Title of article
MOPET: A context-aware and user-adaptive wearable system for fitness training
Author/Authors
Buttussi، نويسنده , , Fabio and Chittaro، نويسنده , , Luca، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2008
Pages
11
From page
153
To page
163
Abstract
SummaryObjective
vascular disease, obesity, and lack of physical fitness are increasingly common and negatively affect people’s health, requiring medical assistance and decreasing people’s wellness and productivity. In the last years, researchers as well as companies have been increasingly investigating wearable devices for fitness applications with the aim of improving user’s health, in terms of cardiovascular benefits, loss of weight or muscle strength. Dedicated GPS devices, accelerometers, step counters and heart rate monitors are already commercially available, but they are usually very limited in terms of user interaction and artificial intelligence capabilities. This significantly limits the training and motivation support provided by current systems, making them poorly suited for untrained people who are more interested in fitness for health rather than competitive purposes. To better train and motivate users, we propose the mobile personal trainer (MOPET) system.
s and material
is a wearable system that supervises a physical fitness activity based on alternating jogging and fitness exercises in outdoor environments. By exploiting real-time data coming from sensors, knowledge elicited from a sport physiologist and a professional trainer, and a user model that is built and periodically updated through a guided autotest, MOPET can provide motivation as well as safety and health advice, adapted to the user and the context. To better interact with the user, MOPET also displays a 3D embodied agent that speaks, suggests stretching or strengthening exercises according to user’s current condition, and demonstrates how to correctly perform exercises with interactive 3D animations.
s and conclusion
cribing MOPET, we show how context-aware and user-adaptive techniques can be applied to the fitness domain. In particular, we describe how such techniques can be exploited to train, motivate, and supervise users in a wearable personal training system for outdoor fitness activity.
Keywords
Wearable systems , Context-awareness , User-adaptation , Fitness training , Embodied agents
Journal title
Artificial Intelligence In Medicine
Serial Year
2008
Journal title
Artificial Intelligence In Medicine
Record number
1836666
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