@inproceedings{a4f242ca606c4a30b7f1f55d283fe662,
title = "Driver drowsiness detection via PPG biosignals by using multimodal head support",
abstract = "Drowsy driving can lead to accidents. Therefore, finding methods by which drowsy driving can be prevented is essential. This paper proposes a method of detecting drowsy driving that utilizes the Low Frequency (LF), High Frequency (HF), and LF/HF values of photoplethysmography (PPG) signals measured on fingers and earlobes. In experiments conducted, of 20 subjects, drowsiness was identified in 14 through PPG signals from their fingers. Further, of those 14 drowsy drivers, PPG signals from the earlobes of eight were also used to determine whether they were drowsy while driving.",
keywords = "Biosignals, Drowsy driving, Electrocardiogram (ECG), Photoplethysmography (PPG)",
author = "Sukgyu Koh and Cho, {Bo Ram} and Lee, {Jong Il} and Kwon, {Soon O.} and Suwoong Lee and Lim, {Joon Beom} and Lee, {Soo Beom} and Kweon, {Hyeok Dong}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017 ; Conference date: 05-04-2017 Through 07-04-2017",
year = "2017",
month = nov,
day = "8",
doi = "10.1109/CoDIT.2017.8102622",
language = "English",
series = "2017 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "383--388",
booktitle = "2017 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017",
address = "United States",
}