Driver Distraction Detection Based on EEG Feature Fusion Using Random Forest-Reference-Cited by-同舟云学术

Driver Distraction Detection Based on EEG Feature Fusion Using Random Forest

Published:2023-10-20 Issue: Volume:17 Page:104-109
ISSN:
Container-title:Proceedings of the 2023 8th International Conference on Biomedical Imaging, Signal Processing
language:
Short-container-title:

Author:

Zuo Xin¹^ORCID,Zhang Chi²^ORCID,Zhao Jian³^ORCID,Hämäläinen Timo⁴^ORCID,Cong Fengyu²^ORCID

Affiliation:

1. School of Biomedical Engineering, Dalian University of Technology, China and Faculty of Information Technology, University of Jyväskylä, Finland

2. School of Biomedical Engineering, Dalian University of Technology, China

3. School of Automotive Engineering, Dalian University of Technology, China

4. Faculty of Information Technology, University of Jyväskylä, Finland

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3634875.3634890

Reference37 articles.

1. Barb Darrow. 2016. Distracted driving is now an epidemic in the U.S. Fortune. Retrieved September 14, 2016 from http://fortune.com/2016/09/14/distracted-driving-epidemic/

2. National Highway Traffic Safety Administration. 2020. Distracted driving 2018. Retrieved April 2020 from https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812926

3. National Highway Traffic Safety Administration. 2021. Distracted driving 2019. Retrieved April 2021 from https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/813111

4. Ford Motor Company, and Tsinghua University. 2017. Research on distracted driving in China. Retrieved July 2017 from https://www.chinadaily.com.cn/business/motoring/2017-07/07/content_30026549.htm

5. Survey of Pedestrian Detection for Advanced Driver Assistance Systems

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