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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 趙聖德 | zh_TW |
| dc.contributor.advisor | Sheng-Der Chao | en |
| dc.contributor.author | 歐威佑 | zh_TW |
| dc.contributor.author | Wei-Yu Ou | en |
| dc.date.accessioned | 2024-09-09T16:12:35Z | - |
| dc.date.available | 2024-09-10 | - |
| dc.date.copyright | 2024-09-09 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-08-14 | - |
| dc.identifier.citation | [1] Michael W. Whittle. Generation and attenuation of transient impulsive forces beneath the foot: a review. Gait and Posture, 10(3):264–275, 1999.
[2] Wangdo Kim, Arkady S. Voloshin, and Stanley H. Johnson. Modeling of heel strike transients during running. Human Movement Science, 13(2):221–244, 1994. [3] Chih-Chin Hsu, Wen-Chung Tsai, Yio-Wha Shau, Kay-Lun Lee, and Ching-Fang Hu. Altered energy dissipation ratio of the plantar soft tissues under the metatarsal heads in patients with type 2 diabetes mellitus: A pilot study. Clinical Biomechanics,22(1):67–73, 2007. [4] Adam I. Daoud, Gary J. Geissler, Frank Wang, Jason Saretsky, Yahya A. Daoud, and Daniel E. Lieberman. Foot strike and injury rates in endurance runners: A retrospective study. Medicine and Science in Sports and Exercise, 44(7):1325–1334, 2012. [5] Brian J. Addison and Daniel E. Lieberman. Tradeoffs between impact loading rate, vertical impulse and effective mass for walkers and heel strike runners wearing footwear of varying stiffness. Journal of Biomechanics, 48(7):1318–1324, 2015. [6] David C. Morgenroth, Jonathan R. Medverd, Mahyo Seyedali, and Joseph M. Cz-erniecki. The relationship between knee joint loading rate during walking and degenerative changes on magnetic resonance imaging. Clinical Biomechanics, 29(6):664–670, 2014. [7] Federica Verdini, M. Marcucci, M.G. Benedetti, and T. Leo. Identification and char-acterisation of heel strike transient. Gait and Posture, 24(1):77–84, 2006. [8] Tsz-Ching Hsu, Ying-Shiung Lee, and Yio-Wha Shau. Biomechanics of the heel pad for type 2 diabetic patients. Clinical Biomechanics, 17(4):291–296, 2002. [9] Carl Pai-Chu Chen Yio-Wha Shau Chung-Li Wang Chih-Chin Hsu, Wen-Chung Tsai. Effects of aging on the plantar soft tissue properties under the metatarsal heads at different impact velocities. Ultrasound in Medicine Biology, 31(10):1423–1429, 2005. [10] Arthur D. Kuo Karl E. Zelik. Human walking isn’t all hard work: evidence of soft tissue contributions to energy dissipation and return. Journal of Experimental Biology,213(24):4257–4264, 2010. [11] Peter R Cavanagh. Plantar soft tissue thickness during ground contact in walking. Journal of Biomechanics, 32(6):623–628, 1999. [12] T.-C. Hsu, C.-L. Wang, Y.-W. Shau, F.-T. Tang, K.-L. Li, and C.-Y. Chen. Alteredheel-pad mechanical properties in patients with type 2 diabetes mellitus. DiabeticMedicine, 25(7):60–64, 2008. [13] Kai-Jung Chi and Daniel Schmitt. Mechanical energy and effective foot mass duringimpact loading of walking and running. Journal of Biomechanics, 38(6):1387–1395,2005. [14] Juan C. Pérez-Ibarra; Adriano A. G. Siqueira; Hermano Igo Krebs. Real-time identification of gait events in impaired subjects using a single-imu foot mounted device.IEEE Sensors Journal, 20(5):2616–2624, 2019. [15] Weijun Tao, Tao Liu, Rencheng Zheng, and Hutian Feng. Gait analysis using wearable sensors. Sensors, 12(2):2255–2283, 2012. [16] Hang Shang AXu Ru, Nian Gu and Heng Zhang. Mems inertial sensor calibration technology: Current status and future trends. Micromachines, 13(6):879, 2022. [17] S. M.N. Arosha Senanayake YChathuri Senanayake. A computational method for reliable gait event detection and abnormality detection for feedback in rehabilitation.IEEE Transactions on Neural Systems and Rehabilitation Engineering, 14(10):863–874, 2011. [18] Yi Chiew Han, Kiing Ing Wong, and Iain Murray. Gait phase detection for normal and abnormal gaits using imu sensor. IEEE Sensors Journal, 19(9):264–275, 2019. [19] Yongbin Qi; Cheong Boon Soh; Erry Gunawan; Kay-Soon Low; Rijil Thomas. Assessment of foot trajectory for human gait phase detection using wireless ultrasonic sensor network. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(1):88–97, 2015. [20] A. A. Nikooyan and A. A. Zadpoor. Mass–spring–damper modelling of the human body to study running and hopping – an overview. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 225(12):1121–1140, 2011. [21] Robert F. Ker. The time-dependent mechanical properties of the human heel pad in the context of locomotion. Journal of Experimental Biology, 199(7):1501–1508, 1996. [22] Y. W. Shau F. T. Tang K. L. Li C. Y. Chen T. C. Hsu, C. L. Wang. Altered heel-padmechanical properties in patients with type 2 diabetes mellitus. Diabetic Medicine, 17(10):854–859, 2000. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/95448 | - |
| dc.description.abstract | 足跟著地(heel strike)是步態分析(gait analysis)中足跟與地面接觸的初始時刻。在這一時刻,根據動量守恆,腳與地面動量交換,移動的腳會產生瞬態力(transient force)。足部軟組織的結構、鞋子的材料和粘彈性鞋墊都對緩解這些瞬態力起到了一定作用。
在本研究中,使用了兩個六自由度慣性測量單元(6-DOF IMU)傳感器來測量脛骨(tibia)和足部(foot)的加速度。這些測量結果結合了Wangdo Kim(1994)提出的質量-彈簧-阻尼模型,有助於評估足部下方瞬態力的消散和衰減,並利用模型的公式去計算足部軟組織的負載-位移曲線(load-displacement curve)。 為了得到模型參數,本研究提出了一種新方法。通過將包含IMU傳感器的可穿戴設備(wearable device)與機器學習相結合,可以獲得精確的足跟著地模型,利用模型模擬力的傳播使得讓計算部軟組織的負載-位移曲線成為可能。預測的加速度在行走頻率為2 Hz、1 Hz和0.5 Hz時與實測值幾乎一模一樣。在不同行走頻率下所得到的足部軟組織的負載-位移曲線與傳統從人造外力所獲得的足部軟組織的負載-位移曲線有一點不同,作者猜測是因為使用穿戴式裝置噪音影響以及濾波器可能濾掉真實資料細節,但大致上趨勢仍然與先前文獻相同,因此作者認為本研究的結果仍具有參考價值。 但總體而言,實驗得到的數據並不完美,此方法仍須被進一步的驗證且需要進一步的改良。 | zh_TW |
| dc.description.abstract | Heel strike is the initial moment when the heel makes contact with the ground during gait analysis. At this point, the moving foot generates a transient force due to the momentum exchange. The soft tissue structure of the foot, the materials used in shoe construction, and viscoelastic shoe inserts all contribute to mitigating these transient forces[1].
In this study, two 6-DOF IMU sensors were employed to measure the accelerations of the tibia and foot. These measurements, combined with the mass-spring-damper model proposed by Wangdo Kim (1994)[2], assist in evaluating the dissipation and attenuation of transient forces beneath the foot. This approach also enables the calculation of the load-displacement curve for the foot's soft tissue by utilizing the ground reaction force model derived from the mass-spring-damper framework. To develop a heel strike model, a new method is introduced. By integrating IMU sensors in a wearable device with machine learning, an accurate heel strike model can be obtained. The predicted accelerations perfectly match the measured ones at walking frequencies of 2, 1, and 0.5 Hz. Although the load-displacement curves at different walking frequencies differ from the typical load-displacement curves of the foot's soft tissue obtained from man-made forces[3], they still show a similar trend with the previous studies. This may be due to the inherent differences between the transient forces generated during heel strike while walking and those applied to the foot's soft tissue under man-made forces or simply because of the low-pass filter that filtered out the details or maybe noise by the wearable device. Therefore, the author believes that the results of this study still hold reference value. However, overall, the data obtained from the experiments are not perfect. This method requires further validation and improvement. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-09-09T16:12:35Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-09-09T16:12:35Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Contents
Page Acknowledgements i 摘要iii Abstract v Contents vii List of Figures ix Chapter 1 Introduction 1 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Chapter 2 Paper review 5 2.1 Sensors calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Gait phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Model of heel strike transient . . . . . . . . . . . . . . . . . . . . . 7 Chapter 3 Material and methods 13 3.1 Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.2.1 Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.2.2 Experiment protocol . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.2.3 Neural network . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.3 Coordinate transformation . . . . . . . . . . . . . . . . . . . . . . . 16 3.4 Sensors calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Chapter 4 Results and discussion 23 4.1 Sensors calibration results . . . . . . . . . . . . . . . . . . . . . . . 23 4.2 Acceleration measurement . . . . . . . . . . . . . . . . . . . . . . . 26 4.3 Heel strike model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 4.4 Ground reaction force . . . . . . . . . . . . . . . . . . . . . . . . . 29 4.5 Load-displacements results . . . . . . . . . . . . . . . . . . . . . . . 30 4.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Chapter 5 Conclusion 39 5.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 5.2 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 References 41 Appendix A — Calibration results 45 A.1 Sensor1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 A.2 Sensor2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Appendix B — Different walking frequencies 49 B.1 2Hz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 B.2 1Hz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 B.3 0.5Hz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 | - |
| dc.language.iso | en | - |
| dc.subject | 能量耗散率 | zh_TW |
| dc.subject | 機器學習 | zh_TW |
| dc.subject | 腳底軟組織 | zh_TW |
| dc.subject | 穿戴式裝置 | zh_TW |
| dc.subject | 步態分析 | zh_TW |
| dc.subject | Wearable device | en |
| dc.subject | Gait analysis | en |
| dc.subject | Machine learning | en |
| dc.subject | Foot’s soft tissue | en |
| dc.subject | Energy dissipation ratio | en |
| dc.title | 使用慣性測量感測器測量腳底機械性質之研究 | zh_TW |
| dc.title | Mechanical properties of foot soft tissue during heel strike measured using IMU sensors | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 邵耀華;林哲宇;李皇德 | zh_TW |
| dc.contributor.oralexamcommittee | YIO-WHA SHAU;Che-Yu Lin;Huang-Te li | en |
| dc.subject.keyword | 穿戴式裝置,步態分析,機器學習,腳底軟組織,能量耗散率, | zh_TW |
| dc.subject.keyword | Wearable device,Gait analysis,Machine learning,Foot’s soft tissue,Energy dissipation ratio, | en |
| dc.relation.page | 57 | - |
| dc.identifier.doi | 10.6342/NTU202401279 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2024-08-14 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 應用力學研究所 | - |
| dc.date.embargo-lift | 2027-08-13 | - |
| 顯示於系所單位: | 應用力學研究所 | |
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