基于Kinect的机器人辅助上肢被动康复训练控制方法

现有基于Kinect构建的康复训练系统,大多以患者自行开展主动康复训练为主,未能充分利用康复医师的临床经验且很少用于机器人辅助康复训练系统,具有一定的局限.针对此问题,提出一种基于Kinect的机器人辅助上肢被动康复训练方法.首先,开展基于Kinect的上肢骨骼点跟踪与逆运动学计算;其次,基于Linux/QT及Kinect设计三维虚拟康复训练环境;再次,在康复医师示教训练任务并通过Kinect获取示教任务参考轨迹基础上,根据训练过程中Kinect实时捕获的患肢运动位置反馈,设计基于模糊推理的机器人辅助被动康复训练控制器;最后,基于Kinect及Barrett公司4自由度WAM^TM康复机器人构建试验统平台,对方法有效性进行试验验证.实验结果表明,所提方法能有效利用医师的临床康复经验,并使机器人较平稳地牵引受试者上肢沿示教任务轨迹进行训练,较好地实现了"医师-机器人-患者"之间的人机协同康复训练.

Passive training method using Kinect-based upper-limb rehabilitation robot

Existing Kinect-based rehabilitation training systems,which focus on active rehabilitation training executed by the patients themselves and are seldom applied to robot-aided rehabilitation training,have certain limitations.To solve these problems,a Kinect-based robot-aided upper-limb passive rehabilitation training method was proposed.Firstly,Kinect-based upper-limb skeleton tracking and inverse kinematics computation were conducted.Secondly,the virtual rehabilitation environment based on Linux/QT and Kinect was developed.Using the reference trajectories of the training task demonstrated by the therapist and the impaired limb''s real-time motion position feedback,a fuzzy-based passive rehabilitation training controller was developed.Finally,using Kinect and the 4-DOF WAM^TM-compliant manipulator of Barrett Inc.,the experimental system platform was constructed to evaluate the effectiveness of the proposed method.The results show that the proposed method can fully learn the therapist''s rehabilitation experiences,make the robot manipulator smoothly stretch the upper-limb of the patient along predefined training task trajectories,and achieve human-robot collaborations between therapist-robot-patient.