S. Diny Syarifah’s research while affiliated with Universitas Suryakancana and other places

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 10Hz. 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.

Stroke is a leading cause of serious long-term disability. World Health Organization (WHO) published that the second leading of death is stroke accident and every year, 15 million people worldwide suffer from stroke attack, two-thirds of them have a permanent disability. Muscle impairment can be treated by intensive movements involving repetitive task, task-oriented and task-variegated. Conventional stroke rehabilitation is expensive, less engaging and at the same time need more time for the rehabilitation process and need more energy and time for the therapist to guide the stroke-survivor. Modern stroke rehabilitation is more promising and more effective with modern rehabilitation aids allowing the rehabilitation process to be faster, however, this therapist method can be obtained in the big cities. To cover the lack of rehabilitation process in this research will develop and improve post-stroke rehabilitation using games. This research using electromyography (EMG) device to analyze the muscle contraction during the rehabilitation process and using Kinect XBOX to record trajectory hands movements. Five games from movements sequence have designed and will be examined in this research. This games obtained two results, the first is the EMG signal and the second is trajectory data. EMG signal can recognize muscle contractions during playing game and the trajectory data can save the pattern of movements and showed the pattern to the monitor. EMG signal processing using time or frequency feature extractions is a good idea to obtain more information from muscle contractions, also velocity, similarities and error movements can be obtained by study the possible approaches.