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My act: an automatic daily caloric estimation based on physical activity data using smart phones

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TLDR
This work modifications the android application to classify into activities: sleep, rest, walk and run, and converts the activity to energy expenditure using MET data published in the compendium of physical activities tracking guide.
Abstract
At last year conference (i-CREATe 2012), we presented the android application that classified our daily physical and commuting activities. It was shown that the classification resulted in good accuracy (higher than 95% on average) and with reasonable battery consumption. We extend our previous work and focus on physical activity detection. We modify in this current work our application to classify into activities: sleep, rest, walk and run. Then we convert the activity to energy expenditure using MET data published in the compendium of physical activities tracking guide. We also provide the following relevant information: duration of each activity, step counts and distance obtained with walk and run activities. This tool can be used to automatically provide information on user's daily pattern of physical activity. We perform several tests of performance and show that although the application depends on several factors, it works very well in most situations.

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Tracking daily activity using smart phones

TL;DR: Three important issues are addressed in this work including battery consumption, varying specification of accelerometer chips, and classification in an uncontrolled free environment.
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