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