1. PhysioTreadmill: An Auto-Controlled Treadmill Featuring Physiological-Data-Driven Visual/Audio Feedback
- Author
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Wang Xingce, Ying He, Liu Shaolong, and Wu Zhongke
- Subjects
Adaptive control ,Group method of data handling ,Computer science ,05 social sciences ,020207 software engineering ,02 engineering and technology ,Virtual reality ,Data-driven ,Human–computer interaction ,0202 electrical engineering, electronic engineering, information engineering ,Exercise intensity ,0501 psychology and cognitive sciences ,Audio feedback ,Treadmill ,Robust control ,050107 human factors - 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.
- Published
- 2020