請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73156
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 趙福杉 | |
dc.contributor.author | Bing-Xiu Yang | en |
dc.contributor.author | 楊秉修 | zh_TW |
dc.date.accessioned | 2021-06-17T07:20:02Z | - |
dc.date.available | 2020-07-23 | |
dc.date.copyright | 2019-07-23 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-07-08 | |
dc.identifier.citation | 1.衛生福利部, “長期照顧十年計劃2.0,” 2017.
2.日本厚生省, “國民生活基礎調查,” 2013. 3.台中榮總腦中風中心, “腦中風病人的處置及照護,” 2013. 4.衛生福利部統計處, “105年身心障礙者生活狀況及需求調查報告,” 2016. 5.衛生福利部中央健康保險署指標說明, “缺血性或出血性中風病人住院期間或出院後四個月內接受復健服務比率”. 6.台大醫院復健部, “臺灣腦中風復健治療指引,” 臺灣復健醫誌, 第44卷, 1期, pp. 1-9, 2016. 7.M. A. Dimyan, and L. G. Cohen, “Neuroplasticity in the context of motor rehabilitation after stroke,” Nature Reviews Neurology7.2, p. 76, 2011. 8.Y. N. Wu, M. Hwang, Y. Ren, G. S. Deborah, and L. Q. Zhang, “Combined passive stretching and active movement rehabilitation of lower-limb impairments in children with cerebral palsy using a portable robot,” Neurorehabilitation and neural repair, vol. 25, pp. 378-385, 2011. 9.hocoma http://www.hocoma.com/. 10.H. H. Kuo, “Programmable rehabilitation system for lower limb motion,” M.S. thesis, National Taiwan University, Taipei, 2017. 11.J. Watkins, Series Editor, and I. Mathieson, The Pocket Podiatry Guide: Functional Anatomy, 2009. 12.Optimal Design Lab, “壓力感測元件簡介,” Yuan Ze University, Taoyuan, 2000. 13.V. A. Stavric, and P. J. McNair, “Optimizing muscle power after stroke: a cross-sectional study,” Journal of neuroengineering and rehabilitation 9.1, p. 67, 2012. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73156 | - |
dc.description.abstract | 人口高齡化是目前台灣面臨的重要問題,而其所導致的失能人口增加更是造成社會負擔的主因。失能人口中又以中風居多,占了兩成以上,透過復健治療可以有效改善中風患者的生活機能並降低社會負擔。針對中風後導致的下肢偏癱患者,主要有三種下肢復健模式,分別為被動復健、主動助力復健及主動阻力復健。治療師會根據患者狀況從被動復健治療一路變成主動阻力治療,以改善患者狀況。由本實驗室郭星晧學長所開發之可程式下肢動作復健系統以躺姿的方式協助患者完成被動復健,然其缺乏主動復健之功能,而主動復健為改善患者恢復的重要因素。
本研究以郭星晧學長之第一代下肢復健裝置為基礎,透過力量回饋方式完成主動復健之功能。藉由感測患者進行下肢運動時,伸腳及抬腳動作所施的力,提供系統所需資訊,以此調整系統施予不同程度的助力及阻力給患者,達成主動復健療程。 本研究目前完成一下肢復健之智能系統軟體及硬體架構,透過自製電路板控制要進行的復健模式及得到所需之資訊,其力量感測器已校正且可順利量測使用者在使用此系統時的力量,並且自動調整系統之施力,以完成預定之復健模式。 | zh_TW |
dc.description.abstract | The aging of the population is an important issue in Taiwan, and then ,the increase in disabled population is a huge burden. Among the disables, strokes are the largest proportion, accounting for more than 20%. Through rehabilitation treatment, we can effectively improve the living quality of stroke patients. To treat stroke patients with hemiplegia, there are three types of lower limb rehabilitation modes: passive rehabilitation, active assisted rehabilitation and active resisted rehabilitation. The therapist will change from passive rehabilitation to active resisted rehabilitation based on the patient's condition. The programmable rehabilitation system for lower limb motion developed by Kuo assists patients in passive rehabilitation in a lying position, However, it lacks the function of active rehabilitation. The active rehabilitation is an important mode for patients recovery.
Based on the Kuo’s system, this study implemented the function of active rehabilitation by force feedback. By sensing the force exerted from the patient during the lower limb movement, the necessary information is input to the system, thereby the system adjusting different degrees of assistance or resistance to the patient to complete the active rehabilitation treatment. This study is currently built in with the intelligent system software for lower limb rehabilitation, through the home-made circuit to control the rehabilitation mode and get the essential information. The force sensors have been calibrated and it can measure the force of the user, and then automatically adjust the system to apply the force to complete the predetermined rehabilitation mode. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T07:20:02Z (GMT). No. of bitstreams: 1 ntu-108-R06548050-1.pdf: 2725713 bytes, checksum: 7334b623c78ef04014c3d402500221aa (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | 口試委員會審定書 #
誌謝 i 中文摘要 ii ABSTRACT iii CONTENTS v LIST OF FIGURES vii LIST OF TABLES ix Chapter 1 簡介 1 Chapter 2 研究方法與系統設計 5 2.1 復健裝置系統架構 7 2.1.1 力量感測器元件 8 2.1.2 感測器訊號調適 11 2.1.3 電源供應器 13 2.2 復健裝置機械架構 14 2.3 復健模式 16 2.4 控制器單元 17 2.5 馬達驅動器 22 2.6 脈衝寬度調變(PWM) 23 2.7 系統校正 24 Chapter 3 研究結果 25 3.1 控制器單元 25 3.2 必要訊息顯示介面 26 3.3 機械架構 27 3.4 訊號調適 30 3.4.1 力敏電阻訊號調適電路 30 3.4.2 電源供應器 31 3.5 系統校正 32 3.5.1 力敏電阻校正 32 3.5.2 荷重元校正 32 3.6 牽引速度 34 3.7 系統比較 35 Chapter 4 討論 36 4.1 下肢復健之智能系統軟硬體設計討論 36 4.2 牽引速度誤差 36 4.3 復健模式討論 37 Chapter 5 結論與建議 38 REFERENCE 39 | |
dc.language.iso | zh-TW | |
dc.title | 下肢復健之智能系統 | zh_TW |
dc.title | Intelligent system for lower limb rehabilitation | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 陳右穎,謝建興,鄭國順 | |
dc.subject.keyword | 中風,下肢復健,力量回饋,主動復健,智能系統, | zh_TW |
dc.subject.keyword | stroke,lower limb rehabilitation,force feedback,active rehabilitation,intelligent system, | en |
dc.relation.page | 40 | |
dc.identifier.doi | 10.6342/NTU201901281 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-07-08 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 醫學工程學研究所 | zh_TW |
顯示於系所單位: | 醫學工程學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-108-1.pdf 目前未授權公開取用 | 2.66 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。