IEEE transactions on bio-medical engineering · 2019
FES Cycling in Stroke: Novel Closed-Loop Algorithm Accommodates Differences in Functional Impairments.
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Rouse Courtney A, Downey Ryan J, Gregory Chris M, Cousin Christian A, Duenas Victor H, Dixon Warren E
Аннотация
OBJECTIVE: The objective of this paper was to develop and test a novel control algorithm that enables stroke survivors to pedal a cycle in a desired cadence range despite varying levels of functional abilities after stroke.
METHODS: A novel algorithm was developed which automatically adjusts 1) the intensity of functional electrical stimulation (FES) delivered to the leg muscles, and 2) the current delivered to an electric motor. The algorithm automatically switches between assistive, uncontrolled, and resistive modes to accommodate for differences in functional impairment, based on the mismatch between the desired and actual cadence. Lyapunov-based methods were used to theoretically prove that the rider's cadence converges to the desired cadence range. To demonstrate the controller's real-world performance, nine chronic stroke survivors performed two cycling trials: 1) volitional effort only and 2) volitional effort accompanied by the control algorithm assisting and resisting pedaling as needed.
RESULTS: With a desired cadence range of 50-55 r/min, the developed controller resulted in an average rms cadence error of 1.90 r/min, compared to 6.16 r/min during volitional-only trials.
CONCLUSION: Using FES and an electric motor with a two-sided cadence control objective to assist and resist volitional efforts enabled stroke patients with varying strength and abilities to pedal within a desired cadence range.
SIGNIFICANCE: A protocol design that constrains volitional movements with assistance and resistance from FES and a motor shows potential for FES cycles and other rehabilitation robots during stroke rehabilitation.
METHODS: A novel algorithm was developed which automatically adjusts 1) the intensity of functional electrical stimulation (FES) delivered to the leg muscles, and 2) the current delivered to an electric motor. The algorithm automatically switches between assistive, uncontrolled, and resistive modes to accommodate for differences in functional impairment, based on the mismatch between the desired and actual cadence. Lyapunov-based methods were used to theoretically prove that the rider's cadence converges to the desired cadence range. To demonstrate the controller's real-world performance, nine chronic stroke survivors performed two cycling trials: 1) volitional effort only and 2) volitional effort accompanied by the control algorithm assisting and resisting pedaling as needed.
RESULTS: With a desired cadence range of 50-55 r/min, the developed controller resulted in an average rms cadence error of 1.90 r/min, compared to 6.16 r/min during volitional-only trials.
CONCLUSION: Using FES and an electric motor with a two-sided cadence control objective to assist and resist volitional efforts enabled stroke patients with varying strength and abilities to pedal within a desired cadence range.
SIGNIFICANCE: A protocol design that constrains volitional movements with assistance and resistance from FES and a motor shows potential for FES cycles and other rehabilitation robots during stroke rehabilitation.