基于改进模板匹配的智能下肢假肢运动意图实时识别

Real-time motion intent recognition of intelligent lower limb prosthesis based on improved template matching technique

传统下肢假肢运动意图识别常使用多模态传感器采集残肢侧时频域特征,在短时意图识别中,具有一定的复杂性和滞后性,且时频域特征不稳定难以达到实时意图识别的目的.鉴于此,提出基于改进模板匹配技术的智能下肢假肢运动意图实时识别的方法.在重新定义单侧下肢截肢者的运动模式后,仅采用惯性传感器采集健肢侧位于摆动相的数据,基于改进的模板匹配,通过滑动窗口创建完备的模板库,使得每类运动模式在库中有充足的原子模式,对下肢假肢的运动意图进行实时识别.实验结果表明,所提出方法在5种稳态模式(平地行走、上下楼、上下坡)的识别率为99.50%,在引入8种转换模式后的识别率为97.03%,可以大大提高下肢假肢实时识别性能,助力单侧下肢截肢者更自然地行走.

Traditional lower limb prosthesis motion intent recognition often uses multi-modal sensors to collect timefrequency domain features of the residual limb side. In short-term intent recognition, it has certain complexity and lag,and time-frequency domain features are unstable, which is difficult to achieve the purpose of real-time intent recognition.This paper proposes a real-time intelligent lower limb prosthesis motion intent recognition method based on improved template matching technology. After the amputee’s motion pattern is acquired, onlys an inertial sensor is used to collect the data of the sound limb side in the swing phase. Based on the improved template matching, a complete template library is created through sliding window, so that each kind of motion pattern is sufficient atomic patterns in the library, and the motion intent of the lower limb prosthesis is recognized in real time. The experimental results show that the recognition rate of the algorithm reaches 99.50% in 5 steady states: level-ground walking, stair ascent, stair descent, ramp ascent and ramp descent, and 97.03% after introducing 8 transitional states. This method can greatly improve the real-time recognition performance of lower limb prosthesis and help unilateral lower limb amputees walk more naturally.