Surface Electromyography-controlled Pedestrian Collision Avoidance: A Driving Simulator Study
July 24, 2020 Β· Declared Dead Β· π IEEE Sensors Journal
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Authors
Edric John Cruz Nacpil, Zheng Wang, Zhanhong Yan, Tsutomu Kaizuka, Kimihiko Nakano
arXiv ID
2007.12328
Category
cs.HC: Human-Computer Interaction
Citations
4
Venue
IEEE Sensors Journal
Last Checked
4 months ago
Abstract
Drivers with disabilities such as hemiplegia or unilateral upper limb amputation restricting steering wheel operation to one arm could encounter the challenge of stabilizing vehicles during pedestrian collision avoidance. An sEMG-controlled steering assistance system was developed for these drivers to enable rapid steering wheel rotation with only one healthy arm. Test drivers were recruited to use the Myo armband as a sEMG-based interface to perform pedestrian collision avoidance in a driving simulator. It was hypothesized that the sEMG-based interface would be comparable or superior in vehicle stability to manual takeover from automated driving and conventional steering wheel operation. The Myo armband interface was significantly superior to manual takeover from automated driving and comparable to manual steering wheel operation. The results of the driving simulator trials confirm the feasibility of the sEMG-controlled system as a safe alternative that could benefit drivers with the aforesaid disabilities.
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