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Low Energy Physical Activity Recognition System on Smartphones
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 e...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4435175/ https://www.ncbi.nlm.nih.gov/pubmed/25742171 http://dx.doi.org/10.3390/s150305163 |
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author | Morillo, Luis Miguel Soria Gonzalez-Abril, Luis Ramirez, Juan Antonio Ortega de la Concepcion, Miguel Angel Alvarez |
author_facet | Morillo, Luis Miguel Soria Gonzalez-Abril, Luis Ramirez, Juan Antonio Ortega de la Concepcion, Miguel Angel Alvarez |
author_sort | Morillo, Luis Miguel Soria |
collection | PubMed |
description | 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 χ(2) 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. |
format | Online Article Text |
id | pubmed-4435175 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-44351752015-05-19 Low Energy Physical Activity Recognition System on Smartphones Morillo, Luis Miguel Soria Gonzalez-Abril, Luis Ramirez, Juan Antonio Ortega de la Concepcion, Miguel Angel Alvarez Sensors (Basel) Article 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 χ(2) 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. MDPI 2015-03-03 /pmc/articles/PMC4435175/ /pubmed/25742171 http://dx.doi.org/10.3390/s150305163 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Morillo, Luis Miguel Soria Gonzalez-Abril, Luis Ramirez, Juan Antonio Ortega de la Concepcion, Miguel Angel Alvarez Low Energy Physical Activity Recognition System on Smartphones |
title | Low Energy Physical Activity Recognition System on Smartphones |
title_full | Low Energy Physical Activity Recognition System on Smartphones |
title_fullStr | Low Energy Physical Activity Recognition System on Smartphones |
title_full_unstemmed | Low Energy Physical Activity Recognition System on Smartphones |
title_short | Low Energy Physical Activity Recognition System on Smartphones |
title_sort | low energy physical activity recognition system on smartphones |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4435175/ https://www.ncbi.nlm.nih.gov/pubmed/25742171 http://dx.doi.org/10.3390/s150305163 |
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