UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 1
January-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2301626


Registration ID:
520116

Page Number

g183-g187

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Title

Machine Learning Techniques for Drowsiness Detection : A Review

Abstract

Electroencephalogram (EEG) plays an important role in E-healthcare systems, especially in the mental healthcare area, where constant and unobtrusive monitoring is desirable. EEG signals can reflect activities of the human brain and represent different emotional states. Drowsiness can also be a result of your mental, emotional, or psychological state. It can come from any event or thought that makes you feel frustrated, angry, or nervous. Drowsiness has become a social issue and could become a cause of functional disability during routine work. A machine learning (ML) framework is effective for electroencephalogram (EEG) signal analysis. This paper review of machine learning method for drowsiness detection using EEG signals.

Key Words

EEG, Emotion, Drowsiness, Drowsiness , Machine Learning, E-healthcare

Cite This Article

"Machine Learning Techniques for Drowsiness Detection : A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 1, page no.g183-g187, January-2023, Available :http://www.jetir.org/papers/JETIR2301626.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Machine Learning Techniques for Drowsiness Detection : A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 1, page no. ppg183-g187, January-2023, Available at : http://www.jetir.org/papers/JETIR2301626.pdf

Publication Details

Published Paper ID: JETIR2301626
Registration ID: 520116
Published In: Volume 10 | Issue 1 | Year January-2023
DOI (Digital Object Identifier):
Page No: g183-g187
Country: Bhopal, MP, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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