Low Energy Physical Activity Recognition System on Smartphones

Sensors

Luis Miguel Soria Morillo²  Luis Gonzalez-Abril¹  Juan Antonio Ortega Ramirez²  Miguel Angel Alvarez de la Concepcion² 

[1] Applied Economics I Department, University of Seville, 41018 Seville, Spain; E-Mail:;Computer Languages and Systems Department, University of Seville, 41012 Seville, Spain; E-Mails:

关键词: contextual information;    mobile environment;    discretization method;    qualitative systems;    smart-energy computing;   

DOI  :  10.3390/s150305163

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.