Low energy physical activity recognition system on smartphones

Sensors
Luis Miguel Soria MorilloMiguel Angel Alvarez de la Concepcion

Abstract

An innovative approach to physical activity recognition based on the use of discrete variables obtained from accelerometer sensors is presented. The system first performs a discretization process for each variable, which allows efficient recognition of activities performed by users using as little energy as possible. To this end, an innovative discretization and classification technique is presented based on the χ2 distribution. Furthermore, the entire recognition process is executed on the smartphone, which determines not only the activity performed, but also the frequency at which it is carried out. These techniques and the new classification system presented reduce energy consumption caused by the activity monitoring system. The energy saved increases smartphone usage time to more than 27 h without recharging while maintaining accuracy.

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Citations

Sep 9, 2017·Sensors·Lingxiang ZhengHuiru Zheng
Oct 12, 2016·International Journal of Environmental Research and Public Health·Chung-Tse Liu, Chia-Tai Chan
Jul 15, 2021·Computer Methods and Programs in Biomedicine·Manuel AbbasRégine Le Bouquin Jeannès

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Methods Mentioned

BETA
feature extraction
Profiler

Software Mentioned

PAMAP2
WindowsSleep
Trepn
Ameva
Trepn Qualcomm
Android Studio
Nexus
MATLAB
Trepn Profiler
Samsung Galaxy S3

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