Mostrar el registro sencillo del ítem
Portable System for Real-Time Detection of Stress Level
dc.contributor.author | Minguillón Campos, Jesús | |
dc.contributor.author | Pérez Valero, Eduardo | |
dc.contributor.author | López Gordo, Miguel Ángel | |
dc.contributor.author | Pelayo Valle, Francisco José | |
dc.contributor.author | Sanchez-Carrion, Maria Jose | |
dc.date.accessioned | 2019-04-03T11:57:49Z | |
dc.date.available | 2019-04-03T11:57:49Z | |
dc.date.issued | 2018-08-01 | |
dc.identifier.citation | Minguillon, J. [et al.]. Portable System for Real-Time Detection of Stress Level. Sensors 2018, 18, 2504 | es_ES |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://hdl.handle.net/10481/55332 | |
dc.description.abstract | 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. | es_ES |
dc.description.sponsorship | This research was funded by [Ministry of Economy and Competitiveness (Spain)] grant number [TIN2015-67020P], [Ministry of Economy and Competitiveness (Spain)] grant number [DPI2015-69098-REDT], [Junta of Andalucia (Spain)] grant number [P11-TIC-7983], [Spanish National Youth Guarantee Implementation Plan] grant number [Research contract], [Nicolo Association for the R+D in neurotechnologies for disability] grant number [Research support], and [Orden Hospitalaria San Juan de Dios] grant number [Beca investigacion]. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | Atribución 3.0 España | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Biosignal | es_ES |
dc.subject | EEG | es_ES |
dc.subject | ECG | es_ES |
dc.subject | EMG | es_ES |
dc.subject | GSR | es_ES |
dc.subject | Real-time | es_ES |
dc.subject | Healthcare | es_ES |
dc.subject | e-Health | es_ES |
dc.subject | m-Health | es_ES |
dc.title | Portable System for Real-Time Detection of Stress Level | es_ES |
dc.type | journal article | es_ES |
dc.rights.accessRights | open access | es_ES |