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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57631完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 歐陽明 | |
| dc.contributor.author | Tsung-Hua Li | en |
| dc.contributor.author | 李宗樺 | zh_TW |
| dc.date.accessioned | 2021-06-16T06:55:02Z | - |
| dc.date.available | 2014-07-29 | |
| dc.date.copyright | 2014-07-29 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-07-20 | |
| dc.identifier.citation | [1]“Myo – Gesture Control Armband”, from https://www.thalmic.com/en/myo/
[2] Huang, C. Q., L. F. Xie, and Y. L. Liu. 'PD plus error-dependent integral nonlinear controllers for robot manipulators with an uncertain Jacobian matrix.' ISA transactions 51.6 (2012): 792-800. [3] Cardou, Philippe, Samuel Bouchard, and Clement Gosselin. 'Kinematic-sensitivity indices for dimensionally nonhomogeneous jacobian matrices.' Robotics, IEEE Transactions on 26.1 (2010): 166-173. [4] Pham, Hoang-Lan, et al. 'Position and orientation control of robot manipulators using dual quaternion feedback.' IROS'10: International Conference on Intelligent Robots and Systems. 2010. [5] Ha, Sehoon, Yuting Ye, and C. Karen Liu. 'Falling and landing motion control for character animation.' ACM Transactions on Graphics (TOG) 31.6 (2012): 155. [6] Ha, Sehoon, Yunfei Bai, and C. Karen Liu. 'Human motion reconstruction from force sensors.' Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation. ACM, 2011. [7] Jain, Sumit, Yuting Ye, and C. Karen Liu. 'Optimization-based interactive motion synthesis.' ACM Transactions on Graphics (TOG) 28.1 (2009): 10. [8] Brown, William M., et al. 'Dance reveals symmetry especially in young men.' Nature 438.7071 (2005): 1148-1150. [9] Wei, Xiaolin, Peizhao Zhang, and Jinxiang Chai. 'Accurate realtime full-body motion capture using a single depth camera.' ACM Transactions on Graphics (TOG) 31.6 (2012): 188. [10] Wang, Yangang, et al. 'Video-based hand manipulation capture through composite motion control.' ACM Transactions on Graphics (TOG) 32.4 (2013): 43. [11] Ahsan, Md R., Muhammad Ibn Ibrahimy, and Othman Omran Khalifa. 'Hand motion detection from EMG signals by using ANN based classifier for human computer interaction.' Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on. IEEE, 2011. [12] Ding, Qichuan, et al. 'A novel motion estimate method of human joint with EMG-Driven model.' Bioinformatics and Biomedical Engineering,(iCBBE) 2011 5th International Conference on. IEEE, 2011. [13] Margaret Minsky, Ming Ouhyoung, Oliver Steele, Frederick P. Brooks,Jr., Max Behensky,' Feeling and Seeing: Issues in Force Display', ACM Computer Graphics, Vol.24, No.2, pp236-244. [14]“Audio Media Intelligence Group, Oita University', from http://www-ai1.csis.oita-u.ac.jp/ [15]“Tracking Users with Kinect Skeletal Tracking”, from http://msdn.microsoft.com/en-us/library/jj131025.aspx [16]“FSR Integration Guide and Evaluation Parts Catalog with Suggested Electrical Interfaces”, from http://www.interlinklelectronics.com/ [17]“Arduino:Force-Sensitive Resistos”, from http://yehnan.blogspot.tw/2013/09/arduinoforce-sensitive-resistor.html [18]“Arduino:flex/bend sensor”, from http://yehnan.blogspot.tw/2013/09/arduinoflexbend-sensor.html [19]“Flex Sensor Special Edition Length”, from http://www.spectrasymbol.com/ [20]“androciti MMA7361L”, from http://wiki.androciti.com/index.php?MMA7361L [21] Lin, Z. H. A. O. 'Design of sailboard control system based on STC12C5A60S2.' Electronic Design Engineering 4 (2012): 048. [22]“Three‐lead Differential Muscle/Electromyography Sensor for Microcontroller Applications”, from http://www.advancertechnologies.com/ | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57631 | - |
| dc.description.abstract | 本研究使用影像技術與接觸式的硬體裝置,取得人體的運動數據與連續性的訊號,以時間串連出每一個不同的運動數據,讓使用者可以得到不同性質的運動數據,用來表示自己的運動狀況與運動效果。
影像技術以深度攝影機取得的三維資料進行分析,可以透過攝影機的視野分析場景的實際大小,得到攝影機畫面與真實世界的距離轉換比例,以此來做使用者運動狀況分析。我們的研究包含以下三種運動狀況。第一種是用全身關節骨架計算運動速度,第二種是以顏色標記來分析關節旋轉角度,第三種是分析人體的站立姿勢及是否平穩,計算兩腳之間張開的角度與身體重心是否在雙腳所在的投影面上。 根據物理性質的數據量測,運用不同的微處理器裝置幫助分析運動數據。使用了張力計、陀螺儀、肌肉電位感應器,我們預期可以使三種動作量測更加準確。第一種是武術出拳力道,根據物理張力計可以知道直接接觸的受力。第二種是旋轉角度的量測,提出物理量測的目的在於不受方向與環境限制,可以得到更多關節的轉動數據。第三種是肌肉電位分析,在這個實驗中可以取得肌肉微小的數據變化。 本研究從運動過程中取得的數據資料,每一段動作都會擷取運動速度、關節座標、旋轉角度、肌肉電位等數據。數據經由實驗過程分析,具有一定程度的可靠度,在硬體反應時間的許可之內,同時能給予足以呈現動作數據的準確性。我們反覆從多位使用者,與多組實驗數據比較的情況中。我們可以觀察到人體運動的站立姿勢,會和身體重心相關,同樣也對運動穩定性有關。運動過程中的關節旋轉,在符合受力方向的情況下,可以從實驗數據中觀察到呈現正比的提升。 分析人體穩定性與旋轉運動這兩種方式,在實驗的相關數據中,我們可以注意到產生較大受力的動作時,這些情況中因為速度較快,關節瞬間變化較大,都是潛在的運動傷害成因。 | zh_TW |
| dc.description.abstract | In this study, we use the imaging technology and the hardware devices, which consist of human motion data and continuity of the time signal, a time series of data for each different sport, so that users can get the motion data of different properties, to show their movement status and motion effects.
Through the use of three-dimensional imaging technology to obtain information on the depth camera, the actual size of the camera field of view can be analyzed through the scene; we can then get the camera screen and the conversion ratio from the real world, in order to make the user's movement situation analysis. Our study includes the following sports status: The first is to calculate the velocity of a skeleton with joints, and the second is color-coded information to analyze the joint rotation angle, and the third is an analysis of the human body standing position, where the system calculates the opening angle and area between the legs. According to the measurement of physical properties, the use of different microprocessor can be used to analyze the motion data. Using the pressure gauge (strain gauge), a gyroscope, muscle potential sensors, we expect human actions can be more accurately measured. The first is a martial arts punching force, according to the physical force gauge to know direct contact. The second is a measure of the angle of rotation, the advantage of physical methods is that the environment is not restricted, and we can get more data from rotated joints. The third is muscle potential analysis, in this experiment; small changes in the muscle can be obtained . Our data are obtained from the human motion, and at each section we will capture velocity, joint coordinates, rotation, muscle potentials and other data. The experimental data analysis procedure, which has a certain degree of reliability, with a fast response time in the hardware, can give sufficient accuracy of motion data presented. We repeat these experiments from multiple users, and compare with the case of multiple sets of experimental data. We can observe the movement of the human body standing posture, where body weight is also relevant, and can be related to the stability of motion. Rotating joints during exercise, which is subject to compliance with the direction of the force, can be observed from the experimental data to show proportional increase or decrease. This rotational movement of the body and the stability are analyzed in this way: in the experimental data, we can observe that with a greater force action, a large instantaneous change in the joint is measured, and these are potential causes of sport injuries. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T06:55:02Z (GMT). No. of bitstreams: 1 ntu-103-R01944026-1.pdf: 1684779 bytes, checksum: 118ecb3464b9b9f185a0ac81524ac241 (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii Abstract iii Contents v List of Figures vii List of Tables ix 1 Introduction 1 1.1 Background and Motivation 1 1.2 Issues in Human Motion Tracking 3 1.3 Thesis Organization 4 1.4 Contributions 5 2 Related Works 6 2.1 Jacobian Matrix 6 2.2 Feature-Based Methods 7 2.3 Depth-Based Methods 9 2.4 Physical Measurement Methods 10 3 Vision Measuring Methods 11 3.1 System Overview 11 3.2 Velocity Measured by Skeleton Joint Translate 14 3.3 Rotation Measured by Color Marker 18 3.4 Standing Angle Calculation 21 3.5 Image Data Analysis 23 4 Physical Measuring Methods 26 4.1 Hardware Overview 26 4.2 Measured by Force-Sensitive and Bend Sensor 27 4.3 Joint Rotation and Velocity by Gyroscope 35 4.4 Electromyography Sensor 38 4.5 Physical Measurement Data Analysis 41 5 Experiments and Results 44 5.1 Implementation Environment 44 5.2 Results 55 5.3 Limitation 59 6 Conclusion and Future Work 60 6.1 Conclusion 60 6.2 Future Work 62 Bibliography 63 | |
| dc.language.iso | en | |
| dc.subject | 微處理器量測 | zh_TW |
| dc.subject | 視覺影像分析 | zh_TW |
| dc.subject | 深度攝影機計算 | zh_TW |
| dc.subject | 動作捕捉 | zh_TW |
| dc.subject | 運動成果分析 | zh_TW |
| dc.subject | calculate the depth camera | en |
| dc.subject | visual image analysis | en |
| dc.subject | microprocessor measurements | en |
| dc.subject | motion capture | en |
| dc.subject | motion analysis of the results | en |
| dc.title | 動作量測與分析:以兩種中國武術為例 | zh_TW |
| dc.title | Measurement and Analysis of Two Types of Chinese Martial Arts | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 梁容輝,林奕成 | |
| dc.subject.keyword | 深度攝影機計算,視覺影像分析,微處理器量測,動作捕捉,運動成果分析, | zh_TW |
| dc.subject.keyword | calculate the depth camera,visual image analysis,microprocessor measurements,motion capture,motion analysis of the results, | en |
| dc.relation.page | 67 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2014-07-21 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
| 顯示於系所單位: | 資訊網路與多媒體研究所 | |
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