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Portable System for Real-Time Detection of Stress Level
Currently, mental stress is a major problem in our society. It is related to a wide variety of diseases and is mainly caused by daily-life factors. The use of mobile technology for healthcare purposes has dramatically increased during the last few years. In particular, for out-of-lab stress detectio...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111320/ https://www.ncbi.nlm.nih.gov/pubmed/30071643 http://dx.doi.org/10.3390/s18082504 |
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author | Minguillon, Jesus Perez, Eduardo Lopez-Gordo, Miguel Angel Pelayo, Francisco Sanchez-Carrion, Maria Jose |
author_facet | Minguillon, Jesus Perez, Eduardo Lopez-Gordo, Miguel Angel Pelayo, Francisco Sanchez-Carrion, Maria Jose |
author_sort | Minguillon, Jesus |
collection | PubMed |
description | Currently, mental stress is a major problem in our society. It is related to a wide variety of diseases and is mainly caused by daily-life factors. The use of mobile technology for healthcare purposes has dramatically increased during the last few years. In particular, for out-of-lab stress detection, a considerable number of biosignal-based methods and systems have been proposed. However, these approaches have not matured yet into applications that are reliable and useful enough to significantly improve people’s quality of life. Further research is needed. In this paper, we propose a portable system for real-time detection of stress based on multiple biosignals such as electroencephalography, electrocardiography, electromyography, and galvanic skin response. In order to validate our system, we conducted a study using a previously published and well-established methodology. In our study, ten subjects were stressed and then relaxed while their biosignals were simultaneously recorded with the portable system. The results show that our system can classify three levels of stress (stress, relax, and neutral) with a resolution of a few seconds and 86% accuracy. This suggests that the proposed system could have a relevant impact on people’s lives. It can be used to prevent stress episodes in many situations of everyday life such as work, school, and home. |
format | Online Article Text |
id | pubmed-6111320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61113202018-08-30 Portable System for Real-Time Detection of Stress Level Minguillon, Jesus Perez, Eduardo Lopez-Gordo, Miguel Angel Pelayo, Francisco Sanchez-Carrion, Maria Jose Sensors (Basel) Article Currently, mental stress is a major problem in our society. It is related to a wide variety of diseases and is mainly caused by daily-life factors. The use of mobile technology for healthcare purposes has dramatically increased during the last few years. In particular, for out-of-lab stress detection, a considerable number of biosignal-based methods and systems have been proposed. However, these approaches have not matured yet into applications that are reliable and useful enough to significantly improve people’s quality of life. Further research is needed. In this paper, we propose a portable system for real-time detection of stress based on multiple biosignals such as electroencephalography, electrocardiography, electromyography, and galvanic skin response. In order to validate our system, we conducted a study using a previously published and well-established methodology. In our study, ten subjects were stressed and then relaxed while their biosignals were simultaneously recorded with the portable system. The results show that our system can classify three levels of stress (stress, relax, and neutral) with a resolution of a few seconds and 86% accuracy. This suggests that the proposed system could have a relevant impact on people’s lives. It can be used to prevent stress episodes in many situations of everyday life such as work, school, and home. MDPI 2018-08-01 /pmc/articles/PMC6111320/ /pubmed/30071643 http://dx.doi.org/10.3390/s18082504 Text en © 2018 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Minguillon, Jesus Perez, Eduardo Lopez-Gordo, Miguel Angel Pelayo, Francisco Sanchez-Carrion, Maria Jose Portable System for Real-Time Detection of Stress Level |
title | Portable System for Real-Time Detection of Stress Level |
title_full | Portable System for Real-Time Detection of Stress Level |
title_fullStr | Portable System for Real-Time Detection of Stress Level |
title_full_unstemmed | Portable System for Real-Time Detection of Stress Level |
title_short | Portable System for Real-Time Detection of Stress Level |
title_sort | portable system for real-time detection of stress level |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111320/ https://www.ncbi.nlm.nih.gov/pubmed/30071643 http://dx.doi.org/10.3390/s18082504 |
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