Title :
Power and asymmetry ratio of spectral bands for mental task recognition
Author :
Palaniappan, R. ; Raveendan, P.
Author_Institution :
Fac. of Eng., Malaya Univ., Kuala Lumpur, Malaysia
Abstract :
We use the power and asymmetry ratio of spectral bands to recognise mental tasks from electroencephalogram signals using a fuzzy ARTMAP neural network. Classical spectral analysis using the Wiener-Khintchine theorem and modem parametric spectral analysis using the autoregressive method are used to obtain these features. The highest classification results of 90% for a subject recognising two mental tasks validate the method
Keywords :
ART neural nets; autoregressive processes; electroencephalography; fuzzy neural nets; medical signal processing; signal classification; spectral analysis; EEG signals; Wiener-Khintchine theorem; autoregressive method; classification; electroencephalogram signals; fuzzy ARTMAP neural network; mental task recognition; parametric spectral analysis; power asymmetry ratio; spectral bands; Biological neural networks; Electrodes; Electroencephalography; Fuzzy neural networks; Modems; Neural networks; Power engineering and energy; Signal processing algorithms; Spectral analysis; Testing;
Conference_Titel :
Signal Processing and its Applications, Sixth International, Symposium on. 2001
Conference_Location :
Kuala Lumpur
Print_ISBN :
0-7803-6703-0
DOI :
10.1109/ISSPA.2001.950258
