anesthetic drugs; Brain modeling; Central nervous system; Direction of arrival estimation; Electroencephalography; Monitoring; Predictive models; Surgery; Wavelet domain;
Conference_Titel :
Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4132-7
Electronic_ISBN :
978-1-4244-4134-1
DOI :
10.1109/BMEI.2009.5305340
