WEKO3
アイテム
Improving Fatigue Detection with Feature Engineering on Physical Activity Accelerometer Data Using Large Language Models
http://hdl.handle.net/10228/0002001239
http://hdl.handle.net/10228/000200123956e9ea0f-8a61-478e-9500-c9f04dedfe03
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
10444554.pdf (1.1 MB)
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| アイテムタイプ | 共通アイテムタイプ(1) | |||||||||||
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| 公開日 | 2025-02-05 | |||||||||||
| タイトル | ||||||||||||
| タイトル | Improving Fatigue Detection with Feature Engineering on Physical Activity Accelerometer Data Using Large Language Models | |||||||||||
| 言語 | en | |||||||||||
| 著者 |
Elsen Ronando,
× Elsen Ronando,
× 井上, 創造
WEKO
27425
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| 著作権関連情報 | ||||||||||||
| 権利情報 | Copyright (c) 2024 Author. | |||||||||||
| 著作権関連情報 | ||||||||||||
| 権利情報Resource | https://creativecommons.org/licenses/by/4.0/deed.ja | |||||||||||
| 権利情報 | This article is licensed under a Creative Commons Attribution 4.0 International License. https://creativecommons.org/licenses/by/4.0/deed.ja | |||||||||||
| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | In this paper, we improve the classification performance of fatigue detection on physical activity using Large Language Models (LLMs). Fatigue is a critical reminder of a person’s health condition. Currently, studies on fatigue detection solely focus on sensor data to measure body condition. However, changing sensor data for more meaningful inference and improving fatigue detection performance needed to be developed. In this study, we implement LLMs for fatigue detection in physical activity. We use LLMs in the preprocessing steps to generate meaningful features that can improve classification performance. For evaluation, we study the prompt design of LLMs to investigate their effect on improving machine learning performance, and compare evaluation metrics between traditional machine learning and LLMs-based machine learning. Using LLMs, our proposed model achieves better performance for fatigue detection, especially in physical activity, with performance improvement of 2% minimum and 4.5% maximum. | |||||||||||
| 言語 | en | |||||||||||
| 備考 | ||||||||||||
| 内容記述タイプ | Other | |||||||||||
| 内容記述 | 6th International Conference on Activity and Behavior Computing, ABC2024, May 28-31, 2024, Nakatsu and Kitakyushu, Kyushu, Japan (Hybrid) | |||||||||||
| 言語 | en | |||||||||||
| 書誌情報 |
en : International Journal of Activity and Behavior Computing 巻 2024, 号 2, p. 1-22, 発行日 2024-06-13 |
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| 出版社 | ||||||||||||
| 出版者 | 九州工業大学ケアXDXセンター | |||||||||||
| 言語 | ja | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||
| 資源タイプ | journal article | |||||||||||
| 出版タイプ | ||||||||||||
| 出版タイプ | VoR | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||
| DOI | ||||||||||||
| 識別子タイプ | DOI | |||||||||||
| 関連識別子 | https://doi.org/10.60401/ijabc.18 | |||||||||||
| ISSN | ||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||
| 収録物識別子 | 2759-2871 | |||||||||||
| 会議記述 | ||||||||||||
| 会議名 | 6th International Conference on Activity and Behavior Computing, ABC2024 | |||||||||||
| 言語 | en | |||||||||||
| 回次 | 6 | |||||||||||
| 開始年 | 2024 | |||||||||||
| 開始月 | 05 | |||||||||||
| 開始日 | 28 | |||||||||||
| 終了年 | 2024 | |||||||||||
| 終了月 | 05 | |||||||||||
| 終了日 | 31 | |||||||||||
| 開催国 | JPN | |||||||||||
| 研究者情報 | ||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/140_ja.html | |||||||||||
| 論文ID（連携） | ||||||||||||
| 値 | 10444554 | |||||||||||
| 連携ID | ||||||||||||
| 値 | 12695 | |||||||||||
