CPS: Medium: Integrated control of biological and mechanical power for standing balance and gait stability after paralysis
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This project addresses how cyber physical walking systems (CPWS) can be designed to be safe, secure, and resilient despite a variety of unanticipated disturbances and how real-time dynamic control and behavior adaptation can be achieved in a diversity of environments. Specifically, a CPWS will be developed that seamlessly integrates: (1) a person who has a spinal cord injury (SCI) with intact and excitable lower motor nerves; (2) an exoskeleton with controllably locked/unlocked and/or passively damped joints; (3) DC motors for need-dependent joint power assistance; and (4) computational algorithms that continuously and automatically learn to improve standing and walking stability. In this “muscles first” approach, functional neural stimulation (FNS) provides most of the joint torques for walking and for maximum health benefits and, thus, as-needed assistive joint motors may be small and lightweight. The specific aims are 1) Assist the user’s muscles on an as-needed basis and for high- bandwidth stability control by adding small, low passive-resistance motor/transmission pairs to our CPWS; 2) Develop computational algorithms for system estimation, machine learning and stability control for SCI users standing and walking with a CPWS while minimizing upper extremity effort; 3) Verify system performance with able-bodied individuals and assess upper extremity reduction and balance control in individuals with SCI using the CPWS for standing and ambulation.
Submitted by Roger Quinn
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This project addresses how cyber physical walking systems (CPWS) can be designed to be safe, secure, and resilient despite a variety of unanticipated disturbances and how real-time dynamic control and behavior adaptation can be achieved in a diversity of environments. Specifically, a CPWS will be developed that seamlessly integrates: (1) a person who has a spinal cord injury (SCI) with intact and excitable lower motor nerves; (2) an exoskeleton with controllably locked/unlocked and/or passively damped joints; (3) DC motors for need-dependent joint power assistance; and (4) computational algorithms that continuously and automatically learn to improve standing and walking stability. In this “muscles first” approach, functional neural stimulation (FNS) provides most of the joint torques for walking and for maximum health benefits and, thus, as-needed assistive joint motors may be small and lightweight. The specific aims are 1) Assist the user’s muscles on an as-needed basis and for high- bandwidth stability control by adding small, low passive-resistance motor/transmission pairs to our CPWS; 2) Develop computational algorithms for system estimation, machine learning and stability control for SCI users standing and walking with a CPWS while minimizing upper extremity effort; 3) Verify system performance with able-bodied individuals and assess upper extremity reduction and balance control in individuals with SCI using the CPWS for standing and ambulation.