HAND-REHA
Farnaz Farahanipad, Harish Ram Nambiappan, Ashish Jaiswal, Maria Kyrarini, Fillia Makedon
Abstract
Hand-gesture recognition systems have recently gained more popularity. Moreover, there is a growing interest in building games for other purposes apart from entertainment, such as education and rehabilitation. This paper focuses on developing a novel game-based system for wrist rehabilitation, called HandReha. The idea is to automatically recognize pre-defined hand gestures using a web-camera, so to control an avatar in a three dimensional maze run game. The pre-defined gestures are picked from a pool of well-defined gestures suitable for wrist rehabilitation. Deep learning techniques were utilized to perform real-time hand gesture recognition from the images. To evaluate the performance of the developed wrist rehabilitation system, a preliminary study with 12 healthy participants was conducted. The results showed that the developed wrist rehabilitation system is intuitive and engages the user, which is crucial for rehabilitation purposes.