Drowsiness Estimation Model Based on Hemodynamics

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2020/03/01

タイトル(英語): Drowsiness Estimation Model Based on Hemodynamics

著者名: Ayaka Masaki (College of Science and Engineering, Aoyama Gakuin University), Kent Nagumo (College of Science and Engineering, Aoyama Gakuin University), Kosuke Oiwa (College of Science and Engineering, Aoyama Gakuin University), Akio Nozawa (College of Sc

著者名(英語): Ayaka Masaki (College of Science and Engineering, Aoyama Gakuin University), Kent Nagumo (College of Science and Engineering, Aoyama Gakuin University), Kosuke Oiwa (College of Science and Engineering, Aoyama Gakuin University), Akio Nozawa (College of Science and Engineering, Aoyama Gakuin University)

キーワード: convolutional neural network，deep learning，drowsiness detection，hemodynamics

要約(英語): A large number of traffic fatalities are caused by falling asleep at the wheel. Several drowsiness detection technologies have been developed in recent years. A previous study describes how hemodynamics can vary significantly due to drowsiness. However, it was difficult to estimate drowsiness from the time series of hemodynamics. In this study, general models for estimating three drowsiness levels (i.e., high, medium, and low) based on hemodynamics were constructed using a convolutional neural network for detecting the condition before a state of complete sleepiness is reached, the goal being traffic accident prevention. The results showed that the accuracy of the model was 68.9%.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.140 No.3 （2020） 特集Ⅰ：スマートシステムと計測・制御技術―IoT時代の計測・制御技術―　特集Ⅱ：産業応用をにらんだ高周波システム・電子デバイス・回路・材料技術

本誌掲載ページ: 409-410 p

原稿種別: 研究開発レター／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/140/3/140_409/_article/-char/ja/