Development of arm training system for hemiplegic upper-extremityafter stroke using virtual reality motor learning and evaluation of the effect.

中风后偏瘫上肢需要一种有效的、日常可执行的训练方法。本研究利用镜像神经元系统理论开发了一种新的训练系统。该系统由PC机、显示器和患手的运动传感器组成。受试者被要求根据虚拟手在显示器上的移动来移动桌子上受影响的手。通过对健康受试者和偏瘫患者进行3D运动分析和问卷调查，评价模拟动作训练的效果。

A training method that can be executed effectively and daily is requested for hemiplegic upper-extremity after stroke. In this study, a new training system was developed using the theory of mirror neuron system. The system was consisted of PC, display and motion sensor of an affected hand. Subjects were required to move the affedcted hand on the desk according to the movement of the virtual hand in the display. The effects of imitating movement for hemiplegic training were evaluated by 3D motion analysis and questionnaires with healthy subjects and hemiplegic patients.