Hip-Knee Motion-Lagged Coordination Mapping Enables Speed Adaptive Walking for Powered Knee Prosthesis

Area of Science:

• Biomedical Engineering
• Robotics
• Biomechanics

Background:

• Traditional finite-state-machine (FSM) impedance control for powered prostheses requires numerous parameter adjustments and is prone to gait phase misrecognition.
• This complexity hinders seamless adaptation to varying walking speeds and gait dynamics.

Purpose of the Study:

• To present a novel, continuous, and speed-adaptive control strategy for powered prosthetic knees.
• To demonstrate the efficacy of hip-knee motion-lagged coordination mapping (MLCM) as a simplified alternative to FSM control.

Main Methods:

• Developed a hip-knee motion-lagged coordination mapping (MLCM) that generates prosthetic knee gait using a second-order polynomial.
• Analyzed the linear evolution of motion lag and polynomial coefficients with walking speed and gait period.
• Validated the MLCM controller through experimental trials with non-disabled subjects and transfemoral amputees.

Main Results:

• MLCM effectively reduces hip compensatory behavior and generates biomimetic knee kinematics.
• The controller improves stance phase time, stride length, and hip-knee coordination across different walking speeds.
• MLCM significantly reduces the number of control parameters from 17 to 7 and eliminates misrecognition during gait phase transitions.

Conclusions:

• Hip-knee motion-lagged coordination mapping (MLCM) provides a simplified, continuous, and speed-adaptive control solution for powered prostheses.
• MLCM enhances gait performance and coordination while reducing control complexity compared to FSM impedance control.
• The linear relationship between control parameters and walking speed facilitates real-time deployment and personalization.