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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 傅立成(Li-Chen Fu) | |
dc.contributor.author | Chien-Ke Liao | en |
dc.contributor.author | 廖建科 | zh_TW |
dc.date.accessioned | 2021-06-08T00:03:06Z | - |
dc.date.copyright | 2013-08-26 | |
dc.date.issued | 2013 | |
dc.date.submitted | 2013-08-15 | |
dc.identifier.citation | [1] Thomas R., Lynda A., Robert H., “Public Health for an AGING SOCIETY”, 2012
[2] Taiwanese population projection in 2010-2060, http://www.cepd.gov.tw/m1.aspx?sNo=0000455 [3] 101年底我國老人長期照顧及安養機構概況, http://www.moi.gov.tw/stat/news_content.aspx?sn=7230 [4] The European Parkinson's Disease Association (EPDA), “The European Parkinson’s Disease Standards of Care Consensus Statements,” 2011, Volume i. [5] Stephen K. Van Den Eeden, “Incidence of Parkinson’s Disease: Variation by Age, Gender, and Race/Ethnicity,” American journal of Epidemiology, 2003, Volume 157, Issue 11, pp. 1015-1022. [6] Laplante MP, Hendershot GE, Moss AJ. Assistive technology devices and home accessibility features: prevalence, payment, needs and trends. Advance Data from Vital and Health Statistics. Vol 217. Hyattsville: National Center for Health Statistics; 1992. [7] Mann WC, Granger C, Hurren D, Tomita M, Charvat B. An analysis of problems with canes encountered by elderly persons. Phys Occup Ther Geriatr 1995;13:25-49. [8] Mann WC, Granger C, Hurren D, Tomita M, Charvat B. An analysis of problems with walkers encountered by elderly persons. Phys Occup Ther Geriatr 1995;13:1-23. [9] H. Bateni, BE. Maki, “Assistive devices for balance and mobility: Benefits, demands, and adverse consequences”. Archives of Physical Medicine and Rehabilitation. (Jan, 2005), 86:134–145 [10] A. Morris, R. Donamukkala, A. Kapuria, A. Steinfeld, J. Matthews, J. Dunbar-Jacobs, and S. Thrun. “A robotic walker that provides guidance”. ANSI Standard Y10.5-1968 [11] S. MacNamara, G. Lacey, A Smart Walker for the Frail Visually Impaired, “A smart walker for the frail visually impaired”, ICRA'00, Vol: 2 , 2000. Pages:1354 – 1359 [12] S. Dubows!q. F. Genot, and S. Godding. PAMM. A robotic aid to the elderly for mobility assistance and monitoring: A’Belping-hand for the elderly. IEEE Inremnrionol Conference on Roborics and Aurornorion (ICRA). San Francisco, CA, 2002. I C W [13] M. Spenko, H. Yu and S. Dubowsky, “Robotic personal aids for mobility and monitoring for the elderly, in IEEE Transactions on Neural systems and Rehabilitation Engineering, 14(3), pp. 344–351 [14] G. S. Wasson, J. P. Gunderson, “Variable autonomy in a shared control pedestrian mobility aid for the elderly”, IJCAI Workshop on Autonomu, Delegation and Control. 2001 [15] K. T. Song, S. Y. Jiang, “Force-Cooperative Guidance Design of an Omni-Directional Walking Assistive Robot”, International Conference on Mechatronics and Automation, 2011, pp. 1258 – 1263 [16] Dejnabadi H, Jolles BM, Aminian K. , “A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes,” IEEE Trans Biomed Eng. 2005 Aug;52(8), pp. 1478-84. [17] Dejnabadi H, Jolles BM, Casanova E, Fua P, Aminian K,“Estimation and visualization of sagittal kinematics of lower limbs orientation using body-fixed sensors,” IEEE Trans Biomed Eng. 2006 Jul;53(7) pp. 1385-93. [18] T. Liu, H. Utsunomiya, Y. Inoue, and K. Shibata, “Synchronous imitation control for biped robot based on wearable human motion analysis system,” IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008 [19] Benoit Mariani, Mayt′e Castro Jim′enez, Franc﹐ois J. G. Vingerhoets, and Kamiar Aminian, “On-Shoe Wearable Sensors for Gait and Turning Assessment of Patients With Parkinson’s Disease,” IEEE Trans Biomed Eng. 2013 VOL. 60, NO. 1, 155 [20] Young-Sook Lee, Wan-Young Chung, “camera sensor based human gait analysis for ubiquitous healthcare monitoring system,” 14th International Meeting on Chemical Sensors, 2012, PP. 963-966 [21] K.T. Yu, C.P. Lam, M.F. Chang, W.H. Mou, S.H. Tseng, L.C. Fu, “An interactive robotic walker for assisting elderly mobility in senior care unit”. ARSO, 2010, pp. 24-29 [22] O. Bernier, P. Cheung-Mon-Chan, and A. Bouguet. Fast nonparametric belief propagation for real-time stereo articulated body tracking. Comput. Vis. Image Underst.,113(1):29–47, 2009. [23] G. Mori, X. Ren, A. A. Efros, and J. Malik. Recovering human body configurations: Combining segmentation and recognition. In 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’04), volume2, pages 326–333, 2004. [24] Fischler, M. and R. Bolles (1981). Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Communications of the ACM 24, 381-395. [25] Y. R. Chen, C. M. Huang, and L. C. Fu, “Visual Tracking of Human Head and Arms with a Single Camera,”IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3416-3421, Oct. 2010. [26] S. Knoop, S. Vacek, and R. Dillmann, “Fusion of 2Dand 3DSensor Data for Articulated Body Tracking,”Robotics and Autonomous Systems, vol. 57, no. 3, pp. 321-329, March 2009. [27] J. Favrea, B.M. Jollesb, R. Aissaouic, K. Aminiana, “Ambulatory measurement of 3D knee joint angle”, Journal of Biomechanics, vol. 41, issue 5, pp. 1029–1035, 2008. [28] http://www.parkinson.org/Parkinson-s-Disease/PD-101/10-Early-Warning-Signs-of-Parkinson-s-Disease [29] Suzanne E Hallidaya, David A Winterb, James S Frankb, Aftab E Patlab, François Princec,“The initiation of gait in young, elderly, and Parkinson's disease subjects,” Gait & Posture Volume 8, Issue 1, August 1998, Pages 8–14 [30] Dr. Bastiaan R. Bloem, Dennis J. Beckley2, J. Gert van Dijk1, Aeilko H. Zwinderman, Michael P. Remler, Raymund A. C. Roos1,“Influence of dopaminergic medication on automatic postural responses and balance impairment in Parkinson's disease,” Movement Disorders, Volume 11, Issue 5, pages 509–521, September 1996 [31] Diener HC, Dichgans J, Guschlbauer B, Bacher M, Rapp H, Langenbach P. “Associated postural adjustments with body movement in normal subjects and patients with parkinsonism and cerebellar disease,” Rev Neurol (Paris). [32] M. A. Fischler, R. C. Bolles. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM, vol. 24, pp. 381-395, 1981. [33] M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking,”IEEE Transactions onSignal Processing, vol.50, no.2, pp.174-188,Feb. 2002. [34] M. Isard and A. Blake, 'CONDENSATION—Conditional Density Propagation for Visual Tracking,' International Journal of Computer Vision, vol. 29, pp. 5-28, 1998. [35] N. Gordon, D. Salmond, and A. Smith, 'Novel approach to nonlinear/non-Gaussian Bayesian state estimation,' IEE Proceedings, vol. 140, pp. 107-113, 1993. [36] M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, 'A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,' Signal Processing, IEEE Transactions on, vol. 50, pp. 174-188, 2002. [37] J. MacCormick and M. Isard, 'Partitioned sampling, articulated objects and interface-quality hand tracking,' Lecture Notes in Computer Science, vol. 1843, pp. 3-19, 2000. [38] R. Navaratnam, A. Thayananthan, P. Torr, and R. Cipolla, 'Hierarchical part-based human body pose estimation,' in Pattern Analysis, Statistical Modelling and Computational Learning Oxford, UK, 2005. [39] R.W, Bohannon., J. Bear-Legman., J. Desrosiers., N. Massy-Westropp., V. Mathiowetz. 'Average Grip Strength- A Meta-Analysis of Data Obtained with a Jamar Dynamometer from Individuals 75 Years or More of Age', J Geriatr Phys Ther, 2007 [40] Susu Jiang, Bofeng Zhang, Daming Wei “The Elderly Fall Risk Assessment and Prediction Based on Gait Analysis,” Computer and Information Technology (CIT), 2011 [41] Pressley, J. C., E. D. Louis, et al. (2003). 'The impact of comorbid disease and injuries on resource use and expenditures in parkinsonism.'Neurology 60(1): 87-93. [42] Guimaraes RM, Isaacs B:Characteristics of the gait in old people who fall. Int Rehabil Med 1980,2:177-180. [43] J. A. Grahn and M. Brett, 'Impairment of beat-based rhythm discrimination in Parkinson's disease', Cortex, VoI.45-1, pp.54-61,2009. [44] Hirotaka Uchitomi, Yoshihiro Miyake, Satoshi Orimo, Yoshiaki Wada, Kazuki Suzuki, Michael J Hove and Tatsunori Nishi, “Interpersonal Synchrony-based Dynamic Stabilization in Walking Rhythm of Parkinson's Disease,” Proceedings of the 2011 IEEE/ICME International Conference on Complex Medical Engineering [45] M. E. Morris, R. Iansek, T. A. Matyas, Summers, JJ. “Stride length regulation in Parkinson’s disease: normalization strategies and underlying mechanisms”. Brain. (1996), 119(pt 2):551–568 [46] Wei-Hao Mou, Ming-Fang Chang, Chien-Ke Liao, Yuan-Han Hsu and Li-Chen Fu, Fellow, IEEE, “Context-Aware Assisted Interactive Robotic Walker for Parkinson’s Disease Patients”, Intelligent Robots and Systems (IROS), 2012 [47] M. Stamp, A revealing introduction to hidden Markov models'. (2004) www.cs.sjsu.edu/faculty/stamp/RUA/HMM.pdf [48] M. Stamp, “A Revealing Introduction to Hidden Markov Models,”April 2012 [49] Baum LE: An equality and associated maximization technique in statistical estimation for probabilistic functions of Markov processes. Inequalities 1972, 3:1-8. [50] M. J. F. Gales, “The Generation and use of Regression Class Trees for MLLR Adaptation”. Technical Report, Cambridge University, August 1996 [51] H. K Wu, H. R Chen, C. H Yu, “Development of Posterior Walker with Adjustable Visual Cues to Improve Gait Performance for Patients with Parkinson’s Disease”. IECON (Jan. 2010), 1512–1516 [52] E. Cubo , CG. Moore , S. Leurgans , CG. Goetz, “Wheeled and standard walkers in Parkinson’s disease patients with gait freezing”. Parkinsonism & Related Disorders (Oct. 2003), 10:9–14 [53] Y. C Huang, H.PYang, C. H. Ko, K. Y. Young, “Human intention recognition for robot walking helper using ANFIS”. Asian Control Conference, (May. 2011), 311-316 [54] Lynn Rochester, David J. Burn, Gillian Woods, Jon Godwin, Alice Nieuwboer “Does auditory rhythmical cueing improve gait in people with Parkinson's disease and cognitive impairment? A Feasibility study,” Movement Disorders, Volume 24, Issue 6, pages 839–845, 30 April 2009 [55] National Parkinson Foundation - http://www.parkinson.org/ [56] Hoehn, M. Margaret, Yahr, D. Melvin, 'Parkinsonism: onset, progression and mortality', Neurology. 2001, Vol 57, S11-S26 [57] Jennifer Barry, Leslie Pack Kaelbling, Tomas Lozano-Perez, “A Hierarchical Approach to Manipulation with Diverse Actions,” ICRA 2013 [58] J. Barry, K. Hsiao, L. Kaelbling, and T. Lozano-P′erez, “Manipulation with Multiple Action Types,” in ISER, 2012 [59] J. M. Hausdorff, D. A. Rios, H. K. Edelberg, 'Gait Variability and Fall Risk in Community-Living OlderAdults', Arch Phys Med Rehabil Vol 82, August 2001 [60] A. Contreras, F. Grandas, 'Risk of Falls in Parkinson’s Disease: A Cross-Sectional Studyof 160 Patients', Hindawi Publishing Corporation Parkinson’s Disease, Volume 2012. [61] Gwyn N. Lewis, Winston D. Byblow and Sharon E. Walt “Stride length regulation in Parkinson’s disease: the use of extrinsic, visual cues,” Brain (2000) 123 (10): 2077-2090. doi: 10.1093/brain/123.10.2077 [62] Giuseppe Frazzitta, Roberto Maestri, Davide Uccellini, Gabriella Bertotti, and Paola Abelli “Rehabilitation Treatment of Gait in Patients with Parkinson’s Disease with Freezing: A Comparison Between Two Physical Therapy Protocols Using Visual and Auditory Cues with or Without Treadmill Training,” Movement Disorders Vol. 24, No. 8, 2009, pp. 1139–1143 [63] S. Jiang, B. Zhang, D. Wei, 'The Elderly Fall Risk Assessment and Prediction Based on Gait Analysis', IEEE CIT (2011). [64] Hough P.V.C., Method and mean for recognizing complex patterns. U.S. Patents 3,069,654, 1962. [65] D. Arthur and S. Vassilvitskii, “K-Means++:TheAdvantages of Careful Seeding,”ACM-SIAM Symposium on Discrete algorithms, pp. 1027-1035, Jan. 2007. [66] E-Jui Weng , Li-Chen Fu, “On-line human action recognition by combining joint tracking and key pose recognition,” IROS 2012 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/17251 | - |
dc.description.abstract | 本篇論文提出了一個建置於主動式助行器機器人平台,基於步態分析的行走平衡復健系統。隨著社會人口高齡化現象益趨明顯,醫療照護人員不足的問題將變得更加嚴峻。因此,我們需要藉由步行輔助機器人協助照護人員來舒緩人手不足的困擾。對於很多年長者來說,行動不便於日常生活中造成非常大的困擾,因此,如何改善老人的行動力一直是個重要的議題,特別是對於巴金森氏症患者而言,他們在行走過程中會經常性的發生異常步態。為了改善巴金森氏症患者的行動力,我們必須觀察並分析他們的行走步態,並且針對異常步態做出對應的改善措施。因此在本篇論文中,我們將以患有巴金森氏症的使用者作為探討對象,建置一個以步態分析為基礎的行走平衡復健系統,在此系統中,不同於傳統上的輔助行走機器人,我們加入深度資訊感測器於使用者下肢前方作步態辨識。並配合改變輔助行走機器人的移動速率與發出配合使用者正常步態的頻率提示音等過程協助使用者脫離異常步態。我們也實際於安養中心請巴金森氏症長者測試此系統,結果顯示當巴金森氏症長者使用此系統輔助行走時,相較於不使用此系統時,呈現較穩定的步態。 | zh_TW |
dc.description.abstract | This thesis proposes a gait analysis based walking stabilization system on an active robotic walker for Parkinson’s Disease patients. Due to population aging, the demand of caregivers will be very insufficient in the future. Therefore, we need a robotic walker to help the caregivers. The improvement of elderly mobility has also been an important issue, especially for the Parkinson’s Disease patients. Most of the Parkinson’s Disease patients are suffer from losing balance and abnormal walking gaits, so we take Parkinson’s Disease patients as our user of the system. To improve the Parkinson’s Disease patient’s gait performance, we must comprehend the meaning of human gaits. Thus, we develop a gait analysis based walking stabilization system. Instead of using laser range finder or body-mounted sensors to estimate the walking motion, we use only one RGB-D sensor mounted on the robotic walker to capture the user’s lower limbs from the frontal view. After we captured the depth information of the lower part of body from the sensor, we automatically construct the skeleton of the lower limbs. By the kinematic model of the lower limbs, we can establish the user’s walking gait features such as average walking step length, velocity, width and joint angle. By adjusting walker's velocity and prompting user with auditory cues, the walker will help user to stabilize their gaits when they suffering from abnormal gaits. We invite Parkinson’s Disease patients to test our system in senior care unit, the experiment results show that when Parkinson’s Disease patients use this system, they have relatively stable gait than without using this system. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T00:03:06Z (GMT). No. of bitstreams: 1 ntu-102-R00922084-1.pdf: 4366547 bytes, checksum: a53533347f93602517c425959b173444 (MD5) Previous issue date: 2013 | en |
dc.description.tableofcontents | 口試委員會審定書 #
誌謝 i 中文摘要 ii ABSTRACT iii TABLE OF CONTENTS iv LIST OF FIGURES vii LIST OF TABLES ix Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Related Work 3 1.2.1 Robotic Walkers 3 1.2.2 Human Walking Gait Analysis 4 1.2.3 Walking Gait Recovering and Rehabilitation for Parkinson’s Disease Patients 6 1.3 System Overview 6 1.4 Objectives 8 1.5 Thesis Organization 9 Chapter 2 Preliminary 10 2.1 Parkinson’s Disease 10 2.2 Architecture of Active Assisting Walker 12 2.3 Particle Filter 14 2.3.1 Tracking Problem 14 2.3.2 Sequential Importance Sampling 15 2.3.3 Sampling Importance Resampling 16 Chapter 3 Gait Analysis based Walking Stabilization System 18 3.1 Gait Monitoring Module 18 3.1.1 Human Gait Configuration 18 3.1.2 Depth Image Pre-processing 19 3.1.3 Coordinate System Conversion 22 3.1.4 Construct 3D Skeleton 23 3.1.5 Particle Filter Based Human Gait Tracking 27 3.1.6 Construct Kinematic model 31 3.1.7 Gait Features Extraction 32 3.2 User Walking Gait Analysis Module 36 3.2.1 Force Analyzer 36 3.2.2 Gait Analyzer 39 3.2.3 Abnormal Gait Identification 40 3.3 Synchrony-Based Dynamic Stabilization Recovering Module 43 3.3.1 Walking Gait Synchrony Process 43 3.3.2 Robotic Walker Action Planner 45 Chapter 4 Experiments 51 4.1 Pretest 51 4.1.1 Parkinson’s Disease Patients Pre-Test 51 4.2 Parkinson’s Disease Patients Test 53 4.2.1 Experimental Setup 53 4.2.2 Standard Deviation of Walking Velocity 54 4.2.3 Standard Deviation of Cadence 56 Chapter 5 Conclusion 57 REFERENCE 58 | |
dc.language.iso | en | |
dc.title | 基於步態分析之巴金森氏症患者穩定行走系統 | zh_TW |
dc.title | Gait Analysis based Walking Stabilization System for Patients with Parkinson's Disease on a Robotic Walker | en |
dc.type | Thesis | |
dc.date.schoolyear | 101-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 宋開泰,練光祐,葉在庭,戴浩志 | |
dc.subject.keyword | 主動式輔助行走機器人,步態分析,巴金森氏症, | zh_TW |
dc.subject.keyword | Active robotic walker,Gait analysis,Parkinson’s Disease, | en |
dc.relation.page | 65 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2013-08-15 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
顯示於系所單位: | 資訊工程學系 |
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