EEG-based Automatic Detection of Drowsy State
Electrical signal generated by the brain represents not only the brain function but also the status of the whole body. This paper focuses on finding the relation between EEG signal and human drowsiness, for which we require efficient algorithms. In the drowsiness state, a decrease of vigilance is generally observed. Identification was done by giving the preprocessed signal to a trained ANN to identify correctly the sleep condition of the person under observation. Different back-propagation algorithms are used for the study and the best one chosen by using the MSE estimation. Then using this system, classification is done and the drowsy signal sample is identified from given input samples.
KeywordsEEG signal Central nervous system ERS IIR digital filters Feed-forward neural network
- 2.M.S. Amin, M.R. Azim, F.M. Hasan, Spectral Analysis of Human Sleep EEG Signal, in 2nd International Conference on Signal Processing System ICPS (2010)Google Scholar
- 6.T. Tanaka, Y. Saito, Rhythmic component extraction for multichannel EEG data analysis. ICASSP 2008, 425–428 (2008)Google Scholar