A smart drive monitoring system with the driver's musculo-skeletal model for a motorized mobility scooter to assess and assist safety driving

2021 Fiscal Year Final Research Report

• Project/Area Number: 19H04507
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Review Section: Basic Section 90150:Medical assistive technology-related
• Research Institution: National Rehabilitation Center for Persons with Disabilities
• Principal Investigator: Suzurikawa Jun 国立障害者リハビリテーションセンター(研究所), 研究所 福祉機器開発部, 研究室長 (50571577)
• Co-Investigator(Kenkyū-buntansha): 長谷 和徳 東京都立大学, システムデザイン研究科, 教授 (10357775) ; 近藤 知子 杏林大学, 保健学部, 教授 (90274084)
• Project Period (FY): 2019-04-01 – 2022-03-31
• Keywords: 電動車椅子 / 技能評価 / ライフログ / 慣性センサ / 移動支援機器

Outline of Final Research Achievements

This study aimed to develop a smart drive monitoring system for a motorized mobility scooter (MMS) to assess and assist safety driving. To achieve this objective, we proposed and developed a simulation model that can estimate the burden of driving MMS and an estimation method of the angles of the steering wheel and throttle lever of MMS. The coupled analysis of the musculo-skeletal model of the upper body and the mechanical model of the MMS structure successfully estimated the joint torques in the shoulder and elbow. The estimated torque values were experimentally proven to be associated with the integrated electromyographic signals recorded at the relating muscles in the upper limbs. For quantification of MMS operation during driving, we proposed a novel estimation method of the interface operating angles of MMS using inertial measurement units. The evaluation experiments of the proposed method confirmed its practicable accuracy and robustness against the terrain inclination.

Free Research Field

福祉工学

Academic Significance and Societal Importance of the Research Achievements

近年，シニアカーは高齢者の自動車運転免許返納後の近距離移動支援手段として注目されている．一方で，法的には歩行者の扱いとなり，操作訓練や技能習得に関する規則が存在しないため，安全走行のための技術的な支援策が求められている．本研究で提案した操作負担シミュレーションモデルや操作状態推定手法は，このような安全促進に資する基盤的技術として，シニアカー利用現場で活用できる．特に，ユーザの操作行動を定量化できれば，客観的な技能評価指標として，従来の技能評価・訓練介入手法を大きく改善できる可能性がある．