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研究生: 陳盈如
Chen, Ying-Ju
論文名稱: 仿醫生操作之機械手臂電漿治療系統:傷口辨識、面積計算與使用者介面設計與評估
A Doctor-Mimicking Robot Arm Plasma Treatment System: Wound Segmentation, Area Measurement, and User Interface Design and Evaluation
指導教授: 廖峻德
Liao, Jiunn-Der
潘信誠
Pan, Shin-Chen
學位類別: 碩士
Master
系所名稱: 工學院 - 材料科學及工程學系
Department of Materials Science and Engineering
論文出版年: 2025
畢業學年度: 113
語文別: 中文
論文頁數: 127
中文關鍵詞: 非熱微電漿深度學習影像分割視覺型機械手臂使用者介面自動化治療
外文關鍵詞: Non-thermal micro-plasma, Deep learning, Image segmentation, Visual robot arm, User interface, Automated treatment
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  • 慢性傷口因其不易癒合且易感染的特性,對醫療體系與病患生活品質皆造成重大負擔。現行臨床多仰賴人工評估與手動操作進行治療,耗時費力且治療品質易受影響,顯示出自動化精準治療技術的需求。本研究針對此臨床困境,開發一套具人工智慧與自動控制能力的仿醫生操作之機械手臂電漿治療系統,整合非熱微電漿裝置(Gentle Plasma Skin Regenerator Model 2, GPSR_M2)、深度學習傷口辨識模型、深度相機三維掃描與面積計算,以及六軸機械手臂控制,實現全流程自動化治療作業。本研究所應用之非熱微電漿技術,具備低溫與活性氧氮物種特性,可有效促進傷口癒合且不產生熱傷害,為近年醫療應用研究焦點之一。相較於以往研究多著重於電漿治療或影像辨識單一面向,本研究整合上述多項技術,實現從傷口辨識、面積量測、到電漿治療的流程控制。系統採用U-Net深度學習模型進行影像分割,搭配深度相機與點雲處理演算法進行傷口面積估算。軟硬體整合架構方面,採取前後端分離架構建立直覺式使用者介面,並達成資料處理與機械手臂控制。六軸機械手臂搭載電漿裝置與深度相機,依據辨識結果執行傷口定位與治療作業。本研究進一步驗證系統的移動性能與安全性,包括電漿溫度、放射光譜、紫外線強度、以及機械手臂在負載條件下的移動精度與速度,皆符合相關規範或本研究所定義之標準。軟體系統亦展現良好效能與整合度,涵蓋深度學習模型訓練、即時影像處理與人機互動控制。綜上所述,本研究提出之仿醫生操作之機械手臂電漿治療系統為一具整合性與自動化潛力之創新平台,未來可望應用於臨床傷口照護流程中,進一步提升治療效率與品質。

    Chronic wounds, due to poor healing and high infection risk, strain healthcare systems and patients. Current treatments rely on manual assessment and operation, which are time-consuming and inconsistent—highlighting the need for automated, accurate solutions. To address this, this study developed a doctor-mimicking plasma treatment system integrating AI and automated treatment. The system combines two non-thermal micro-plasma devices (GPSR_M2), a deep learning wound recognition model, 3D scanning via a depth camera, and a six-axis robot arm, enabling full-process automation. The plasma produces low-temperature reactive species that promote healing without thermal damage, ideal for medical use. Unlike prior work focusing solely on plasma therapy or image analysis, our system performs wound segmentation, measurement, and treatment in an integrated workflow. A U-Net model was used for image segmentation, and point cloud algorithms for area measurement. The software adopts a frontend-backend structure enabling an intuitive user interface, real-time image processing, and robot control. The robot arm, with plasma devices and depth camera, executes wound localization and automated treatment based on segmentation results. System safety was confirmed through tests on plasma temperature, emission spectrum, UV intensity, and robotic accuracy, all meeting medical standards. The interface showed strong functionality and real-time responsiveness. In summary, this doctor-mimicking plasma system provides a compact, automated wound care solution that improves treatment quality.

    摘要 I Extended Abstract III 誌謝 XIV 目錄 XV 表目錄 XIX 圖目錄 XXI 1 第一章 緒論 1 1.1 前言 1 1.2 研究動機 3 2 第二章 理論基礎與文獻回顧 5 2.1 非熱微電漿 5 2.1.1 非熱微電漿的基本原理 5 2.1.2 非熱微電漿促進傷口癒合理論 7 2.1.3 非熱微電漿的安全規範 8 2.2 深度學習模型應用於傷口分割 9 2.2.1 深度學習的基本概念 9 2.2.2 U-Net模型的影像分割實例 10 2.3 基於三維掃描技術量測傷口面積 11 2.3.1 三維掃描技術量測傷口面積實例 11 2.3.2 傷口面積量測之使用者介面架設 12 2.4 視覺型機械手臂 13 2.4.1 視覺型機械手臂的基本原理 13 2.4.2 視覺型機械手臂的移動精度驗證 14 2.4.3 視覺型機械手臂於醫療領域的應用實例 15 2.5 研究目的 16 3 第三章 材料與方法 17 3.1 硬體設置 17 3.1.1 非熱微電漿裝置GPSR_M2 17 3.1.2 UFACTORY xArm 6機器手臂 18 3.1.3 Intel® RealSense™ Depth Camera D435i深度相機 19 3.1.4 Pernis W3電腦視訊鏡頭 20 3.2 深度學習模型訓練 21 3.2.1 資料收集 21 3.2.2 傷口標註 23 3.2.3 實作環境 24 3.2.4 影像分割 24 3.3 傷口面積計算 29 3.3.1 擬合點雲平面 29 3.3.2 計算空間多邊形面積 30 3.3.3 傷口面積計算之驗證工具 30 3.4 使用者介面與電漿治療流程之整合 31 3.4.1 電漿治療流程 31 3.4.2 建構電漿治療使用者介面 33 3.5 機械手臂負重移動精度與速度量測 34 3.5.1 機械手臂負重移動精度量測 34 3.5.2 機械手臂負重移動速度量測 37 3.6 電漿源量測 38 3.6.1 電漿源溫度量測 38 3.6.2 電漿源活性物種放射光譜分析 39 3.6.3 電漿源紫外光輻射強度量測 39 4 第四章 治療前安全性測試 41 4.1 機械手臂負重移動性能量測 41 4.1.1 機械手臂負重平面移動精度量測 41 4.1.2 機械手臂負重垂直移動精度量測 44 4.1.3 機械手臂負重移動速度量測 48 4.1.4 機械手臂負重移動性能討論 50 4.2 電漿源安全性量測 51 4.2.1 電漿源溫度量測 51 4.2.2 電漿源活性物種量測 52 4.2.3 電漿源紫外光量測 54 4.2.4 電漿源安全性討論 55 4.3 安全性測試綜合討論 55 5 第五章 仿醫生操作之機械手臂電漿治療系統 57 5.1 傷口分割模型訓練 57 5.1.1 訓練資料集 57 5.1.2 超參數訓練成效比較 58 5.1.3 有無預訓練成效比較 62 5.1.4 傷口分割模型訓練討論 64 5.2 傷口分割與面積計算驗證 64 5.2.1 測試用傷口影像分割 64 5.2.2 傷口假體影像分割 66 5.2.3 傷口假體面積計算 68 5.2.4 傷口分割與面積計算驗證討論 68 5.3 電漿治療使用者介面設計 69 5.3.1 使用者介面程式架構 69 5.3.2 使用者介面功能與流程設計 75 5.3.3 使用者介面功能驗證 81 5.3.4 電漿治療使用者介面討論 82 5.4 仿醫生操作之機械手臂電漿治療系統綜合討論 83 結論 84 未來展望 85 參考文獻 86 附錄 95

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