Optimal Feature Search for Vigilance Estimation Using Deep Reinforcement Learning

Optimal Feature Search for Vigilance Estimation Using Deep Reinforcement Learning

A low level of vigilance is one of the main reasons for traffic and industrial accidents. We conducted experiments to evoke the low level of vigilance and record physiological data through single-channel electroencephalogram (EEG) and electrocardiogram (ECG) measurements. In this study, a deep Q-net...

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Bibliographic Details
Main Authors: Woojoon Seok, Minsoo Yeo, Jiwoo You, Heejun Lee, Taeheum Cho, Bosun Hwang, Cheolsoo Park
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Electronics
Subjects:
feature extraction
deep q-network
electrocardiogram
electroencephalogram
optimal feature selection
vigilance estimation
Online Access:https://www.mdpi.com/2079-9292/9/1/142

Internet

https://www.mdpi.com/2079-9292/9/1/142

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