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Portable System for Real-Time Detection of Stress Level

Department of Computer Architecture and Technology, University of Granada, 18014 Granada, Spain
Research Centre for Information and Communications Technologies (CITIC), University of Granada, 18014 Granada, Spain
Department of Signal Theory, Telematics and Communications, University of Granada, 18014 Granada, Spain
Nicolo Association, 18194 Churriana de la Vega, Spain
School for Special Education San Rafael, 18001 Granada, Spain
Author to whom correspondence should be addressed.
Sensors 2018, 18(8), 2504;
Received: 30 June 2018 / Revised: 25 July 2018 / Accepted: 28 July 2018 / Published: 1 August 2018
(This article belongs to the Special Issue New Trends in Psychophysiology and Mental Health)
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. View Full-Text
Keywords: stress; biosignal; EEG; ECG; EMG; GSR; real-time; healthcare; e-Health; m-Health stress; biosignal; EEG; ECG; EMG; GSR; real-time; healthcare; e-Health; m-Health
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MDPI and ACS Style

Minguillon, J.; Perez, E.; Lopez-Gordo, M.A.; Pelayo, F.; Sanchez-Carrion, M.J. Portable System for Real-Time Detection of Stress Level. Sensors 2018, 18, 2504.

AMA Style

Minguillon J, Perez E, Lopez-Gordo MA, Pelayo F, Sanchez-Carrion MJ. Portable System for Real-Time Detection of Stress Level. Sensors. 2018; 18(8):2504.

Chicago/Turabian Style

Minguillon, Jesus, Eduardo Perez, Miguel Angel Lopez-Gordo, Francisco Pelayo, and Maria Jose Sanchez-Carrion. 2018. "Portable System for Real-Time Detection of Stress Level" Sensors 18, no. 8: 2504.

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