Bio-Inspired Auto-Adaptive Framework for Passive Knee Prosthesis

Abstract

This research addresses the challenges faced by amputees due to missing limbs, which hinder them from performing daily tasks. Prostheses are used as replacements for the lost limb and it is difficult for them to learn to adapt. Therefore, the mobility and gait posture are disturbed. These factors lead to fatigue, and the amputees are at high risk of falling. The goal was to design a bio-inspired framework that can adapt automatically to compensate for lost movement of amputees using passive knee prosthesis. The framework thoroughly examines the bio-mechanics of human movement, gait analysis, use of prosthesis with damping control mechanism, and a data acquisition system with IMU sensors, electro-goniometer, EMG, and tactile sensors. We performed an empirical analysis of the functional roles of the human brain (HBN) and machine brain (MBN) in daily activities. We applied the framework and tested it on the patient in the real-world to optimize the movement with the prosthetic leg. We collected the gait data for able-bodied persons exhibiting periodic and smooth curves of gait data termed natural gait. The correction factor "h(N)" of our mathematical model vanishes after ’03’ gait cycles, and the movement is optimized with smoothed patterns. The framework efficiently controlled the amputee’s knee flexion curve within the normal range of motion (64◦±6). our deep learning architecture obtained a good accuracy of the model to be 94.44% and With 93% testing accuracy for the amputee, for gait phase detection. Our empirical study showed a functional distribution of 70% HBN involvement and 30% MBN (the machine’s brain) input to routine life activities. The success rate was 95% to maintain balance and fall prevention using the proposed strategies. It takes the signal from the rectus femoris muscles using an EMG sensor when there is a danger of falling. The hard tone of muscles maximizes the damping through the gear design mechanism, which in turn provides natural locking, and the amputee stops the movement. The suggested framework showed enhanced mobility, decreased hip hikes and tiredness, control of normal knee flexion, and less risk of falling. This study offers a viable way to improve the functionality of passive knee prosthesis, significantly improving the quality of life for amputees.