Abstract
This paper presents the design, implementation and validation of a novel fitness mobile application called CalAid, aimed at promoting an active lifestyle, in the context of ever growing sedentarism in population of all ages. The application uses sensors present in most modern smartphones such as motion sensors, the 3-axial accelerometer, the gyroscope and the step counter in order to track energy expenditure and to obtain a more precise approximation of consumed calories. By using machine learning we can recognize the activities performed by the application client and, using metabolic equivalents, find the energy expenditure.
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