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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-08-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/18/8/2504 |
| _version_ | 1828118960643506176 |
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| author | Jesus Minguillon Eduardo Perez Miguel Angel Lopez-Gordo Francisco Pelayo Maria Jose Sanchez-Carrion |
| author_facet | Jesus Minguillon Eduardo Perez Miguel Angel Lopez-Gordo Francisco Pelayo Maria Jose Sanchez-Carrion |
| author_sort | Jesus Minguillon |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-11T13:40:27Z |
| format | Article |
| id | doaj.art-27c607f9f65549a5bdab42bf52d3c1bf |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T13:40:27Z |
| publishDate | 2018-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-27c607f9f65549a5bdab42bf52d3c1bf2022-12-22T04:21:16ZengMDPI AGSensors1424-82202018-08-01188250410.3390/s18082504s18082504Portable System for Real-Time Detection of Stress LevelJesus Minguillon0Eduardo Perez1Miguel Angel Lopez-Gordo2Francisco Pelayo3Maria Jose Sanchez-Carrion4Department of Computer Architecture and Technology, University of Granada, 18014 Granada, SpainResearch Centre for Information and Communications Technologies (CITIC), University of Granada, 18014 Granada, SpainResearch Centre for Information and Communications Technologies (CITIC), University of Granada, 18014 Granada, SpainDepartment of Computer Architecture and Technology, University of Granada, 18014 Granada, SpainSchool for Special Education San Rafael, 18001 Granada, SpainCurrently, 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.http://www.mdpi.com/1424-8220/18/8/2504stressbiosignalEEGECGEMGGSRreal-timehealthcaree-Healthm-Health |
| spellingShingle | Jesus Minguillon Eduardo Perez Miguel Angel Lopez-Gordo Francisco Pelayo Maria Jose Sanchez-Carrion Portable System for Real-Time Detection of Stress Level Sensors stress biosignal EEG ECG EMG GSR real-time healthcare e-Health m-Health |
| 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 | stress biosignal EEG ECG EMG GSR real-time healthcare e-Health m-Health |
| url | http://www.mdpi.com/1424-8220/18/8/2504 |
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