Driver drowsiness detection methods using EEG signals: a systematic review-Reference-Cited by-同舟云学术

Driver drowsiness detection methods using EEG signals: a systematic review

Published:2022-08-19 Issue: Volume: Page:1-13
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Hussein Raed Mohammed¹^ORCID,Miften Firas Sabar²,George Loay E.³

Affiliation:

1. Iraqi Commission for Computers and Informatics, Informatics Institute of Postgraduate Studies, Baghdad, Iraq

2. College of Education for Pure Science, University of Thi-Qar, Nasiriyah, Iraq

3. University of Information Technology & Communication, Baghdad, Iraq

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2022.2112574

Reference68 articles.

1. EEG Spectral Comparison Between Occipital and Prefrontal Cortices for Early Detection of Driver Drowsiness

2. Bajaj V, Taran S, Khare SK, Sengur A. 2020. Feature extraction method for classification of alertness and drowsiness states EEG signals. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078136824&doi=10.1016%2Fj.apacoust.2020.107224&partnerID=40&md5=b581746ac3d8c56b1744037effa3f815.

3. Regression-Based Continuous Driving Fatigue Estimation: Toward Practical Implementation

4. An Effective Hybrid Model for EEG-Based Drowsiness Detection

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