Stress Tracker—Detecting Acute Stress From a Trackpad: Controlled Study

BackgroundStress is a risk factor associated with physiological and mental health problems. Unobtrusive, continuous stress sensing would enable precision health monitoring and proactive interventions, but current sensing methods are often inconvenient, expensive, or suffer fr...

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Main Authors: Goel, Rahul, An, Michael, Alayrangues, Hugo, Koneshloo, Amirhossein, Lincoln, Emmanuel Thierry, Paredes, Pablo Enrique
Format: Article
Language:English
Published: JMIR Publications 2020-10-01
Series:Journal of Medical Internet Research
Online Access:http://www.jmir.org/2020/10/e22743/
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spelling doaj-4ef359b394fc420db4c9c5ebcc28972d2021-04-02T19:20:19ZengJMIR PublicationsJournal of Medical Internet Research1438-88712020-10-012210e2274310.2196/22743Stress Tracker—Detecting Acute Stress From a Trackpad: Controlled StudyGoel, RahulAn, MichaelAlayrangues, HugoKoneshloo, AmirhosseinLincoln, Emmanuel ThierryParedes, Pablo Enrique BackgroundStress is a risk factor associated with physiological and mental health problems. Unobtrusive, continuous stress sensing would enable precision health monitoring and proactive interventions, but current sensing methods are often inconvenient, expensive, or suffer from limited adherence. Prior work has shown the possibility to detect acute stress using biomechanical models derived from passive logging of computer input devices. ObjectiveOur objective is to detect acute stress from passive movement measurements of everyday interactions on a laptop trackpad: (1) click, (2) steer, and (3) drag and drop. MethodsWe built upon previous work, detecting acute stress through the biomechanical analyses of canonical computer mouse interactions and extended it to study similar interactions with the trackpad. A total of 18 participants carried out 40 trials each of three different types of movement—(1) click, (2) steer, and (3) drag and drop—under both relaxed and stressed conditions. ResultsThe mean and SD of the contact area under the finger were higher when clicking trials were performed under stressed versus relaxed conditions (mean area: P=.009, effect size=0.76; SD area: P=.01, effect size=0.69). Further, our results show that as little as 4 clicks on a trackpad can be used to detect binary levels of acute stress (ie, whether it is present or not). ConclusionsWe present evidence that scalable, inexpensive, and unobtrusive stress sensing can be done via repurposing passive monitoring of computer trackpad usage.http://www.jmir.org/2020/10/e22743/
collection DOAJ
language English
format Article
sources DOAJ
author Goel, Rahul
An, Michael
Alayrangues, Hugo
Koneshloo, Amirhossein
Lincoln, Emmanuel Thierry
Paredes, Pablo Enrique
spellingShingle Goel, Rahul
An, Michael
Alayrangues, Hugo
Koneshloo, Amirhossein
Lincoln, Emmanuel Thierry
Paredes, Pablo Enrique
Stress Tracker—Detecting Acute Stress From a Trackpad: Controlled Study
Journal of Medical Internet Research
author_facet Goel, Rahul
An, Michael
Alayrangues, Hugo
Koneshloo, Amirhossein
Lincoln, Emmanuel Thierry
Paredes, Pablo Enrique
author_sort Goel, Rahul
title Stress Tracker—Detecting Acute Stress From a Trackpad: Controlled Study
title_short Stress Tracker—Detecting Acute Stress From a Trackpad: Controlled Study
title_full Stress Tracker—Detecting Acute Stress From a Trackpad: Controlled Study
title_fullStr Stress Tracker—Detecting Acute Stress From a Trackpad: Controlled Study
title_full_unstemmed Stress Tracker—Detecting Acute Stress From a Trackpad: Controlled Study
title_sort stress tracker—detecting acute stress from a trackpad: controlled study
publisher JMIR Publications
series Journal of Medical Internet Research
issn 1438-8871
publishDate 2020-10-01
description BackgroundStress is a risk factor associated with physiological and mental health problems. Unobtrusive, continuous stress sensing would enable precision health monitoring and proactive interventions, but current sensing methods are often inconvenient, expensive, or suffer from limited adherence. Prior work has shown the possibility to detect acute stress using biomechanical models derived from passive logging of computer input devices. ObjectiveOur objective is to detect acute stress from passive movement measurements of everyday interactions on a laptop trackpad: (1) click, (2) steer, and (3) drag and drop. MethodsWe built upon previous work, detecting acute stress through the biomechanical analyses of canonical computer mouse interactions and extended it to study similar interactions with the trackpad. A total of 18 participants carried out 40 trials each of three different types of movement—(1) click, (2) steer, and (3) drag and drop—under both relaxed and stressed conditions. ResultsThe mean and SD of the contact area under the finger were higher when clicking trials were performed under stressed versus relaxed conditions (mean area: P=.009, effect size=0.76; SD area: P=.01, effect size=0.69). Further, our results show that as little as 4 clicks on a trackpad can be used to detect binary levels of acute stress (ie, whether it is present or not). ConclusionsWe present evidence that scalable, inexpensive, and unobtrusive stress sensing can be done via repurposing passive monitoring of computer trackpad usage.
url http://www.jmir.org/2020/10/e22743/
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