研究生: |
蘇昶瑋 Chung-Wei Su |
---|---|
論文名稱: |
承重跑步機訓練之下肢外骨骼復健機器人機械設計與實現 Mechanical Design and implementation of a Lower-limb Exoskeleton Robot for Body-weight Support Treadmill Training |
指導教授: |
郭重顯
Chung-Hsien Kuo |
口試委員: |
黃漢邦
Han-Pang Huang 蘇順豐 Shun-Feng Su 李明義 Ming-Yi Lee 彭昭暐 Jau-Woei Perng |
學位類別: |
碩士 Master |
系所名稱: |
應用科技學院 - 醫學工程研究所 Graduate Institute of Biomedical Engineering |
論文出版年: | 2015 |
畢業學年度: | 103 |
語文別: | 中文 |
論文頁數: | 60 |
中文關鍵詞: | 外骨骼 、下肢復健機器人 、跑步機復健系統 、步態訓練系統 、復健懸吊系統。 |
外文關鍵詞: | Gait Training, Body Support, Suspension System, Exoskeleton, Lower Limb Rehabilitation System |
相關次數: | 點閱:429 下載:0 |
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外骨骼復健系統於近幾年來由於臨床成效以及機器人技術發展的快速進步,廣泛的被大眾討論,一套復健外骨骼機器人系統包含復健外骨骼機器人、承重系統、復健跑步機以及步態控制器,本論文中下肢復健外骨骼機器人之機構設計與實現,用來醫院及照護中心做為復健步態的訓練,本文所提出的外骨骼復建機器人為具有六個自由度的連桿系統,可以控制雙腳髖關節、膝關節及踝關節,除此之外,一套承重系統的機構結合步態控制器、復健外骨骼機器人與跑步機共同組成的系統,來產生復健訓練步態軌跡,以微控制器所開發之步態軌跡控制器來做為逆向運動學(Inverse kinematics)為基礎的軌跡功能來做測試,機器人與已經於本實驗室完成開發並實現,為了驗證,本文以三種逆向運動學的軌跡來做測試,本系統可以成功達成逆運動學之步態訓練。
Exoskeleton rehabilitation systems are widely discussed in recent years because of their clinical effectiveness and the advances of robotic technologies. An exoskeleton rehabilitation system is composed an exoskeleton rehabilitation robot, a body-weight support system, a power treadmill and a locomotion controller. In this thesis, the mechanical design and fabrication of a lower-limb exoskeleton rehabilitation robot is developed for locomotor training in hospitals and healthcare centers. The exoskeleton rehabilitation robot is configured as a 6 degrees-of-freedom linkage, and it is capable of controlling bilateral joints of hips, knees and ankles. In addition, a body-weight support mechanism was also developed to work with the exoskeleton rehabilitation robot and a power treadmill to perform locomotor training trajectories. Moreover, a microcontroller-based locomotor training trajectory controller was also implemented for functional tests based on inverse kinematics (IK) based trajectories. Finally, the aforementioned mechanical and control system have been fabricated in the laboratory. Several inverse kinematics based trajectories have been examined, and the system is capable of performing IK-based locomotor training trajectories.
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