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A Personalized Gait Parameter Prediction-Based Speed-Adaptive Control Method for Hybrid Active-Passive Intelligent
Xiaoming Wang1, Yuanhua Li1, Hui Li1
1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Biomimetics (Basel, Switzerland)
|February 26, 2026
Summary
This study introduces a smart prosthetic knee that adapts to individual walking styles and speeds. It significantly improves gait symmetry and naturalness for users by predicting personalized gait parameters.
Area of Science:
- Biomedical Engineering
- Robotics
- Rehabilitation Technology
Background:
- Current prosthetic knees struggle with personalized adaptation to user gait and walking speed.
- Lack of real-time adjustment leads to unnatural gait and potential asymmetry.
Purpose of the Study:
- To develop a speed-adaptive control method for a hybrid active-passive intelligent prosthetic knee (HAPK).
- To achieve personalized gait control by predicting individual gait parameters.
- To enhance user mobility and reduce gait asymmetry.
Main Methods:
- A perceptron-based model predicts individualized gait parameters from anthropometric data and walking speed.
- Fuzzy logic damping control (swing phase) and position-torque control (stance extension) enable real-time adaptation.
- A hybrid actuation system combines hydraulic damping and motor torque assistance.
Main Results:
- The proposed control method reduced stance and swing asymmetries by 30-38%.
- Achieved smoother and more natural gait transitions compared to fixed-gait controls.
- Demonstrated effectiveness in variable-speed walking tests.
Conclusions:
- The personalized gait parameter prediction-based control is effective for intelligent prosthetic knees.
- The HAPK system offers continuous, personalized, and speed-consistent gait control.
- This approach enhances prosthetic limb functionality and user experience.
