The Effect of Robot-aided Training on Motor Recovery following Stroke

Abstract

Recent advances in robotic technology have been widely applied in rehabilitation medicine. In particular, a robot-aided self-training regimen in combination with virtual reality (VR) feedback is a vital alternative to conventional therapeutic maneuvers (e.g. passive and active range of motion training). Such a self-administered regimen using robotic-aid could lead to longer training hours, in turn leading to intensive rehabilitation potential for both hospital and home settings. To this end, we developed an upper limb rehabilitation robot that allows three-dimensional training in combination with visual feedback and force feedback by the use of VR technology, and we evaluated its effectiveness for patients with hemiplegia after stroke. We recruited 6 chronic patients of stroke-induced hemiplegia. The subjects received 40 minutes of robotic therapy 3 times a week for 6 weeks. The Fugl-Meyer Assessment (FMA) and Motricity Index where measured before beginning and after completion of the 6-week training course. The nonparametric Wilcoxon signed rank test was used to assess any improvement in the test scores between the before and after experimental periods. For the FMA assessment, the paired t-test detected statistically significant improvement (p <0.05). The FMA consisted of four subcomponents for shoulder/elbow/forearm movements, wrist movements, finger movements and speed and coordination. To further investigate the statistically significant improvements in the FMA, additional analyses were performed using these subclass scores. The nonparametric Wilcoxon signed rank test detected statistically significant improvement in the shoulder/elbow/forearm movements (p <0.05), but not in the wrist or finger movements.