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研究生: 林元亨
LIN, Yuan-Heng
論文名稱: 針對長照機構之E化護理輔助車與數據監控系統
E-Clinical Cart and Data Monitoring System for Long Term Care Institutions
指導教授: 王偉彥
Wang, Wei-Yen
口試委員: 蘇順豐
Su, Shun-Feng
呂成凱
Lu, Cheang-Kai
王偉彥
Wang, Wei-Yen
口試日期: 2023/07/11
學位類別: 碩士
Master
系所名稱: 電機工程學系
Department of Electrical Engineering
論文出版年: 2023
畢業學年度: 111
語文別: 中文
論文頁數: 65
中文關鍵詞: E化護理輔助車數據監測系統即時人體動作辨識長期照護機構
英文關鍵詞: E-clinical cart, data monitoring system, real-time human action recognition, long-term care institutions
DOI URL: http://doi.org/10.6345/NTNU202301314
論文種類: 學術論文
相關次數: 點閱:139下載:0
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  • 本篇論文中,主要是應用人工智慧物聯網技術實現長期照護機構的自動異常事件檢測和E化護理輔助車資訊系統。E化護理輔助車可以跟隨醫護人員,以此減輕手動推動護理車的體力負擔。對於自主巡邏工作,使用小樣本學習之人體動作辨識,可以檢測到一些異常動作,例如:跌倒和蹲下。此外,本篇論文所提出的自動監控平台系統可以提高護理工作的質量和效率。根據實驗結果顯示,本智慧數據監測系統可以有效地執行E化護理輔助車的任務分配以及長期照護機構中的事件監測和警示。

    In this thesis, we apply AIoT technologies to implement automatic abnormal event detection and E-clinical cart information systems for long-term care institutions. The E-clinical cart can follow medical personnel, and therefore it eases the physical workload of manually pushing the clinical cart. For autonomous patrol work, using the human action recognition with few-shot data, some abnormal actions, such as falls and squats, can be detected. Moreover, the proposed monitoring platform with a graphical user interface can improve the E-quality and efficiency of nursing works. The experimental results show that the intelligent data monitoring system can effectively carry out the task assignment of the E-clinical cart and event monitoring and warning in long-term care institutions.

    誌  謝 i 摘  要 ii ABSTRACT iii 目  錄 iv 表 目 錄 vii 圖 目 錄 viii 第一章 緒論 1 1.1 研究背景與動機 1 1.2 論文架構 3 第二章 文獻探討 4 2.1 E 化護理輔助車 4 2.2 自動監控平台 5 2.3 人體動作辨識 6 第三章 護理輔助車硬體架構與設計 11 3.1 整體硬體架構 11 3.2 移動載具 12 3.3 控制核心 16 3.4 通訊設備 17 3.5 電源供應 20 3.6 深度攝影機 20 第四章 具AI巡視與監控之遠端管理平台 22 4.1 通訊架構介紹 23 4.1.1 ROS通訊架構 23 4.1.2 MQTT通訊架構 25 4.1.3 Socket通訊架構 26 4.2 Qt架構介紹 27 4.3 護理輔助工作車之遠端移動控制 28 4.4 警示系統 30 4.4.1 無線式呼叫系統 30 4.4.2 機器人錯誤警報 32 4.4.3 室內環境巡邏異常警報 33 4.5 移動式監控影像和定位顯示 33 第五章 實驗結果 35 5.1 人體動作辨識實驗 35 5.1.1 錄製人體動作資料集 36 5.1.2 聚類分析結合合併式模糊類神經網路之訓練和分析 38 5.2 實驗場域介紹 41 5.2.1 實驗場域一 42 5.2.2 實驗場域二 44 5.3 護理輔助車之人員跟隨與物品運送 47 5.3.1 護理輔助車之人員跟隨與物品運系統架構 47 5.3.2 音檔撥放系統 48 5.3.3 護理輔助車之人員跟隨與物品運送系統驗證 49 5.4 護理輔助車之夜間巡房服務 53 5.4.1 護理輔助車之夜間巡房服務系統架構 53 5.4.2 人體動作辨識與夜間巡房系統 54 5.4.3 護理輔助車之夜間巡房服務系統驗證 55 第六章 結論與未來展望 59 6.1 結論 59 6.2 未來展望 59 參考文獻 61 自  傳 64 學術成就 65

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