SERIOUS GAMES FOR REHABILITATION OF LOWER MEMBERS OF POST-AVC PATIENTS USING KINECT, VIRTUAL ENVIRONMENTS AND MYIOELETRIC SIGNS.
Name: JANAÍNA DE OLIVEIRA MUNIZ LYRA
Publication date: 17/11/2016
Advisor:
Name |
Role |
|---|---|
| TEODIANO FREIRE BASTOS FILHO | Advisor * |
Examining board:
| Name |
Role |
|---|---|
| ANTONIO ALBERTO RIBEIRO FERNANDES | Internal Examiner * |
| TEODIANO FREIRE BASTOS FILHO | Advisor * |
Summary: Incapacities are the most common symptoms after stroke. When lower limbs are affected, the performance of daily activities are compromised. A recent development in the rehabilitation field is the use of serious games composed of virtual environments (VE) associated with sEMG Biofeedback to increase and improve the performance of rehabilitation. Through this biofeedback, myoelectric signals are converted into visual and auditory information, allowing patients to control their muscle activity. The objective of this work is to design and evaluate an assistive technology (AT), based on serious games, focused on the rehabilitation of lower limbs of post-stroke volunteers. This AT is composed of VEs and sensors of motion and surface electromyography (sEMG). The system has been developed considering the functional limitations and residual abilities of the target audience, seeking to create a motivating environment. The developed system provides the user with biofeedback in real time, showing his/her muscle activation level in the screen of the VA. The VEs aim to motivate volunteers to perform the movements of stand-up/sit-down and extension/flexion. In order to evaluate the system, trials were performed with nine post-stroke volunteers, which assessed the system through the following questionnaires: System Usability Scale metrics (SUS), Goal Attainment Scale (GAS) and Virtual Environment Assessment Questionnaire (QAAV). Based on the results, the system was well evaluated, highlighting some points to be improved in future releases. Moreover, an analysis of the myoelectric signals and range of motion showed that the system was efficient to accomplish its main purpose.
Key words: Stroke, rehabilitation, serious games, biofeedback, electromyography and virtual environments.
