Exploring Data Glove and Robotics Hand Exergaming: Lessons Learned

Abstract

In this preliminary study, we explore the use of a high-end data glove as a consumer-level hand exergame human interface device. Disorders affecting the musculoskeletal apparatus account for approximately 43 % of all workplace related injuries, leading to increasing claim costs and work absenteeism. Treatment includes unsupervised stretching and exercising with low adherence due to its monotonous and repetitive nature. Exergames, that is the use of games to elicit physical activity, provide engaging experiences that can help motive patients or workers into performing the exercises. Previous works using consumer-level technology have focused on image-based and open electronics 3D printed gloves that have shown the potential of exergames and motion capture as a tool to add immersion. In this paper, we present exergame that employs the Yamaha Data Glove (YDG) integrated to a computer- and robot-based exergame. The data glove allows controlling a virtual arcade crane in addition to interactive sessions with a social robot called ASUS Zenbo Junior. The preliminary quantitative and qualitative data suggest that motion capture data requires further processing and customization to tailor the experience to each user to improve usability and cognitive load affected by suitable tracking hand gestures. The exergame also requires additional cues to ease the experience and maintain users within a state flow.