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With the development of smartphones containing built-in sensors of various kinds, an increasing amount of research effort is being devoted to recognition using wearable devices. In this paper, we limit our research to personal activity recognition, which is important to efficiently accumulate sensor data. We propose 1) a method to recognize conceptual group activity, and 2) a big data model to analyze...
Mobile applications to support physical activity have grown rapidly in the past years. Many users are attracted by the promised support for a healthier lifestyle. Still, the long-term effect of these applications can be doubt. A lack of theoretical foundation from behavior change theory is seen as a root cause for the lack of sustainable effects of these applications. Little is known about design...
Physical inactivity is a leading risk factor in a number of chronic diseases. Older adults are at the highest risk because they are the least inactive of all age groups. Smartphone-based intervention techniques present the opportunity to support cost-effective behavioral intervention to promote physical activity. We present a pilot study that examines the feasibility of utilizing the “Strive” smartphone-based...
This paper presents the practices of a research aiming at the design of a context-aware recommendation system that promotes the adoption of a healthy and active lifestyle. A Smartphone application that provides personalized and contextualized advice on physical activities was developed. The goal of our endeavor is to find out whether this recommendation system can generate motivating advice at an...
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