Force myography controlled intelligent assistive wheelchair-mounted robotic exoskeleton for arm movements
Desai, Jaydip M.
Yihun, Yimesker S.
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J. Desai, B. Schabron and Y. Yihun, "Force Myography Controlled Intelligent Assistive Wheelchair-Mounted Robotic Exoskeleton for Arm Movements," 2019 IEEE International Symposium on Measurement and Control in Robotics (ISMCR), Houston, TX, USA, 2019, pp. D2-5-1-D2-5-5
People suffering from stroke, injury, cerebral palsy, and neuromuscular diseases such as Duchenne Muscular Dystrophy often utilize power wheelchairs for mobility. Recent advancement in embedded systems allowed researchers to safely navigate a power wheelchair using joystick, voice commands, eyeball movements, myoelectric signals, tongue movements, and even human brain signals. Due to muscle weakness or disease progression, many power wheelchair users rely on whole body force to move the arm. This study aimed to design a compact and smart wheelchair-mounted robotic exoskeleton that detects human intent using force myography and ensure safety of the human arm during actuation. The designed prototype offers three degrees of freedom that allows 55° and 45° of the abduction/adduction, flexion/extension respectively at the shoulder, and 60° flexion/extension at the elbow joints. Four participants without upper limb movement disability were recruited to test the effectiveness of the proposed intelligent assistive controller in order to move each joint individually followed by water bottle pick and place task. Each participant was able to successfully perform water bottle pick and place task using force myography signals in less than 90 seconds.
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