Title :
Complexity analysis of EEG signals
Author :
Lin, Yue-Der ; Sung, Shing-Ming ; Chong, Fok-Ching ; Kuo, Te-Son ; Liu, Chi-Hung
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
fDate :
31 Oct-3 Nov 1996
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
Keywords :
electroencephalography; medical signal processing; time series; 55 to 78 y; EEG signals complexity analysis; abnormal EEG; apoplectic population; clinical neurophysiology; complex time series signal; electrodiagnostics; international ten-twenty system; monopolar measurements; normal EEG; Ear; Electrodes; Electroencephalography; Hospitals; Nervous system; Neurophysiology; Nonlinear dynamical systems; Sampling methods; Signal analysis; Time measurement;
Conference_Titel :
Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE
Conference_Location :
Amsterdam
Print_ISBN :
0-7803-3811-1
DOI :
10.1109/IEMBS.1996.647566
