DocumentCode :
333662
Title :
Approximate entropy and its preliminary application in the field of EEG and cognition
Author :
Bo, Hong ; Fusheng, Yang ; Qingyu, Tang ; Tin-cheung, Chan
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Volume :
4
fYear :
1998
fDate :
29 Oct-1 Nov 1998
Firstpage :
2091
Abstract :
Approximate Entropy (ApEn) is a newly introduced statistic that can be used to quantify the complexity (or irregularity) of a time series. A practical fast algorithm of ApEn is proposed in this article and two experimental results in the field of EEG and cognition are presented
Keywords :
computational complexity; electroencephalography; entropy; medical signal processing; neurophysiology; nonlinear estimation; time series; EEG; Laplacian processing; SVD; approximate entropy; cognition; fast algorithm; flow graph; irregularity; mental activity; moving data window; nonlinear parameters; signal complexity; space complexity; time complexity; time series; Biochemistry; Cognition; Electroencephalography; Endocrine system; Entropy; Heart rate variability; Psychology; Statistics; Stochastic processes; Symmetric matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
Conference_Location :
Hong Kong
ISSN :
1094-687X
Print_ISBN :
0-7803-5164-9
Type :
conf
DOI :
10.1109/IEMBS.1998.747019
Filename :
747019
Link To Document :
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