A fuzzy logic based Parkinson´s Disease risk predictor

With the world population aging rapidly, improving the quality of life for senior citizens has become an important societal issue. Parkinson´s Disease (PD) is one of the most debilitating neuro-degenerative disorders that seriously affect the seniors´ quality of life. In recent years, video games have been shown to be a viable way through which partial rehabilitation for PD can be carried out in a fun and low cost manner. Earlier research has shown that both patients´ physical and mental conditions can be improved by playing video games. However, so far, the available games developed for PD are mostly intended for rehabilitation purposes. PD diagnosis still depends on the traditional neurological exams and experience of doctors, which require the patients to become self-aware of the symptoms and are usually too late for the patients to delay the progression of PD. To support the early detection of PD symptoms, we propose a fuzzy logic based PD risk predictor that has been implemented in a tablet game platform. The player´s behavior data in the game environment are captured unobtrusively and analyzed in real-time. The player´s current risk of developing PD is estimated using the proposed fuzzy logic based approach, which will help the player to be aware of high risk of having PD at an earlier stage. A pilot evaluation has been conducted to demonstrate the effectiveness of the proposed approach.