文献の詳細

論文の言語	英語
著者	Andrew W. Vargo, Masayuki Fujimoto, Koichi Kise
論文名	Sleep Quality Tracking and Alignment with a Simple In-the-Wild Task
論文誌名	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)
ページ数	3 pages
出版社	ACM
発表場所	Cambridge, UK
査読の有無	有
発表の種類	ポスター発表
年月	2022年9月
要約	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.

• BibTeX用エントリー

  @InProceedings{Vargo2022,
    author =	{Andrew W. Vargo and Masayuki Fujimoto and Koichi Kise},
    title =	{Sleep Quality Tracking and Alignment with a Simple In-the-Wild Task},
    booktitle =	{Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 International Symposium on Wearable Computers (UbiComp/ISWC \&\#39;22 Adjunct)},
    year =	2022,
    month =	sep,
    numpages =	{3},
    publisher =	{ACM},
    location =	{Cambridge, UK}
  }
  
  
  

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