Long-term disability can reduce someone's performance in activities or jobs. Although stroke is not the leading cause of disability, 75% of stroke survivors have decreased activity caused by disability. Serious long-term disability can be treated by using active movements, repetitive tasks, and task-oriented or movement sequences. Evaluation and monitoring the rehabilitation after stroke is the most crucial element to prevent the injury and determine the next step rehabilitation. This study will discuss monitoring arm movement for virtual reality (VR) game rehabilitation based on the trajectory movements. Five participants have contributed to data collection during three sessions and five repetition. Their movement recorded by using Kinect Xbox One sensor with data sampling 10 Hz. The mean absolute trajectory error (ATE) and hand speed movement methods are used to analyze the arm movement during the VR game. Although this study uses healthy subjects, 80% of them have an improvement in the movements, and this condition is proven by the reduced ATE value in each session. Trajectory data provides useful information about arm movements during the rehabilitation of VR games, including movement errors, hand position errors and hand speed to reach targets. Moreover, the mean ATE and hand speed movement able to provide clear information about the development of hand movements in completing the game.
