Paper Info
Title
Detection of Neonatal Amplitude-Integrated EEG Based on Revised D-S Theory
Abstract
Amplitude-integrated electroencephalography (aEEG) has been widely used in continuous monitoring of neonatal brain function. This paper proposes an aEEG recognition method based on revised D-S Theory. The revised D-S Theory improves traditional D-S theory by introducing weight factor into the algorithm. Combining judgments with different weights can attenuate the conflict among them and get a more sound one. The efficiency of the proposed method is validated by classifying 103 aEEG recordings into normal and abnormal groups. Approximate entropy (ApEn) and amplitudes are used as the features to characterize aEEG signals. Compared with the traditional D-S theory, the classification accuracy of the revised method increases by 4.88%. This method could be helpful in monitoring newborn brain function.
Year
DOI
Venue
2012
10.1109/CIT.2012.123
CIT
Keywords
Field
DocType
neonatal amplitude-integrated eeg detection,d-s theory,revised d-s theory,paediatrics,aeeg recording classification,medical signal detection,aeeg signal characterization,electroencephalography,amplitude-integrated eeg,patient monitoring,traditional d-s theory,weight factor,aeeg recording,medical signal processing,newborn brain function monitoring,newborn brain function,aeeg recognition method,neonatal brain function,signal classification,aeeg signal,approximate entropy,amplitude-integrated electroencephalography,continuous monitoring,conflict attenuation,revised method increase
Approximate entropy,Weight factor,Remote patient monitoring,Computer science,Speech recognition,Continuous monitoring,Signal classification,Amplitude,Electroencephalography
Conference
ISBN
Citations 
PageRank 
978-1-4673-4873-7
0
0.34
References 
Authors
5
5
Name
Order
Citations
PageRank
Su Yang111014.58
Weiting Chen202.03
Yang Liu3491116.11
Lei Li42424.54
Zhizhong Wang510911.91