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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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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