下肢外骨骼康复机器人步态相识别

Gait Phase Recognition of Lower Limb Exoskeleton Rehabilitation Robot

外骨骼机器人作为一种新型的康复设备,在脊髓损伤患者的康复训练中具有广阔的应用前景。其中,人体步态相识别是实现外骨骼机器人穿戴者运动意图识别和准确控制的关键之一。首先,针对脊髓损伤患者康复训练中摆腿触地过程无法自主锁定膝关节的问题,设计了一款绳驱下肢外骨骼康复机器人。该款外骨骼机器人通过足底开关传感器和膝关节编码器来采集患者步态信息,并在一个步态周期内不同的步态相对膝关节进行锁定或放松。其次,通过对人体行走步态的研究和脊髓损伤患者康复训练中锁膝和松膝的需求分析,提出了一种基于足底与地面接触过程信息的步态相分类方法。由于脊髓损伤患者的足底接触过程不可控且不稳定,将膝关节摆角和摆动速度信息引入步态相识别中,提出了融合脚与地面接触信息、膝关节摆角及摆动速度信息的步态相识别方法。最后,基于采集到的志愿者步态数据,进行了步态相识别方法的实验验证。结果表明,所提方法的平均步态相识别率达到99.906%,并且当足底开关传感器发生故障或未正常触发时,锁膝相和松膝相的正确识别率仍然分别达到94.488%和91.853%,从而验证了所提方法的有效性和容错能力。

Exoskeleton robots,as a new type of rehabilitation equipment,have a broad application pros-pect in the rehabilitation training of patients with spinal cord injuries.Human gait phase recognition is a key technology to realize the movement intention recognition of wearers and accurately control exoskeleton robots.As the knee joint cannot be locked automatically in the process of swinging the leg to the ground during the rehabilitation training of patients with spinal cord injuries,a rope-drive lower limb rehabilitation training exoskeleton robot is first designed.Foot switch sensors and a knee joint encoder are used to acquire the gait information of the patient to ensure that the knee joint is locked and released in the corresponding gait phase.Based on research on human walking gait and the need to lock and release the knee during the rehabilitation training of patients with spinal cord injuries,a gait phase classification method based on information about the contact process between the foot and the ground is proposed.Because the plantar contact process of patients with spinal cord injuries is uncontrollable and unstable,a gait phase recognition method integrating information about the contact between the foot and the ground and the swing angle and speed of the knee joint is proposed.Finally,the experimental verification of the gait phase recognition method is performed using the acquired gait data of volunteers.The results show that the average gait phase recognition rate of the proposed method is 99.906%.When the foot switch sensor fails or is not triggered normally,the correct recognition rates of the locking and releasing knee phases are 94.488%and 91.853%,respectively,demonstrating the effectiveness and fault tolerance of the proposed method.