從人工智慧視野反思防跌AI模式之開發

Development of a Fall Prevention Model from the Perspective of Artificial Intelligence in Healthcare

柯雅婷(Ya-Ting Ke) ； 邱旅揚(Lu-Yang Chiu) ； 楊禮謙(Li-Chien Yang) ； 馬淑清(Shu-Ching Ma) ； 江惠英(Hui-Ying Chiang) ； 劉忠峰(Chung-Feng Liu) ； 王志中(Jhi-Joung Wang) ； 郭嘉琪(Chia-Chi Kuo)

《醫務管理期刊》 25卷1期 (2024/03) Pp. 66-80

https://doi.org/10.6174/JHM.202403_25(1).66

摘要

目的：探討預防跌倒導入人工智慧科技的現況，與「智慧防跌照明暨警示系統」於醫療院所之開發。方法：開發「智慧防跌照明暨警示系統」，含建構AI人體骨幹影像辨識演算模式、建立離床預警軟體判斷的流程，並將此AI防跌系統導入臨床進行前驅驗證。結果：完成「智慧防跌照明暨警示系統」建構，前驅驗證防跌燈偵測準確性可達90%。結論：運用AI離床警示偵測病人離床辨識為預防跌倒之創舉，AI技術應用於臨床照護環境為未來之發展趨勢，然而AI技術不斷持續演進，實際運用於複雜的臨床照護環境之持續驗證與準確率仍需努力。

關鍵字

床邊跌倒 ； 智慧防跌系統 ； 人工智慧

並列摘要

Objectives: To examine the current state of fall prevention by the integration artificial intelligence (AI) technology and deploying "intelligent fall prevention lighting and alert systems in healthcare settings." Methods: This study developed an AI algorithm for human skeletal image recognition and established a workflow for bed-exit alert software, which was thereafter incorporated into a holistic AI-based fall prevention framework for clinical validation. Results: The project successfully developed an AI algorithm for human skeletal image recognition and established a workflow for the bed-exit warning software. The preliminary validation of the fall prevention lighting system achieved a detection accuracy rate of up to 90%. Conclusions: The application of AI to bed-exit alerts and patient recognition is an innovative step toward fall prevention strategies. The use of AI technology in clinical care settings is an anticipated future trend with the potential to improve the quality of care. However, as AI technology rapidly evolves, the continuous validation and enhancement of accuracy in complex clinical care environments remain challenging and require ongoing effort.

並列關鍵字

Bedside Falls ； Intelligent Fall Prevention System ； Artificial Intelligence

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