How to relax in stressful situations : a smart stress reduction system

Can, YS ORCID: https://orcid.org/0000-0002-6614-0183, Iles-Smith, HM ORCID: https://orcid.org/0000-0002-0520-2694, Chalabianloo, N ORCID: https://orcid.org/0000-0001-7228-4725, Ekiz, D ORCID: https://orcid.org/0000-0002-8130-3841, Fernández-Álvarez, J, Repetto, C ORCID: https://orcid.org/0000-0001-8365-7697, Riva, G ORCID: https://orcid.org/0000-0003-3657-106X and Ersoy, C ORCID: https://orcid.org/0000-0001-7632-7067 2020, 'How to relax in stressful situations : a smart stress reduction system' , Healthcare, 8 (2) , p. 100.

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Abstract

Stress is an inescapable element of the modern age. Instances of untreated stress may lead to a reduction in the individual’s health, well-being and socio-economic situation. Stress management application development for wearable smart devices is a growing market. The use of wearable smart devices and biofeedback for individualized real-life stress reduction interventions has received less attention. By using our unobtrusive automatic stress detection system for use with consumer-grade smart bands, we first detected stress levels. When a high stress level is detected, our system suggests the most appropriate relaxation method by analyzing the physical activity-based contextual information. In more restricted contexts, physical activity is lower and mobile relaxation methods might be more appropriate, whereas in free contexts traditional methods might be useful. We further compared traditional and mobile relaxation methods by using our stress level detection system during an eight day EU project training event involving 15 early stage researchers (mean age 28; gender 9 Male, 6 Female). Participants’ daily stress levels were monitored and a range of traditional and mobile stress management techniques was applied. On day eight, participants were exposed to a ‘stressful’ event by being required to give an oral presentation. Insights about the success of both traditional and mobile relaxation methods by using the physiological signals and collected self-reports were provided.

Item Type:	Article
Schools:	Schools > School of Health and Society > Centre for Health Sciences Research
Journal or Publication Title:	Healthcare
Publisher:	MDPI
ISSN:	2227-9032
Related URLs:	Publication
Funders:	Horizons 2020 Marie-Curie Innovation Training Network
Depositing User:	Professor Heather Iles-Smith
Date Deposited:	20 Nov 2020 13:30
Last Modified:	16 Feb 2022 06:17
URI:	https://usir.salford.ac.uk/id/eprint/58881

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