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Sensors, Vol. 18, Pages 4477: Portable Drowsiness Detection through Use of a Prefrontal Single-Channel Electroencephalogram
In this study, we outline the development of a drowsiness detection system that makes use of a low-priced, prefrontal single-channel EEG device and evaluate its performance in an offline analysis and a practical experiment. Firstly, for the development of the system, we compared three feature extraction methods: power spectral density (PSD), autoregressive (AR) modeling, and multiscale entropy (MSE) for detecting characteristics of an EEG. In order to efficiently select a meaningful PSD, we utilized step-wise linear discriminant analysis (SWLDA). Time-averaging and robust-scaling were used to fit the data for pattern recog...
Source: Sensors - December 18, 2018 Category: Biotechnology Authors: Mikito Ogino Yasue Mitsukura Tags: Article Source Type: research