Sleep Quality Tracking and Alignment with a Simple In-the-Wild Task
Language
English
Type
Proceedings of International Conferences
Authors
Andrew W. Vargo, Masayuki Fujimoto, Koichi Kise
Title
Sleep Quality Tracking and Alignment with a Simple In-the-Wild Task
Journal
Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 International Symposium on Wearable Computers (UbiComp/ISWC '22 Adjunct)
Number of pages
3
Publisher
ACM
Location
Cambridge, UK
Reviewed
Reviewed
Presentation type
Poster
Date
September 2022
Research fields
Learning Analytics, Sensing
Key
Vargo2022_ISWCa (id=1889)
Abstract
The introduction of wearable sleep trackers, such as the Oura Ring, allow users to monitor the duration and quality of their sleep. For researchers in the fields of education and cognitive sciences, these wearables promise a new source of valuable data, especially if the wearables can be used outside of the laboratory. A problem in validating the wearable data for daily life is that it is difficult to give tasks which are both effective enough challenging users, but simple and quick enough that they can be completed by participants daily. In this poster, we present and in-the-wild study which employs a simple arithmetic task. The results indicate that sleep quality data from a wearable sleep trackers can be used to gauge performance.
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