Paper Info
Title
A cepstral analysis based method for quantifying the depth of anesthesia from human EEG.
Abstract
In this paper, a cepstral analysis based approach to measuring the depth of anesthesia (DoA) is presented. Cepstral analysis is a signal processing technique widely used especially for speech recognition in order to extract speech information regardless of vocal cord characteristics. The resulting index for the DoA is called index based on cepstral analysis (ICep). The Fisher criterion is engaged to evaluate the performance of indices. All analyses are based on a single-channel electroencephalogram (EEG) of 10 human subjects. To validate the proposed technique, ICep is compared with bispectral index (BIS), which is the most commonly used method to estimate the level of consciousness via EEG during general anesthesia. The results show that ICep has high correlation with BIS, and is outstanding in terms of the Fisher criterion and offers faster tracking than BIS in the transition from consciousness to unconsciousness.
Year
DOI
Venue
2013
10.1109/EMBC.2013.6610918
EMBC
Keywords
Field
DocType
consciousness to unconsciousness transition,fisher criterion,bispectral index,depth of anesthesia,human eeg,speech recognition,general anesthesia,speech information extraction,electroencephalography,medical signal processing,vocal cord characteristics,consciousness level,signal processing technique,cepstral analysis,cepstral analysis based method,single-channel electroencephalogram,icep,doa,indexes,vectors,anesthesia
Signal processing,Level of consciousness,Computer science,Depth of anesthesia,Speech recognition,Correlation,Cepstral analysis,Fisher criterion,Electroencephalography,Bispectral index
Conference
Volume
ISSN
Citations 
2013
1557-170X
0
PageRank 
References 
Authors
0.34
1
6
Name
Order
Citations
PageRank
Tae-Ho Kim101.01
Young-Gyu Yoon200.34
Jinu Uhm300.34
Dae-Woong Jeong400.34
Seung Zhoo Yoon500.68
Sang-Hyun Park600.34