A SERIOUS GAME FOR IMPROVING ELDERLY MOBILITY BASED ON USER EMOTIONAL STATE

• Published in: eLearning and Software for Education 2017, Vol.13 (2), p.487-494
• Main Authors: Mocanu, Irina, SCHIPOR, Ovidiu Andrei
• Format: Article
• Language: English
• Subjects: Social Sciences
• ISSN: 2066-026X; 2066-8821

Many studies highlight the relationship between emotional state and behaviour. Emotions influence elderly people especially on physical activity and their mobility. It was shown that people with positive emotions perform more physical activity and have less difficulty in walking. Thus we can say that positive emotions can be associated with mobility in case of older people. Some older people may develop fear of moving, leading to reduce the outdoor mobility. An active lifestyle can maintain or improve everyday life, delaying different types of disabilities and mental health disease through elderly people. Also, emotions play a primary role into the structure and experience of Serious Games. The linkage between emotions and actions is extremely relevant in learning processes - learning is viewed as a process of participatory appropriation, where the learner acts and actively participates in doing within specific routinized contexts. The purpose of this paper is to present the development of an application as a serious game that aims to help elderly people to learn how to perform physical exercises in order to maintain a healthy lifestyle in their homes. A personalized program has as main advantage a higher flexibility, as it offers the patient the possibility of adjusting his training schedule according to his preferences and daily activities. In this sense, there is need for a sustainable platform designed specifically for performing physical exercises at home that would promote increasing mobility, especially for elderly people. An efficient method to accomplish this purpose is through the development of a cheap, accessible and easy to use a serious game, based on the motion capture technology. The exercises that need to be performed by the patient are automatically selected according to his profile, medical condition and acquired progress. By using the Kinect motion capture device, our application analyses the user's movements and compares them to those of a trainer character, by taking into account the performance and efficiency parameters. Also, the type of the exercise will be adjusted based on emotions, and the motivation of the user in performing physical exercises will be increased. Emotions are recognised using facial features (Facial Action Coding System) extracted from the user face using Microsft.Kinect and Microsoft.Kinect.Face libraries. Our system has been tested with several users who acquired a certain degree of progress. Therefore, we con