跳到主要內容

臺灣博碩士論文加值系統

(216.73.216.102) 您好!臺灣時間:2025/12/04 13:38
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:田晉瑋
研究生(外文):Chin-Wei Tien
論文名稱:以三通道EMG訊號控制3D列印之多軸電動機械義肢手
論文名稱(外文):The use of 3 channels EMG to control 3D printed and multi-axis electro-mechanical prosthetic hand
指導教授:程德勝
指導教授(外文):Tak-Shing Ching
口試委員:孫台平蕭進松
口試委員(外文):Tai-Ping SunChin-Sung Hsiao
口試日期:2018-07-16
學位類別:碩士
校院名稱:國立中興大學
系所名稱:生醫工程研究所
學門:工程學門
學類:生醫工程學類
論文種類:學術論文
論文出版年:2018
畢業學年度:106
語文別:中文
論文頁數:53
中文關鍵詞:3D列印多軸機電手臂
外文關鍵詞:3D printingmulti–axismyo prosthetics
相關次數:
  • 被引用被引用:0
  • 點閱點閱:287
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
肢體殘障一直是國內身心障礙者之中比率最高的類別,其中上肢殘疾更是職業災害傷殘的最大宗。隨著近年來機器人科技發展以及3D列印技術的便利與普及,機械化的功能性義肢因此被廣泛開發設計。
現今市售的肘下義肢只能做手掌的開關或預先設定好的常用動作,且擷取肌電訊號的電極數目最少需要10片,所能做到的自由度最多只有兩軸,對患者在訓練及實裝使用上仍有一定的不便。
故本研究設計並開發一三通道多軸3D列印機械手臂系統,整個系統包含訓練介面以及機械手臂義肢兩個架構,訓練介面以Labview建立完成,機械手臂義肢則會以3D列印的方式製作。本機械手臂利用模式切換的概念,在減少電極數量的同時維持手勢動作的數量,並以3D列印技術降低生產成本且提高生產速率,同時增加機械手臂活動的自由度,希望能夠提供患者更加人性化的義肢。
Upper limb disability has highest rate among the physical disabled people in the country. With the development of robotics and 3D printing technology in recent years, mechanized functional prostheses have been widely developed.
However, the below elbow prosthetic on the market can only control the palm or achieve the pre-set action. The most degrees of freedom is only six axes, including the five finger and thumb opposition. Also, they need at least 10 pieces of EMG electrodes to achieve the gesture movement. It will result the much longer time when user training. The six axes also will be inconvenience on some normal life movement.
Therefore, this research designed and developed a three-channel multi-axis 3D printing prosthetic system. This system consists of two parts: the training interface and the prosthetic arm. The training interface is built by Labview, and the prosthetic arm is made by 3D printer. Employ the idea of mode switching in this research, we can reduce the number of electrodes while maintaining the number of gestures. Our prosthetic also has two more degrees of freedom than other products. The 3D printing technology also helps reduce the time and money costs. Hope this research can provide much more humanized prosthetic to patients.
目錄
誌謝................................i
摘要................................ii
Abstract...............................iii
目錄................................iv
圖目錄...............................vii
表目錄...............................x
第一章 緒論...........................1
1.1 研究動機與目的......................1
1.2 研究論文架構.......................2
第二章 文獻回顧.........................3
2.1 EMG訊號........................3
2.1.1 前臂肌肉結構介紹.................3
2.1.2 前臂截肢介紹...................5
2.1.3 肌電訊號擷取...................6
2.1.4 EMG訊號特徵值.................6
2.2 前臂肌電義肢.......................7
2.2.1 前臂肌電義肢產品現況...............7
2.2.2 3D列印義肢之發展................11
第三章 材料與研究方法.....................12
3.1 硬體架構.........................12
3.1.1 EMG電路....................13
3.1.1.1 EMG電路架構與材料細項..........13
3.1.1.2 EMG電極貼片位置..............17
3.1.1.3 EMG電路評估................19
3.1.2 馬達控制電路...................19
3.1.2.1 馬達控制電路架構與材料細項.........19
3.1.2.2 馬達控制電路評估..............21
3.1.3 3D列印義肢手..................21
3.1.3.1 3D列印義肢手設計................21
3.1.3.2 3D列印義肢手評估................27
3.2 韌體程式.........................27
3.2.1 微處理器模組介紹................27
3.2.2 程式設計架構...................27
3.3 軟體介面.........................30
3.3.1 訓練系統程式架構................30
3.3.2 訓練系統評估...................31
第四章 結果與討論........................32
4.1 電路評估.........................32
4.1.1 EMG電路評估....................32
4.1.2 馬達控制電路評估................32
4.2 機電義肢手........................35
4.2.1 義肢手八軸自由度活動範圍............36
4.2.2 義肢手動作模式與手勢動作............37
4.2.2.1 自由模式...................37
4.2.2.2 工作模式...................38
4.2.2.3 手腕模式...................41
4.2.3 本義肢手與市售義肢比較 .............42
4.2.4 本義肢手硬體規格....................47
4.3 訓練系統.........................48
第五章 結論.............................50
5.1 結論........................50
5.2 未來展望........................50
第六章 參考文獻...........................52
[1]M.C. Lin, S.Y. Chen and et al. (2004, March). A Survey of Prosthesis Use Among Patients with Upper Limb Amputation. Formosan Journal of Medicine. 8(2), 190-198.
[2]T.W. Wright, A. D. Hagen and M.B. Wood. (1995, July). Prosthetic usage in major upper extremity amputations. The Journal of Hand Surgery. 20(4), 619-622.
[3]科技發展觀測平台。2017年4月。3D列印的醫療應用:仿生機械手。科技政策研究與資訊中心。取自:https://outlook.stpi.narl.org.tw。上網日期:2018/07/02。
[4]A.H. Al-Timemy, G. Bugmann and et al. (2013, May). Classification of Finger Movements for the Dexterous Hand Prosthesis Control with Surface Electromyography. IEEE Journal of biomedical and health informatics. 17(3), 608-618.
[5]R.E. McGovern. (2015, February). Introduction to Electromyography. American Journal of EEG Technology. 1(4), 93-100.
[6]W. Rose. (2014, July). Electromyogram analysis. Mathematics and Signal Processing for Biomechanics. KAAP686.
[7]Alila Medical Media. Available at: https://anatomyclass01.us/. Accessed July 02, 2018.
[8]S.G. Edwards. (2017, October). Wrist and Forearm Amputations. eMedicine Journal. 2(12).
[9]B. Geiger. (2015, May). 10 Laws Of Forearm Training. Available at: https://www.bodybuilding.com/forearmanatomy. Accessed July 02, 2018.
[10]M.B.I. Raez. (2006, March). Techniques of EMG signal analysis: detection, processing, classification and applications. Biol Proced Online. 8(163), 11-35.
[11]F.V. Tenore, A. Ramos and et al. (2009, May). Decoding of Individuated Finger MovementsUsing Surface Electromyography. IEEE Transactions on biomedical engineering, 56(5), 1427-1434.
[12]M. Hakonen, H. Piitulainen and A. Visala. (2015, April). Current state of digital signal processing in myoelectric interfaces and related applications. Biomedical Signal Processing and Control. 18, 334-359.
[13]S. Pizzolato, L. Tagliapietra and et al. (2017, April). Comparison of six electromyography acquisition setups on hand movement classification tasks. PLOS ONE. 12(10), 1-17.
[14]J.T. Belter, J.L. Segil, A.M. Dollar and et al. (2013). Mechanical design and performance specifications of anthropomorphic prosthetic hands: A review. Journal of Rehabilitation Research & Development (JRRD). 50(5), 599-618.
[15]薛漪平。2011。生理疾病職能治療學:I評估理論與技巧。禾楓書局。
[16]TheAverageBody.com. 2015. Average Hand Size. Available at: http://www.theaveragebody.com. Accessed July 02, 2018.
[17] MediaTek Labs (2017, May). LinkIt 7697 HDK v1.0 user's guide.
[18]Touch Bionics (2016, December). i-limb hand user manual.
[19]R.N. Khushaba, A. Al-Timemy, S. Kodagoda and et al. (2016, January). Combined influence of forearm orientation and muscular contraction on EMG pattern recognition Expert Systems with Applications. 61, 154-161.
[20]M. Atzori, A. Gijsberts, C. Castellini and et al. (2014, December). Electromyography data for noninvasive naturally-controlled robotic hand prostheses. Scientific Data. 1.
[21]M. Atzori, A. Gijsberts, I. Kuzborskij and et al. (2014, June) Characterization of a benchmark database for myoelectric movement classification. Neural Systems and Rehabilitation Engineering. 23, 73-83.
連結至畢業學校之論文網頁點我開啟連結
註: 此連結為研究生畢業學校所提供,不一定有電子全文可供下載,若連結有誤,請點選上方之〝勘誤回報〞功能,我們會盡快修正,謝謝!
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top