PhysioTreadmill: An Auto-Controlled Treadmill Featuring Physiological-Data-Driven Visual/Audio Feedback
PubDate: October 2020
Teams: Nanyang Technological University
Writers: Shaolong Liu; Xingce Wang; Zhongke Wu; Ying He
Abstract
We present an automated treadmill featuring physiological-data-driven feedback-PhysioTreadmill, which allows its user to easily control running settings based on their physical condition and can also motivate them through real-time physiological computing. We developed a robust exercise intensity self-adaptive adjustment algorithm using physiological data processing to adjust the user’s physiological state accurately. We also designed exergames with physiological-data-driven visual/audio feedback in PhysioTreadmill. With PhysioTreadmill, we can ideally increase exercise duration, and enhance exercise performance and safety. Two user studies involving 42 participants showed that PhysioTreadmill is user-friendly and can effectively extend users’ training duration.
