Literature DB >> 30825538

Stress detection in daily life scenarios using smart phones and wearable sensors: A survey.

Yekta Said Can1, Bert Arnrich2, Cem Ersoy3.   

Abstract

Stress has become a significant cause for many diseases in the modern society. Recently, smartphones, smartwatches and smart wrist-bands have become an integral part of our lives and have reached a widespread usage. This raised the question of whether we can detect and prevent stress with smartphones and wearable sensors. In this survey, we will examine the recent works on stress detection in daily life which are using smartphones and wearable devices. Although there are a number of works related to stress detection in controlled laboratory conditions, the number of studies examining stress detection in daily life is limited. We will divide and investigate the works according to used physiological modality and their targeted environment such as office, campus, car and unrestricted daily life conditions. We will also discuss promising techniques, alleviation methods and research challenges.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Daily life physiological data; Machine learning; Smartphone; Stress recognition; Wearable sensors

Mesh:

Year:  2019        PMID: 30825538     DOI: 10.1016/j.jbi.2019.103139

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  26 in total

1.  Stress Detection via Keyboard Typing Behaviors by Using Smartphone Sensors and Machine Learning Techniques.

Authors:  Ensar Arif Sağbaş; Serdar Korukoglu; Serkan Balli
Journal:  J Med Syst       Date:  2020-02-17       Impact factor: 4.460

2.  A multimodal and signals fusion approach for assessing the impact of stressful events on Air Traffic Controllers.

Authors:  Gianluca Borghini; Gianluca Di Flumeri; Pietro Aricò; Nicolina Sciaraffa; Stefano Bonelli; Martina Ragosta; Paola Tomasello; Fabrice Drogoul; Uğur Turhan; Birsen Acikel; Ali Ozan; Jean Paul Imbert; Géraud Granger; Railane Benhacene; Fabio Babiloni
Journal:  Sci Rep       Date:  2020-05-25       Impact factor: 4.379

3.  Predicting Chronic Stress among Healthy Females Using Daily-Life Physiological and Lifestyle Features from Wearable Sensors.

Authors:  Noa Magal; Sharona L Rab; Pavel Goldstein; Lisa Simon; Talita Jiryis; Roee Admon
Journal:  Chronic Stress (Thousand Oaks)       Date:  2022-07-25

4.  How to Relax in Stressful Situations: A Smart Stress Reduction System.

Authors:  Yekta Said Can; Heather Iles-Smith; Niaz Chalabianloo; Deniz Ekiz; Javier Fernández-Álvarez; Claudia Repetto; Giuseppe Riva; Cem Ersoy
Journal:  Healthcare (Basel)       Date:  2020-04-16

5.  How Laboratory Experiments Can Be Exploited forMonitoring Stress in the Wild: A Bridge BetweenLaboratory and Daily Life.

Authors:  Yekta Said Can; Dilara Gokay; Dilruba Reyyan Kılıç; Deniz Ekiz; Niaz Chalabianloo; Cem Ersoy
Journal:  Sensors (Basel)       Date:  2020-02-04       Impact factor: 3.576

6.  Wireless, continuous monitoring of daily stress and management practice via soft bioelectronics.

Authors:  Hojoong Kim; Yun-Soung Kim; Musa Mahmood; Shinjae Kwon; Fayron Epps; You Seung Rim; Woon-Hong Yeo
Journal:  Biosens Bioelectron       Date:  2020-11-04       Impact factor: 10.618

7.  Discrimination of simultaneous psychological and physical stressors using wristband biosignals.

Authors:  Mert Sevil; Mudassir Rashid; Iman Hajizadeh; Mohammad Reza Askari; Nicole Hobbs; Rachel Brandt; Minsun Park; Laurie Quinn; Ali Cinar
Journal:  Comput Methods Programs Biomed       Date:  2020-12-17       Impact factor: 5.428

8.  Validation of Affect-tag Affective and Cognitive Indicators.

Authors:  Laurent Sparrow; Hugo Six; Lauren Varona; Olivier Janin
Journal:  Front Neuroinform       Date:  2021-05-10       Impact factor: 4.081

9.  How Contextual Constraints Shape Midcareer High School Teachers' Stress Management and Use of Digital Support Tools: Qualitative Study.

Authors:  Julia B Manning; Ann Blandford; Julian Edbrooke-Childs; Paul Marshall
Journal:  JMIR Ment Health       Date:  2020-04-27

10.  Comparison of Regression and Classification Models for User-Independent and Personal Stress Detection.

Authors:  Pekka Siirtola; Juha Röning
Journal:  Sensors (Basel)       Date:  2020-08-07       Impact factor: 3.576

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.