請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73890
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 林達德(Ta-Te Lin) | |
dc.contributor.author | Chi-Fan Hsu | en |
dc.contributor.author | 徐啟凡 | zh_TW |
dc.date.accessioned | 2021-06-17T08:12:56Z | - |
dc.date.available | 2019-08-20 | |
dc.date.copyright | 2019-08-20 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-08-14 | |
dc.identifier.citation | 何柏融。2017。輔助型下肢外骨骼機器人控制系統之研究。碩士論文。台北:台灣大學生物產業機電工程學系。
張家瑋。2015。輔助行走下肢外骨骼機器人之設計。碩士論文。台北:台灣大學生物產業機電工程學系。 葉文裕、林彥輝。1997。工作現場人因工程檢核表示用性之研究,行政院勞工委員會勞工安全衛生研究所。 ISOH86-H329。 陳志勇、劉立文、潘儀聰、游志雲、陳協慶。2014。人因工程肌肉骨骼傷病預防指引。台北:勞動部勞動及職業安全衛生研究所。 李恆儒、徐瑋勵、楊秉祥。2011。生物力學¬¬¬¬—臨床與研究的應用。初版,20。台灣:愛思唯爾。 Ahmad, N., Ghazilla, R. A. R., Khairi, N. M., & Kasi, V. (2013). Reviews on various inertial measurement unit (IMU) sensor applications. International Journal of Signal Processing Systems. 1(2): 256-262. Anam, K., & Al-Jumaily, A. A. (2012). Active exoskeleton control systems: State of the art. Procedia Engineering. 41: 988-994. Ansari, N. A., & Sheikh, M. J. (2014). Evaluation of work Posture by RULA and REBA: A Case Study. IOSR Journal of Mechanical and Civil Engineering. 11(4): 18-23. Chen, J., Ahn, C. R., & Han, S. (2014). Detecting the hazards of lifting and carrying in construction through a coupled 3D sensing and IMUs sensing system. In Computing in Civil and Building Engineering. 1110-1117. Dahmen, C., Hölzel, C., Wöllecke, F., & Constantinescu, C. (2018). Approach of Optimized Planning Process for Exoskeleton Centered Workplace Design. Procedia CIRP. 72: 1277-1282. David, G. C. (2005). Ergonomic methods for assessing exposure to risk factors for work-related musculoskeletal disorders. Occupational medicine. 55(3): 190-199. Dollar, A. M., & Herr, H. (2008). Lower extremity exoskeletons and active orthoses: challenges and state-of-the-art. IEEE Transactions on robotics. 24(1): 144-158. Doulah, A. S. U., Iqbal, M. A., & Jumana, M. A. (2012). ALS disease detection in EMG using time-frequency method. In 2012 International Conference on Informatics, Electronics & Vision (ICIEV), IEEE. 648-651. dos Reis, D. C., Ramos, E., Reis, P. F., Hembecker, P. K., Gontijo, L. A., & Moro, A. R. P. (2015). Assessment of risk factors of upper-limb musculoskeletal disorders in poultry slaughterhouse. Procedia Manufacturing. 3: 4309-4314. Education, P. (2015). Ergonomics evaluation of a packaging workstation in an electric supplies industry. In Proceedings 19th Triennial Congress of the IEA. 9: 14. Fazi, H. M., Mohamed, N. M. Z. N., Ab Rashid, M. F. F., & Rose, A. N. M. (2017). Ergonomics study for workers at food production industry. In MATEC Web of Conferences, EDP Sciences. 90: 01003. Gandavadi, A., Ramsay, J. R. E., & Burke, F. J. T. (2007). Assessment of dental student posture in two seating conditions using RULA methodology–a pilot study. British dental journal. 203(10): 601. Hedge, A. (2000). RULA employee assessment worksheet. Cornell University. Hignett, S., & McAtamney, L. (2000). Rapid entire body assessment (REBA). Applied ergonomics. 31(2): 201-205. Karhu, O., Härkönen, R., Sorvali, P., & Vepsäläinen, P. (1981). Observing working postures in industry: Examples of OWAS application. Applied Ergonomics. 12(1): 13-17. Karhu, O., Kansi, P., & Kuorinka, I. (1977). Correcting working postures in industry: a practical method for analysis. Applied ergonomics. 8(4): 199-201. Klussmann, A., Steinberg, U., Liebers, F., Gebhardt, H., & Rieger, M. A. (2010). The Key Indicator Method for Manual Handling Operations (KIM-MHO)-evaluation of a new method for the assessment of working conditions within a cross-sectional study. BMC musculoskeletal disorders. 11(1): 272. Ko, H. K., Lee, S. W., Koo, D. H., Lee, I., & Hyun, D. J. (2018). Waist-assistive exoskeleton powered by a singular actuation mechanism for prevention of back-injury. Robotics and Autonomous Systems. 107: 1-9. Lasota, A. M. (2014). A REBA-based analysis of packers workload: a case study. LogForum. 10(1). Li, P., Meziane, R., Otis, M. J. D., Ezzaidi, H., & Cardou, P. (2014). A Smart Safety Helmet using IMU and EEG sensors for worker fatigue detection. In 2014 IEEE International Symposium on Robotic and Sensors Environments (ROSE) Proceedings. 55-60. LPMS-B2 IMU and its structure. Tokyo, Japan: LP-RESEARCH. Retrieved from: https://www.lp-research.com/lpms-b2/ Martin, C. C., Burkert, D. C., Choi, K. R., Wieczorek, N. B., McGregor, P. M., Herrmann, R. A., & Beling, P. A. (2012, April). A real-time ergonomic monitoring system using the Microsoft Kinect. In 2012 IEEE Systems and Information Engineering Design Symposium. 50-55 McAtamney, L., & Corlett, E. N. (2004). Rapid Upper limb assessment (RULA) in Stanton. N. et al.(eds.) Handbook of Human Factors and Ergonomics Methods. 7. McAtamney, L., & Corlett, E. N. (1993). RULA: a survey method for the investigation of work-related upper limb disorders. Applied ergonomics. 24(2): 91-99. Mohamad, D., Md Deros, B., Ismail, A. R., Daruis, D. D. I., & Sukadarin, E. H. (2013). RULA analysis of work-related disorder among packaging industry worker using digital human modeling (DHM). In Advanced Engineering Forum. Trans Tech Publications. 10:9-15. Norhidayah, M. S., Mohamed, N. M. Z. N., Mansor, M. A., & Ismail, A. R. (2016). RULA: Postural loading assessment tools for Malaysia mining industry. Journal of Engineering Science and Technology. 11: 1-8. Petriková, A., & Petrik, M. (2015). Modern methods of evaluation workplace factors in ergonomy. Acta Simulatio. 1(3): 7-11. Rissanen, S., Kankaanpää, M., Tarvainen, M. P., Nuutinen, J., Tarkka, I. M., Airaksinen, O., & Karjalainen, P. A. (2007). Analysis of surface EMG signal morphology in Parkinson's disease. Physiological measurement. 28(12): 1507. Scott, G. B., & Lambe, N. R. (1996). Working practices in a perchery system, using the OVAKO Working posture Analysing System (OWAS). Applied Ergonomics. 27(4): 281-284. Shair, E. F., Ahmad, S. A., Marhaban, M. H., Mohd Tamrin, S. B., & Abdullah, A. R. (2017). EMG processing based measures of fatigue assessment during manual lifting. BioMed research international. Sharan, D., & Ajeesh, P. S. (2012). Correlation of ergonomic risk factors with RULA in IT professionals from India. Work. 41(1): 512-515. Singh, J., Lal, H., & Kocher, G. (2012). Musculoskeletal disorder risk assessment in small scale forging industry by using RULA method. International Journal of Engineering and Advanced Technology. 1(5): 513-518. Singh, T., & Singh, J. (2014). Review on Ergonomic Evaluation of Industrial tasks in Indian Manufacturing Industries. International Journal of Science and Research. 3(6): 295-300. Steger, R., Kim, S. H., & Kazerooni, H. (2006). Control scheme and networked control architecture for the Berkeley lower extremity exoskeleton (BLEEX). In ICRA 2006. 3469-3476. Stephens, J. A., & Taylor, A. (1972). Fatigue of maintained voluntary muscle contraction in man. The Journal of physiology. 220(1): 1-18. Sukkarieh, S., Nebot, E. M., & Durrant-Whyte, H. F. (1999). A high integrity IMU/GPS navigation loop for autonomous land vehicle applications. IEEE Transactions on Robotics and Automation.15(3): 572-578. Tee, K. S., Low, E., Saim, H., Zakaria, W. N. W., Khialdin, S. B. M., Isa, H., ... & Soon, C. F. (2017). A study on the ergonomic assessment in the workplace. In AIP Conference Proceedings. 1883(1): 020034. Vignais, N., Miezal, M., Bleser, G., Mura, K., Gorecky, D., & Marin, F. (2013). Innovative system for real-time ergonomic feedback in industrial manufacturing. Applied ergonomics. 44(4): 566-574. Yan, X., Li, H., Li, A. R., & Zhang, H. (2017). Wearable IMU-based real-time motion warning system for construction workers' musculoskeletal disorders prevention. Automation in Construction. 74: 2-11. Yang, S., & Li, Q. (2012). Inertial sensor-based methods in walking speed estimation: A systematic review. Sensors. 12(5): 6102-6116. Zhu, R., & Zhou, Z. (2004). A real-time articulated human motion tracking using tri-axis inertial/magnetic sensors package. IEEE Transactions on Neural systems and rehabilitation engineering. 12(2): 295-302. Zoss, A., Kazerooni, H., & Chu, A. (2005). On the mechanical design of the Berkeley Lower Extremity Exoskeleton (BLEEX). In 2005 IEEE/RSJ international conference on intelligent robots and systems. 3465-3472. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73890 | - |
dc.description.abstract | 近年來,人們開始更多地關注不同工作領域的人體工學相關議題,特別在大多數工作會引起不適或效率下降的農業場所。重複和密集的腰部運動常常可能導致背部受傷,這是由於農業機具操作引起較為常見的併發症。本研究提出了一種系統,結合了慣性測量單元(IMU)和外骨骼機器人的使用來即時評估人體工學風險並可在多項工作中協助工人進行操作。本系統基於其重量、耐用性、便利性和成本進行了優化,通過在受試者的軀幹和大腿上放置三顆IMU,藉由IMU來控制外骨骼機器人移動穿戴者的腿,並同時支撐他們的背部。在為配戴者提供的工作輔助時,同時使用了人體工學評估方法量測,例如快速上肢評估(RULA)、快速全身評估 (REBA)和肌電圖(EMG)。在我們的研究中,通過使用我們建造的外骨骼,在彎腰抬起動作時豎脊肌活動平均減少約21.62%,在半蹲抬起時減少22.53%;而股二頭肌的肌肉活動對於與上述相同的任務,分別下降6.775%和18.51%。本研究所開發之外骨骼機器人降低穿戴者的發生肌肉骨骼傷病之風險,並且可延緩大約兩成疲勞產生的時間,能實際讓受試者穿戴在農業場域進行應用,真正能幫助農業工作者進行勞務相關工作。這項工作不僅適用於農業任務,也適用於物流人員、建築工作和其他相關工作領域。 | zh_TW |
dc.description.abstract | In recent years, people have started to pay more attention to ergonomics in different fields of work, especially in agricultural workplaces in which most tasks cause discomfort or a decline in work efficiency. In particular, repeated and intensive waist motions may lead to back injuries, which is a very common complication caused by agricultural operations. This study proposes a system that combines the usage of inertial measurement units (IMUs) and an exoskeleton robot to automatically assess work performance and assist workers while performing several agricultural tasks. The system was optimized based on its weight, endurance, convenience, and cost. By placing three IMUs on the subject’s trunk and legs, the system is able to control the exoskeleton robot to move the wearers’ legs while supporting their backs. In order to evaluate the waist assistance provided by the system, ergonomic assessment tests were used, such as Rapid Upper Limb Assessment (RULA), Rapid Entire Body Assessment (REBA) and electromyography (EMG). In our research, by using the exoskeleton robot we built, the muscle activity of the Erector Spinae decreased by about 21.62% for lifting objects during stoop lifting and 22.53% during semi-squat lifting, while the muscle activity of Biceps Femoris decreased by 6.775% and 18.51%, respectively, for the same tasks as above. The development of exoskeleton robots in this study reduces the risk of musculoskeletal injuries in the wearer and can delay the time of about 20% of fatigue generation, and actually allows the subjects to wear them in the agricultural field for application, which can really help agricultural workers. Carry out labor related work. This work can be applied not only to agricultural tasks, but also for logistics personnel, construction work, and other related work fields. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T08:12:56Z (GMT). No. of bitstreams: 1 ntu-108-R06631012-1.pdf: 3588210 bytes, checksum: 5c6e296c432a5e3171d15e0b734cb425 (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | 目錄
誌謝 i 摘要 ii Abstract iii 目錄 v 圖目錄 viii 表目錄 xi 第一章 緒論 1 1.1 前言 1 1.2 研究目的 3 第二章 文獻探討 4 2.1 人因相關職業傷害簡介 4 2.2 人體工學評估方法與檢核表 5 2.3 慣性測量單元(Inertial Measurement Unit) 5 2.4 外骨骼機器人簡介 7 2.4.1 初期發展與應用 8 2.4.2 外骨骼機器人機構設計 9 2.5 生理肌電訊號 10 2.5.1 肌電圖(EMG)介紹 11 2.5.2 訊號處理與分析 11 2.6 多人機介面互動設計與原理 12 第三章 研究方法 14 3.1 人體工學量測系統 14 3.1.1 RULA快速上肢評估 15 3.1.2 REBA快速全身評估 17 3.1.3 資料收集與感測器裝戴 20 3.1.4 圖形化介面 21 3.2 省力型外骨骼機器人 22 3.2.1 電子無刷馬達 26 3.2.2 馬達控制器 28 3.2.3 諧波減速機 30 3.2.4 致動模組扭力計算 31 3.2.5 控制策略與控制模型 33 3.3 肌電圖量測系統 38 3.3.1 實驗設備 38 3.3.2 訊號擷取與處理 40 3.4 實驗規劃與方法 41 3.4.1 實驗室場域試驗 41 3.4.2 農業場域實地試驗 42 3.5 軟體架構與說明 43 3.5.1 架構 43 3.5.2 模組說明 44 第四章 結果與討論 45 4.1 人體工學評估系統驗證與實驗 45 4.1.1 系統驗證 45 4.1.2 實驗結果 47 4.2 外骨骼機器人室內場域實驗 51 4.2.1 肌電圖系統結果比較 53 4.2.2 人體工學評估系統結果比較 58 4.3 外骨骼機器人農業場域實地實驗 62 4.3.1 肌電圖系統結果比較 62 4.3.2 人體工學評估系統結果比較 65 4.4 肌肉疲勞試驗 69 第五章 結論與建議 72 5.1 結論 72 5.2 建議 72 參考文獻 74 | |
dc.language.iso | zh-TW | |
dc.title | 基於慣性測量單元之人因工程分析系統及其應用於外骨骼機器人省力分析 | zh_TW |
dc.title | Development of an Ergonomics Evaluation System Based on Inertial Measurement Unit and Its Application in the Analysis of Exoskeleton Robot Load Reduction | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 葉仲基(Jhong-Ji Ye),顏炳郎(Ping-Lang Yen) | |
dc.subject.keyword | 農業人體工程學,外骨骼機器人,人體工學方法,慣性測量單位(IMU),肌電圖 (EMG), | zh_TW |
dc.subject.keyword | Agricultural ergonomics,Exoskeleton robot,Ergonomic methods,Inertial Measurement Units (IMUs),Electromyography (EMG), | en |
dc.relation.page | 79 | |
dc.identifier.doi | 10.6342/NTU201903693 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-08-15 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物產業機電工程學研究所 | zh_TW |
顯示於系所單位: | 生物機電工程學系 |
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 | 3.5 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。