CloudMat: Context-aware Personalization of Fitness Content
Penn collection
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Computer Engineering
Electrical and Computer Engineering
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Abstract
Digital video content via broadcast television, Internet and other content distribution networks provide limited interaction for fitness and wellness activities. The content delivery is one-way only and provides no personalization to the pace, programming and progress of the user’s exercise routine. Furthermore, the content is to be viewed only on a screen which makes it awkward and incompatible with full-body activities such as yoga, pilates and T’ai chi. We present CloudMat, a system for context-aware personalization of fitness content with cloudenabled connected surfaces. CloudMat provides real-time closedloop feedback between the state of the user on the physical mat and the state of the content in the cloud service. Content is tagged with actuation signals where events are delegated from the screen to display on an electroluminescent lighting layer on the mat, which provides spatial guidance to the end-user. Through the sensor-layer embedded in the mat, the physical interface captures the pose and timing of the user activity and relays it to the Context-aware Personalization cloud service. This service coordinates sensing and actuation between the content stream and mat by generating pose templates and metadata files about the exercise routine to be delivered to the user. Through this interactive process between the physical mat and the content service, the feedback provided by the user performing the routine continuously adapts the pace and programming to maintain the desired user experience. We demonstrate the utility of the system and evaluate the system performance with a case study on interactive yoga.