Complexity analysis of EEG signals
Resource
Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE
Journal
Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE
Pages
-
Date Issued
1996-11
Date
1996-11
Author(s)
Lin, Yue-Der
Sung, Shing-Ming
Chong, Fok-Ching
Kuo, Te-Son
Liu, Chi-Hung
DOI
N/A
Abstract
Electroencephalogram (EEG) is known to be a complex time series signal and also is important in clinical neurophysiology. Here the technique of easily calculable measure of complexity C was applied to the analysis of EEG signals. Sixteen-channel EEG signals of 20 normal and 20 apoplectic subjects between 55 and 78 years of age were measured monopolarly according to the international ten-twenty system with the ipsilateral ear (A1 or A2) as the reference. The results show that the C values for the normal population are significantly higher than those of the apoplectic population at 0.01 confidence level for all channels and the authors propose that complexity C could help determine if EEG is normal or abnormal.
Type
journal article
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