Sleep Quality Tracking and Alignment with a Simple In-the-Wild Task
| 言語 | 英語 |
|---|---|
| 種類 | 国際会議等の予稿 |
| 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 |
| 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 |
| 分野 | 学習解析, センシング |
| キー | Vargo2022_ISWCa (id=1889) |
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.
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