Estimation of Human Sleepiness based on Intelligent Spaces and Machine Learning

2022 Fiscal Year Final Research Report

• Project/Area Number: 20H04266
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Review Section: Basic Section 61050:Intelligent robotics-related
• Research Institution: Chuo University
• Principal Investigator: HASHIMOTO Hideki 中央大学, 理工学部, 教授 (30183908)
• Co-Investigator(Kenkyū-buntansha): 田村 裕 中央大学, 理工学部, 教授 (60227288) ; 長津 裕己 岐阜工業高等専門学校, その他部局等, 准教授 (60804987)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 空間知能化 / 機械学習 / 眠気推定 / 生体情報 / 状態推定 / Wifi

Outline of Final Research Achievements

Regarding driver drowsiness that causes traffic accidents, we have developed a technology that uses electrodes embedded in the seat, a camera that captures the driver's face, and Wi-Fi (radio waves) to acquire biological information such as heartbeats without restraint and contact. We have developed a system that accurately estimates drowsiness during driving using techniques such as machine learning and deep learning. It is a spatial intelligence technology that makes the driving space itself smarter, and it not only contributes to the prevention of traffic accidents, but can also be applied to estimate the quality of sleep in daily life at home.

Free Research Field

空間知能化

Academic Significance and Societal Importance of the Research Achievements

本研究では、運転時にドライバーに負担をかけない非拘束・非接触の電極、カメラ、Wifi（電波）のセンサ技術を開発した。これらの技術はドライバーの眠気だけではなく家屋での睡眠の質の推定にも適用できるものである。さらに、機械学習・深層学習を用いることにより眠気だけでなく血圧、血中酸素濃度の推定も可能であることを示した。日常生活でわざわざ計測するという手間をかけずに健康に関するデータを簡単に取得できるので応用範囲はとても広いと思われる。