Mathematical model for the prediction of driver's health condition

2021 Fiscal Year Final Research Report

• Project/Area Number: 18H01392
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Review Section: Basic Section 20010:Mechanics and mechatronics-related
• Research Institution: Waseda University
• Principal Investigator: KANEKO SHIGEHIKO 早稲田大学, 理工学術院, 教授(任期付) (70143378)
• Project Period (FY): 2018-04-01 – 2021-03-31
• Keywords: モデル化 / 自動車 / 交通事故 / 居眠り運転 / 体調モニタリング / 生体信号処理 / 温熱環境 / 非侵襲計測

Outline of Final Research Achievements

In this study, we integrated a model of the pumping flow from the heart and a model of the vascular system into a model that reproduces the effect of the activity state of the autonomic nerves on the heart system and a model of peripheral blood vessels, and combined them with a physiological and thermodynamic model. We proposed a model that can evaluate the correlation between changes in the thermal environment and changes in the autonomic nervous index by combining a thermoregulatory model of the human body based on the principle. In the experiment, we prototyped an experimental environment in which the heartbeat interval of the subject was acquired while changing the room temperature in a short time in a booth simulating the vehicle interior environment, and the change in the autonomic nervous index could be evaluated. An experiment was conducted to verify the validity of the proposed model.

Free Research Field

機械力学・計測制御

Academic Significance and Societal Importance of the Research Achievements

漫然運転や健康起因事故による交通事故が増加している昨今，ドライバーの居眠り及び体調急変の予測は国民的喫緊の課題である．最近，生体信号や画像による眠気の検知や覚醒状態維持が可能な眠気制御装置が発表されているが，その原理は明らかにされてはいない．また，運転者に体調急変が発生した際のデータは狙って取得できるものではないため，解析に用いるに十分なデータ数が確保できず，信頼性のある推定手法を構築することは難しい．そこで，数理モデルにもとづくシミュレータによって，信頼に足りるデータを提供することが求められている．以上を踏まえ，本研究ではドライバーの体調予測に資する数理モデルの構築を行った．