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Sensors 2019, 19(6), 1308; https://doi.org/10.3390/s19061308

Design and Evaluation of a Surface Electromyography-Controlled Steering Assistance Interface

1
Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
2
School of Automotive Engineering, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian 116024, China
*
Author to whom correspondence should be addressed.
Received: 26 January 2019 / Revised: 7 March 2019 / Accepted: 12 March 2019 / Published: 15 March 2019
(This article belongs to the Special Issue Advance in Sensors and Sensing Systems for Driving and Transport)
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Abstract

Millions of drivers could experience shoulder muscle overload when rapidly rotating steering wheels and reduced steering ability at increased steering wheel angles. In order to address these issues for drivers with disability, surface electromyography (sEMG) sensors measuring biceps brachii muscle activity were incorporated into a steering assistance system for remote steering wheel rotation. The path-following accuracy of the sEMG interface with respect to a game steering wheel was evaluated through driving simulator trials. Human participants executed U-turns with differing radii of curvature. For a radius of curvature equal to the minimum vehicle turning radius of 3.6 m, the sEMG interface had significantly greater accuracy than the game steering wheel, with intertrial median lateral errors of 0.5 m and 1.2 m, respectively. For a U-turn with a radius of 7.2 m, the sEMG interface and game steering wheel were comparable in accuracy, with respective intertrial median lateral errors of 1.6 m and 1.4 m. The findings of this study could be utilized to realize accurate sEMG-controlled automobile steering for persons with disability. View Full-Text
Keywords: human-machine interface (HMI); surface electromyography (sEMG); advanced driver assistance system (ADAS); automated driving human-machine interface (HMI); surface electromyography (sEMG); advanced driver assistance system (ADAS); automated driving
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Nacpil, E.J.C.; Wang, Z.; Zheng, R.; Kaizuka, T.; Nakano, K. Design and Evaluation of a Surface Electromyography-Controlled Steering Assistance Interface. Sensors 2019, 19, 1308.

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