(3.237.178.91) 您好!臺灣時間:2021/03/07 02:28
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:張博堯
研究生(外文):CHANG, PO-YAO
論文名稱:智慧型腿部伸展機即時運動指導與使用狀況監測
論文名稱(外文):Real-time Exercise Instruction and Condition Monitoring of Intelligent Leg Extension Machine
指導教授:蕭耀榮蕭耀榮引用關係
指導教授(外文):SHIAO, YAO-JUNG
口試委員:蕭耀榮陳立文蕭俊祥
口試委員(外文):SHIAO, YAO-JUNGCHEN, LI-WENSHAW, JIN-SIANG
口試日期:2020-07-24
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:車輛工程系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:114
中文關鍵詞:即時運動監測運動指導肌肉疲勞偵測腿部伸展機
外文關鍵詞:Real-time Condition MonitoringExercise InstructionMuscle Fatigue DetectionLeg Extension Machine
相關次數:
  • 被引用被引用:0
  • 點閱點閱:30
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
如今社會上運動風氣越來越盛行,健身房已經是隨處可見的現象,運動固然可以讓人更加健康,但貿然且隨意的運動卻有可能帶來受傷的風險,這時如何安全且有效率的運動就是需要考量的問題。在健身房傳統的運動器材中,雖然有使用說明,但若無一位合適的指導員在一旁教導,往往都不知該如何正確的使用這些器材,若是在運動過程中施力不當、姿勢錯誤,或突然的疲勞感導致肌肉無力,無法負荷槓片的重量,這時就容易導致受傷等後果。
本研究的目的正是為了改善這項問題,利用慣性量測單元(IMU),來量測使用者在腿部伸展機上的運動姿態,藉由分析這些數據來監測使用者的運動和疲勞情況,在使用者出現姿勢錯誤、速度過快或過慢、疲勞等狀況時能即時的給予告知,讓使用者可以即時調整,之後可以再透過本實驗室開發的磁流變液阻力器來即時的改變阻力,讓使用者可以隨時在正確且安全的狀況下,降低運動帶來傷害的可能性。
本研究比較多種角度的估測方式,選用卡爾曼濾波器來做估測角度的工具,並找出腿部伸展運動時的各種數據,利用慣性量測單元達到判斷腿部伸展的運動特徵,能夠即時判斷出運動當下的狀況。以及提出新的判斷疲勞方法,並驗證其結果,制定出一個量表來表示疲的程度,讓慣性量測單元能夠代替肌電圖感測器偵測運動時的疲勞。最後開發人機介面,將所有的功能呈現給使用者,完成即時的運動指導與監測。

Nowadays, sports become more and more popular in our society. Being inseparable with our lives. Although sports or exercise can keep people healthy and comfortable, accidents from sports may increase the risk of injury. Therefor doing exercise safely and efficiently at this time is very important. When it comes to the training device in gymnasium. Usually, there have instructions on the equipment for the user. However, without the instructor on the side, people do not understand the correct exercise method and lead to irreversible misery. For example, if the load settings are wrong, trainee could end up feeling exhausted and hurting oneself muscle.
The purpose of this study is to improve this problem. The Inertial Measurement Unit (IMU) is used to measure the user's movement posture on leg extension machine. By analyzing these data, people could observe the user's movement and fatigue. Moreover, it could allow people to track their exercise condition whether it is posture incorrect, too fast, too slow, fatigue, etc. These will be notified immediately and changed the resistance in time by the magnetorheological fluid resistance developed by our laboratory so that the people always exercise under right position.
In conclusion, we use the IMU to determine the characteristics of leg extension. And propose a new method for judging fatigue. Compare the results with EMG. Let the IMU can replace the EMG sensor to detect fatigue. The interface we design which can monitor the user's condition and provide appropriate guidance immediately.
Monitoring the trainee’s condition in time can not only provide them professional instruction but also help them avoid irreversible injuries and miseries. With the help of The Inertial Measurement Unit (IMU) and magnetorheological fluid resistance, can exercise more relieve and effectively.

摘 要 I
ABSTRACT III
誌 謝 V
目 錄 VI
表目錄 IX
圖目錄 X
第一章 緒論 1
1.1 前言 1
1.2 研究動機與目的 2
1.3 文獻回顧 3
1.3.1 腿部伸展機 3
1.3.2 磁流變液阻力器 5
1.3.3 肌電圖傳感器 6
1.3.4 慣性量測單元 8
1.4 論文架構 9
第二章 慣性量測單元訊號處理 10
2.1 訊號濾波 10
2.1.1 加速度計 11
2.1.2 陀螺儀 12
2.1.3 磁力計 13
2.1.4 分析與探討 14
2.2 加速度計磁力計角度估測 14
2.2.1 加速度計估測角度 14
2.2.2 磁力計估測角度 16
2.3 感知器融合 16
2.3.1 互補濾波器 17
2.3.2 梯度下降 18
2.3.3 卡爾曼濾波 19
2.3.4 角度估測實驗 20
2.3.5 實驗結果分析 21
第三章 運動模式分析與疲勞監測 28
3.1 腿部伸展器運動方式 28
3.2 實驗設備介紹 29
3.3 實驗方法 32
3.4 運動數據分析 32
3.4.1 腿部伸展運動特徵 33
3.4.1.1 小腿運動特徵 33
3.4.1.2 大腿運動特徵 42
3.4.1.3 膝關節的角度 50
3.4.2 運動週期判斷 51
3.5 疲勞監測 53
3.5.1 Jerk Cost 54
3.5.2 曲線擬合 55
3.5.4 肌電圖感測器 56
3.5.4 實驗結果分析 58
第四章 即時監測與運動指導 75
4.1 控制流程 75
4.2 腿部伸展的訓練方式及規範 77
4.2.1 重量選擇 77
4.2.2 組數 78
4.2.3 力竭 78
4.2.4 運動速度 79
4.2.5 課表安排 80
4.3 MR訓練模式 81
4.4 可視化人機介面之設計 84
4.5 即時監測與指導分析 89
第五章 結論與未來展望 101
5.1 結論 101
5.2 未來展望 102
參考文獻 103
附錄 108
符號彙編 112

[1]Pueo, Basilio Journal of Human Sport and Exercise, "High speed cameras for motion analysis in sports science," vol. 11, no. 1, pp. 53-73, 2016.
[2]Quintana, Marc, Padullés, Josep Maria and Buscà, Bernat, "High-speed cameras in sport and exercise: Practical applications in sports training and performance analysis," vol. 34, no. 2, pp. 11-24, 2016.
[3]Patterson, Matt, McGrath, Denise and Caulfield, Brian, "Using a tri-axial accelerometer to detect technique breakdown due to fatigue in distance runners: a preliminary perspective," in 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011, pp. 6511-6514: IEEE.
[4]J. Liang et al., "Accurate Estimation of Gait Altitude Using One Wearable IMU Sensor," in 2018 IEEE 1st International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS), 2018, pp. 64-67: IEEE.
[5]Fourati, Hassen, "Heterogeneous data fusion algorithm for pedestrian navigation via foot-mounted inertial measurement unit and complementary filter," vol. 64, no. 1, pp. 221-229, 2014.
[6]Chen, Po-Han, "運用單一慣性測量單元於深蹲動作之力竭預測," pp. 1-47, 2017.
[7]McGinnis, Ryan S, Cain, Stephen M, Davidson, Steven P, Vitali, Rachel V, Perkins, Noel C, McLean, "Quantifying the effects of load carriage and fatigue under load on sacral kinematics during countermovement vertical jump with IMU-based method," vol. 19, no. 1, pp. 21-34, 2016.
[8]Kos, Marko, Ženko, Jernej, Vlaj, Damjan, Kramberger, Iztok, "Tennis stroke detection and classification using miniature wearable IMU device," in 2016 International Conference on Systems, Signals and Image Processing (IWSSIP), 2016, pp. 1-4: IEEE.
[9]Huang, Yi-Chen, Chen, Tsung-Long, Chiu, Bo-Chun, Yi, Chih-Wei, Lin, Chung-Wei, Yeh, Yu-Jung and Kuo, Lun-Chia, "Calculate golf swing trajectories from imu sensing data," in 2012 41st International Conference on Parallel Processing Workshops, 2012, pp. 505-513: IEEE.
[10]Groh, Benjamin H, Kautz, Thomas, Schuldhaus, Dominik and Eskofier, Bjoern M, "IMU-based trick classification in skateboarding," in KDD workshop on large-scale sports analytics, 2015, vol. 17.
[11]Neumann, Donald A, "Kinesiology of the musculoskeletal" system-e-book: foundations for rehabilitation. Elsevier Health Sciences, 2013.
[12]Yaojung Shiao, Thang Hoang, Mahendra Babu Kantipudi, Nung-Chin Kao, Chien-Hung Lai*, "Development of Multilayer Magneto-rheological Brake for Knee-orthosis Applications," Chinese Mechanical Engineers, 2020.
[13]康堯閎, "具疲勞偵測之智慧型可變阻力腿部肌力訓練系統" 碩士論文, 國立台北科技大學, 2019.
[14]Yaojung Shiao, Thang Hoang, "Condition Sensing for User in Semi-active Leg Extension Exercise," presented at the 2019 IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, Okinawa, Japan, May 31-June 3, 2019
[15]Medicine, ACSM's Resources for the Personal Trainer. Lippincott Williams & Wilkins, 2013.
[16]Yaojung Shiao, Edwin Santillan, "A Smart Variable-Resistance Leg Extension Machine Using Magneto-rheological Technology," presented at the Automation Technology, Taichung, Taiwan, Dec. 6-8, Dec. 6-82018.
[17]T. Triwiyanto, O. Wahyunggoro, H. Nugroho, "Muscle fatigue compensation of the electromyography signal for elbow joint angle estimation using adaptive feature," vol. 71, pp. 284-293, 2018.
[18]Subasi, Abdulhamit, Kiymik, M Kemal, "Muscle fatigue detection in EMG using time–frequency methods, ICA and neural networks," vol. 34, no. 4, pp. 777-785, 2010.
[19]E. Top, "The effect of fatigue exercise on the electromyogram (EMG) and balance performance of individuals with mental disability," 2017.
[20]Zhang, Qin, Liu, Runfeng, Chen, Wenbin, Xiong, Caihua, "Simultaneous and continuous estimation of shoulder and elbow kinematics from surface emg signals," vol. 11, p. 280, 2017.
[21]H. Desa, M. Zuber, R. Jailani, N. Tahir, "Development of EMG circuit for detection of leg movement," in 2016 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), 2016, pp. 46-51: IEEE.
[22]Jamal, Muhammad Zahak, "Signal acquisition using surface EMG and circuit design considerations for robotic prosthesis," vol. 18, pp. 427-448, 2012.
[23]Konrad, Peter, "The ABC of EMG: A Practical Introduction to Kinesiological Electromyography," 2005.
[24]SparkFun 9DoF Razor IMU M0. Available: https://www.taiwaniot.com.tw/product/sparkfun-9dof-razor-imu-m0/
[25]P. Gui, L. Tang, S.Mukhopadhyay, "MEMS based IMU for tilting measurement: Comparison of complementary and kalman filter based data fusion," in 2015 IEEE 10th conference on Industrial Electronics and Applications (ICIEA), 2015, pp. 2004-2009: IEEE.
[26]Chang, Hsing-Cheng, Hsu, Yu-Liang, Yang, Shih-Chin, Lin, Jung-Chih, Wu, Zhi-Hao, "A wearable inertial measurement system with complementary filter for gait analysis of patients with stroke or Parkinson’s disease," vol. 4, pp. 8442-8453, 2016.
[27]Madgwick, Sebastian OH, Harrison, Andrew JL, Vaidyanathan, Ravi, "Estimation of IMU and MARG orientation using a gradient descent algorithm," in 2011 IEEE international conference on rehabilitation robotics, 2011, pp. 1-7: IEEE.
[28]Wu, Jin, Zhou, Zebo, Chen, Jingjun, Fourati, Hassen, Li, Rui,"Fast complementary filter for attitude estimation using low-cost MARG sensors," vol. 16, no. 18, pp. 6997-7007, 2016.
[29]黃昱傑, 成維華, "利用卡曼濾波器整合全球定位系統及慣性量測單元之精簡模型研究," 2009.
[30]Boonstra, Miranda C, Van Der Slikke, Rienk MA, Keijsers, Noel LW, Van Lummel, Rob C, de Waal Malefijt, Maarten C, Verdonschot, "The accuracy of measuring the kinematics of rising from a chair with accelerometers and gyroscopes," vol. 39, no. 2, pp. 354-358, 2006.
[31]F. Alam, Z. ZhaiHe, H. JiaJia, "A comparative analysis of orientation estimation filters using MEMS based IMU," in Proceedings of the International Conference on Research in Science, Engineering and Technology, Dubai, UAE, 2014, pp. 21-22.
[32]M. Admiraal, S. Wilson, and R. Vaidyanathan, "Improved formulation of the IMU and MARG orientation gradient descent algorithm for motion tracking in human-machine interfaces," in 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), 2017, pp. 403-410: IEEE.
[33]M. Narasimhappa, A. D. Mahindrakar, V. C. Guizilini, M. H. Terra, S. L. Sabat, "An improved Sage Husa adaptive robust Kalman Filter for de-noising the MEMS IMU drift signal," in 2018 Indian Control Conference (ICC), 2018, pp. 229-234: IEEE.
[34]Y. Kim, H. Bang, "Introduction to Kalman Filter and Its Applications," in Introduction and Implementations of the Kalman Filter: IntechOpen, 2018.
[35]Kim, Youngjoo, Bang, Hyochoong, "Kalman filter and its application," in 2015 8th International Conference on Intelligent Networks and Intelligent Systems (ICINIS), 2015, pp. 74-77: IEEE.
[36]W. L. Westcott, T. R. Baechle, Strength training past 50. Human Kinetics, 2015.
[37]Schoenfeld, Brad J, "The mechanisms of muscle hypertrophy and their application to resistance training," vol. 24, no. 10, pp. 2857-2872, 2010.
[38]Zhang, Lichen, Diraneyya, Mohsen Mutasem, Ryu, JuHyeong, Haas, Carl T, Abdel-Rahman, Eihab M "Jerk as an indicator of physical exertion and fatigue," vol. 104, pp. 120-128, 2019.
[39]L. Zhang, M. Diraneyya, J. Ryu, C. Haas, E. Abdel-Rahman, "Automated Monitoring of Physical Fatigue Using Jerk," in ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction, 2019, vol. 36, pp. 989-997: IAARC Publications.
[40]Huang, Stephanie, Ferris, Daniel P, "Muscle activation patterns during walking from transtibial amputees recorded within the residual limb-prosthetic interface," vol. 9, no. 1, p. 55, 2012.
[41]Perry, Bruce W, Fitness for geeks: real science, great nutrition, and good health. " O'Reilly Media, Inc.", 2012, pp. 237
[42]Linnamo, Vesa, Pakarinen, Arto, Komi, Paavo V, Kraemer, William J, Häkkinen, Keijo "Acute hormonal responses to submaximal and maximal heavy resistance and explosive exercises in men and women," vol. 19, no. 3, p. 566, 2005.


電子全文 電子全文(網際網路公開日期:20250819)
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔