WEKO3
アイテム
Recognizing Nursing Activities in Endotracheal Suction: Utilizing Multiple Readouts Reservoir Computing and Large Language Models
http://hdl.handle.net/10228/0002001224
http://hdl.handle.net/10228/000200122453c4ccfe-f875-4418-8dd4-c3d58a0afada
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
10434288.pdf (1.4 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 | 2025-02-04 | |||||||||||||||
| タイトル | ||||||||||||||||
| タイトル | Recognizing Nursing Activities in Endotracheal Suction: Utilizing Multiple Readouts Reservoir Computing and Large Language Models | |||||||||||||||
| 言語 | en | |||||||||||||||
| 著者 |
Rachmad Syulistyo, Arie
× Rachmad Syulistyo, Arie
× 田中, 悠一朗
WEKO
30537
× 田向, 権
WEKO
6059
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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. | |||||||||||||||
| 抄録 | ||||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||||
| 内容記述 | Identifying nursing activity during critical procedures, such as endotracheal suction (ES), is crucial for ensuring patient safety and the quality of received treatment. The expansion of home care requires an increase in the number of certified professionals who can perform endotracheal procedures and provide monitoring during these activities. To fulfill these needs, this study aims to develop an algorithm that is able to recognize ES activities that have the potential to be implemented on edge devices and perform real-time processing of nurse’s pose keypoint extracted from the video using YOLOv7, which is represented in x and y coordinates. The edge device implementation is crucial for health care for ensuring security and privacy, and reducing cost network congestion and latency. In this study, we introduce a combination of a reservoir computing (RC)-based recognition model and large language models (LLMs) to identify nursing activities related to endotracheal suction. RC is suitable for edge device implementation because of its low computational cost requirement and processes temporal features necessary for recognizing nursing activity in real-time. To enhance the performance of RC, we introduce a reservoir computing model with multiple readouts for the recognition model, called RCMRO. The proposed model, which uses LLMs to analyze keypoint data and generate synthetic training data to improve the performance of RCMRO, shows promising performance in distinguishing between various nursing activities. This tool provided healthcare professionals with a prospective method to monitor and evaluate nursing activity in real-time and achieved an accuracy of 70.5% and an F1 score of 68.1% when evaluated by using a test dataset. | |||||||||||||||
| 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, 発行日 2024-06-27 |
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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 | |||||||||||||||
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| 言語 | jpn | |||||||||||||||
| 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.30 | |||||||||||||||
| 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 | 28 | |||||||||||||||
| 開催国 | JPN | |||||||||||||||
| 研究者情報 | ||||||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/100001426_ja.html | |||||||||||||||
| 研究者情報 | ||||||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/100000641_ja.html | |||||||||||||||
| 論文ID（連携） | ||||||||||||||||
| 値 | 10434288 | |||||||||||||||
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| 値 | 12292 | |||||||||||||||
