A Nonlinear Penalty Driven Adaptive Thresholding Algorithm for Drowsiness Detection using EEG

Drowsiness, leading to traffic and workplace accidents has been a persistent safety concern over years. Most of the electroencephalogram (EEG)-based drowsiness detection methods in literature use pre-trained classifier models. However, due to the non-stationarity of EEG signals, the patterns associa...

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Bibliographic Details

Published in:	2021 4th International Conference on Bio-Engineering for Smart Technologies (BioSMART) pp. 1 - 4
Main Authors:	Gangadharan, Sagila K., Vinod, A. P.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 08.12.2021
Subjects:	Adaptation models adaptive thresholding Brain modeling Drowsiness detection electroencephalogram Electroencephalography MUSE headband Prediction algorithms Predictive models Real-time systems Support vector machines
Online Access:	Get full text
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