IEEE Transactions on Neural Systems and Rehabilitation Engineering (Jan 2024)
Hip-Knee Motion-Lagged Coordination Mapping Enables Speed Adaptive Walking for Powered Knee Prosthesis
Abstract
The commonly used finite-state-machine (FSM) impedance control for powered prostheses deploys diverse control parameters according to different gait phases, resulting in dozens of parameter adjustments and possible gait phase misrecognition. In contrast, this study presents a straightforward, continuous, and speed-adaptive control approach based on hip-knee motion-lagged coordination mapping (MLCM). The mapping, featured by the motion lag, can effectively generate the prosthetic knee’s goal gait within a second-order polynomial. It is also verified from extensive gait analysis that the motion lag and polynomial coefficients evolve linearly with respect to walking speed and gait period, promising a simple real-time deployment for prosthesis control. Experimental validation with two non-disabled subjects and two transfemoral amputees wearing a prosthesis demonstrates the MLCM controller’s ability to reduce the hip compensatory behavior, generate biomimetic knee kinematics, stance phase time, stride length, and hip-knee motion coordination across various speeds. Furthermore, compared to the benchmark FSM impedance controller, the MLCM controller reduces the number of control parameters from 17 to 7 and avoids misrecognition during gait phase transitions.
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