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Leveraging consumer activity trackers for accurate sleep stage prediction
https://ipsj.ixsq.nii.ac.jp/records/205413
https://ipsj.ixsq.nii.ac.jp/records/20541395a26371-ce9a-4bd6-a757-eca13ee514cd
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
IPSJ-Z82-2E-04.pdf (272.0 kB)
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Copyright (c) 2020 by the Information Processing Society of Japan
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| Item type | National Convention(1) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2020-02-20 | |||||||||
| タイトル | ||||||||||
| タイトル | Leveraging consumer activity trackers for accurate sleep stage prediction | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | ネットワーク | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||
| 資源タイプ | conference paper | |||||||||
| 著者所属 | ||||||||||
| 京都先端科学大 | ||||||||||
| 著者所属 | ||||||||||
| Silver Egg Technology | ||||||||||
| 著者名 |
Zilu, Liang
× Zilu, Liang
× Mario, Chapa-Martell
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| 論文抄録 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | Consumer activity trackers such as Fitbit have been increasingly used in longitudinal studies to track sleep patterns. However, these devices are known to be inaccurate especially for measuring sleep stages. In this study we propose a two-stage classification method to predict more accurate sleep stage data from Fitbit data. Support vector machine was used in stage-1 classification to predict whether a Fitbit measurement is correct, and XGBoost algorithm was used in stage-2 classification to correct predicted wrong measurements. The results showed that our method improved Cohen’s Kappa and Matthews correlation coefficient by up to 14.3% and 13.3% respectively. | |||||||||
| 書誌レコードID | ||||||||||
| 収録物識別子タイプ | NCID | |||||||||
| 収録物識別子 | AN00349328 | |||||||||
| 書誌情報 |
第82回全国大会講演論文集 巻 2020, 号 1, p. 17-18, 発行日 2020-02-20 |
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| 出版者 | ||||||||||
| 言語 | ja | |||||||||
| 出版者 | 情報処理学会 | |||||||||
