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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃漢邦 | zh_TW |
| dc.contributor.advisor | Han-Pang Huang | en |
| dc.contributor.author | 王信逸 | zh_TW |
| dc.contributor.author | Hsin-Yi Wang | en |
| dc.date.accessioned | 2023-03-19T22:37:22Z | - |
| dc.date.available | 2023-12-26 | - |
| dc.date.copyright | 2022-09-12 | - |
| dc.date.issued | 2022 | - |
| dc.date.submitted | 2002-01-01 | - |
| dc.identifier.citation | [1] S. Lee and A. M. Naguib, "Toward a Sociable and Dependable Elderly Care Robot: Design, Implementation and User Study," Journal of Intelligent & Robotic Systems, vol. 98, no. 1, pp. 5-17, 2020. [2] G. Livingston, J. Huntley, A. Sommerlad, D. Ames, C. Ballard, S. Banerjee, C. Brayne, A. Burns, J. Cohen-Mansfield, C. Cooper, S. G. Costafreda, A. Dias, N. Fox, L. N. Gitlin, R. Howard, H. C. Kales, M. Kivimäki, E. B. Larson, A. Ogunniyi, V. Orgeta, K. Ritchie, K. Rockwood, E. L. Sampson, Q. Samus, L. S. Schneider, G. Selbæk, L. Teri, and N. Mukadam, "Dementia Prevention, Intervention, and Care: 2020 Report of the Lancet Commission," Lancet, vol. 396, no. 10248, pp. 413-446, 2020. [3] J. E. Ahlskog, Y. E. Geda, N. R. Graff-Radford, and R. C. Petersen, "Physical Exercise as a Preventive or Disease-Modifying Treatment of Dementia and Brain Aging," Mayo Clinic Proceedings, vol. 86, no. 9, pp. 876-884, 2011. [4] Z. Arvanitakis, R. C. Shah, and D. A. Bennett, "Diagnosis and Management of Dementia," Jama, vol. 322, no. 16, pp. 1589-1599, 2019. [5] L. Hung, M. Gregorio, J. Mann, C. Wallsworth, N. Horne, A. Berndt, C. Liu, E. Woldum, A. Au-Yeung, and H. Chaudhury, "Exploring the Perceptions of People with Dementia About the Social Robot Paro in a Hospital Setting," Dementia (London), vol. 20, no. 2, pp. 485-504, 2021. [6] L. Pu, W. Moyle, and C. Jones, "How People with Dementia Perceive a Therapeutic Robot Called Paro in Relation to Their Pain and Mood: A Qualitative Study," J Clin Nurs, vol. 29, no. 3-4, pp. 437-446, 2020. [7] H. Lv, G. Yang, H. Zhou, X. Huang, H. Yang, and Z. Pang, "Teleoperation of Collaborative Robot for Remote Dementia Care in Home Environments," IEEE Journal of Translational Engineering in Health and Medicine, vol. 8, no. 1400510, pp. 1-10, 2020. [8] K. H. Pitkälä, M. M. Pöysti, M. L. Laakkonen, R. S. Tilvis, N. Savikko, H. Kautiainen, and T. E. Strandberg, "Effects of the Finnish Alzheimer Disease Exercise Trial (Finalex): A Randomized Controlled Trial," JAMA Intern Med, vol. 173, no. 10, pp. 894-901, 2013. [9] M. Cooney, A. Orand, H. Larsson, J. Pihl, and E. E. Aksoy, "Exercising with an "Iron Man": Design for a Robot Exercise Coach for Persons with Dementia," 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), Naples, Italy, pp. 899-905, 2020. [10] T. Hamada, H. Kawakami, A. Inden, K. Onose, M. Naganuma, Y. Kagawa, and T. Hashimoto, "Physical Activity Rehabilitation Trials with Humanoid Robot," 2016 IEEE International Conference on Industrial Technology (ICIT), Taipei, Taiwan, pp. 1592-1596, 2016. [11] M. Schrum, C. H. Park, and A. Howard, "Humanoid Therapy Robot for Encouraging Exercise in Dementia Patients," 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Daegu, Korea, pp. 564-565, 2019. [12] T. B. Sheridan, "Human–Robot Interaction:Status and Challenges," Human Factors, vol. 58, no. 4, pp. 525-532, 2016. [13] Z. Hussain, M. Sheng, and W. E. Zhang, "Different Approaches for Human Activity Recognition: A Survey," arXiv preprint arXiv:1906.05074, 2019. [14] C. Torres-Huitzil and A. Alvarez-Landero, "Accelerometer-Based Human Activity Recognition in Smartphones for Healthcare Services," Mobile Health: A Technology Road Map, 1st ed. Switzerland: Springer International Publishing, pp. 147-169, 2015. [15] A. Wickramasinghe and D. C. Ranasinghe, "Ambulatory Monitoring Using Passive Computational Rfid Sensors," IEEE Sensors Journal, vol. 15, no. 10, pp. 5859-5869, 2015. [16] F. Hu, L. Wang, S. Wang, X. Liu, and G. He, "A Human Body Posture Recognition Algorithm Based on Bp Neural Network for Wireless Body Area Networks," China Communications, vol. 13, no. 8, pp. 198-208, 2016. [17] S. Ma, W. Cho, C. Quan, and S. Lee, "A Sitting Posture Recognition System Based on 3 Axis Accelerometer," 2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Chiang Mai, Thailand, pp. 1-3, 2016. [18] J. Wang, Z. Huang, W. Zhang, A. Patil, K. Patil, T. Zhu, E. J. Shiroma, M. A. Schepps, and T. B. Harris, "Wearable Sensor Based Human Posture Recognition," 2016 IEEE International Conference on Big Data (Big Data), Washington, DC, USA, pp. 3432-3438, 2016. [19] L. Yao, Q. Z. Sheng, X. Li, T. Gu, M. Tan, X. Wang, S. Wang, and W. Ruan, "Compressive Representation for Device-Free Activity Recognition with Passive Rfid Signal Strength," IEEE Transactions on Mobile Computing, vol. 17, no. 2, pp. 293-306, 2018. [20] M. Gochoo, T. H. Tan, S. C. Huang, T. Batjargal, J. W. Hsieh, F. S. Alnajjar, and Y. F. Chen, "Novel Iot-Based Privacy-Preserving Yoga Posture Recognition System Using Low-Resolution Infrared Sensors and Deep Learning," IEEE Internet of Things Journal, vol. 6, no. 4, pp. 7192-7200, 2019. [21] A. Iazzi, M. Rziza, and R. Oulad Haj Thami, "Fall Detection System-Based Posture-Recognition for Indoor Environments," Journal of Imaging, vol. 7, no. 3, p. 42, 2021. [22] A. Abobakr, M. Hossny, and S. Nahavandi, "A Skeleton-Free Fall Detection System from Depth Images Using Random Decision Forest," IEEE Systems Journal, vol. 12, no. 3, pp. 2994-3005, 2018. [23] M. U. Islam, H. Mahmud, F. B. Ashraf, I. Hossain, and M. K. Hasan, "Yoga Posture Recognition by Detecting Human Joint Points in Real Time Using Microsoft Kinect," 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), Dhaka, Bangladesh, pp. 668-673, 2017. [24] W. Ren, O. Ma, H. Ji, and X. Liu, "Human Posture Recognition Using a Hybrid of Fuzzy Logic and Machine Learning Approaches," IEEE Access, vol. 8, no. 1, pp. 135628-135639, 2020. [25] Z. Cao, G. Hidalgo, T. Simon, S. E. Wei, and Y. Sheikh, "Openpose: Realtime Multi-Person 2d Pose Estimation Using Part Affinity Fields," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 1, pp. 172-186, 2021. [26] A. Rejeb, J. G. Keogh, G. K. Leong, and H. Treiblmaier, "Potentials and Challenges of Augmented Reality Smart Glasses in Logistics and Supply Chain Management: A Systematic Literature Review," International Journal of Production Research, vol. 59, no. 12, pp. 3747-3776, 2021. [27] Y. Siriwardhana, P. Porambage, M. Liyanage, and M. Ylianttila, "A Survey on Mobile Augmented Reality with 5g Mobile Edge Computing: Architectures, Applications, and Technical Aspects," IEEE Communications Surveys & Tutorials, vol. 23, no. 2, pp. 1160-1192, 2021. [28] J. Carmigniani, B. Furht, M. Anisetti, P. Ceravolo, E. Damiani, and M. Ivkovic, "Augmented Reality Technologies, Systems and Applications," Multimedia Tools and Applications, vol. 51, no. 1, pp. 341-377, 2011. [29] M. Sereno, X. Wang, L. Besancon, M. J. Mcguffin, and T. Isenberg, "Collaborative Work in Augmented Reality: A Survey," IEEE Transactions on Visualization and Computer Graphics, vol. 28, no. 6, pp. 2530-2549, 2020. [30] S. Büttner, M. Prilla, and C. Röcker, "Augmented Reality Training for Industrial Assembly Work - Are Projection-Based Ar Assistive Systems an Appropriate Tool for Assembly Training?," Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA: Association for Computing Machinery, pp. 1–12, 2020. [31] T. Joda, G. O. Gallucci, D. Wismeijer, and N. U. Zitzmann, "Augmented and Virtual Reality in Dental Medicine: A Systematic Review," Computers in Biology and Medicine, vol. 108, no. 1, pp. 93-100, 2019. [32] V. Ivanov, A. Klygach, S. Shterenberg, S. Strelkov, and J. Levy, "Advances in Augmented Reality (Ar) for Medical Simulation and Training," 3C Tecnología. Glosas de innovación aplicadas a la pyme, vol. 1, no. 1, pp. 303-312, 2020. [33] I. Horváth, "Evolution of Teaching Roles and Tasks in Vr / Ar-Based Education," 2018 9th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), Budapest, Hungary, pp. 000355-000360, 2018. [34] Y. Wu, J. Xu, l. Li, D. Ge, and J. Zhang, "The Design of an Equipment Induction Maintenance System Based on Ar Technology," IOP Conference Series: Earth and Environmental Science, vol. 440, no. 3, p. 032041, 2020. [35] N. Yonov and D. Petkov, "Augmented Reality Navigation Map of Mountain Area," 8th International Conference on Cartography and GIS, Nessebar, Bulgaria, 2020. [36] G. Livingston, A. Sommerlad, V. Orgeta, S. G. Costafreda, J. Huntley, D. Ames, C. Ballard, S. Banerjee, A. Burns, and J. Cohen-Mansfield, "Dementia Prevention, Intervention, and Care," The Lancet, vol. 390, no. 10113, pp. 2673-2734, 2017. [37] M. Yoon, P.-S. Yang, M.-N. Jin, H. T. Yu, T.-H. Kim, E. Jang, J.-S. Uhm, H.-N. Pak, M.-H. Lee, and B. Joung, "Association of Physical Activity Level with Risk of Dementia in a Nationwide Cohort in Korea," JAMA Network Open, vol. 4, no. 12, pp. e2138526-e2138526, 2021. [38] R. Andel, M. Crowe, N. L. Pedersen, L. Fratiglioni, B. Johansson, and M. Gatz, "Physical Exercise at Midlife and Risk of Dementia Three Decades Later: A Population-Based Study of Swedish Twins," The Journals of Gerontology: Series A, vol. 63, no. 1, pp. 62-66, 2008. [39] C. S. Jensen, S. G. Hasselbalch, G. Waldemar, and A. H. Simonsen, "Biochemical Markers of Physical Exercise on Mild Cognitive Impairment and Dementia: Systematic Review and Perspectives," Frontiers in Neurology, Review vol. 6, no. 1, pp. 1-10, 2015. [40] C.-K. Law, F. M. H. Lam, R. C. K. Chung, and M. Y. C. Pang, "Physical Exercise Attenuates Cognitive Decline and Reduces Behavioural Problems in People with Mild Cognitive Impairment and Dementia: A Systematic Review," Journal of Physiotherapy, vol. 66, no. 1, pp. 9-18, 2020. [41] V. Bazarevsky, I. Grishchenko, K. Raveendran, T. Zhu, F. Zhang, and M. Grundmann, "Blazepose: On-Device Real-Time Body Pose Tracking," arXiv preprint arXiv:2006.10204, 2020. [42] Y. Cheng, B. Wang, B. Yang, and R. T. Tan, "Monocular 3d Multi-Person Pose Estimation by Integrating Top-Down and Bottom-up Networks," Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Nashville, TN, USA, pp. 7649-7659, 2021. [43] H. Xu, E. G. Bazavan, A. Zanfir, W. T. Freeman, R. Sukthankar, and C. Sminchisescu, "Ghum & Ghuml: Generative 3d Human Shape and Articulated Pose Models," Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA, pp. 6184-6193, 2020. [44] Y. Li, Z. Chu, and Y. Xin, "Posture Recognition Technology Based on Kinect," IEICE Transactions on Information and Systems, vol. 103, no. 3, pp. 621-630, 2020. [45] D. He and L. Li, "A New Kinect-Based Posture Recognition Method in Physical Sports Training Based on Urban Data," Wireless Communications and Mobile Computing, vol. 2020, no. 2020, pp. 1-9, 2020. [46] T. Sărătean, M. Antal, C. Pop, T. Cioara, I. Anghel, and I. Salomie, "A Physiotheraphy Coaching System Based on Kinect Sensor," 2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP), Cluj-Napoca, Romania, pp. 535-540, 2020. [47] L. A. Zadeh, G. J. Klir, and B. Yuan, Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers, 1st ed. Singapore: World Scientific, 1996. [48] M. Vlachos, G. Kollios, and D. Gunopulos, "Discovering Similar Multidimensional Trajectories," Proceedings 18th International Conference on Data Engineering, San Jose, CA, USA, pp. 673-684, 2002. [49] E. J. Keogh and M. J. Pazzani, "Derivative Dynamic Time Warping," Proceedings of the 2001 SIAM international conference on data mining, Chicago, IL, USA: SIAM, pp. 1-11, 2001. [50] H. P. H. S. R. Lu, "Implementation of Pre-Engagement Detection on Human-Robot Interaction in Complex Environments," Master, Graduate Institute of Mechanical Engineering, National Taiwan University, 2020. [51] J. Redmon and A. Farhadi, "Yolov3: An Incremental Improvement," arXiv preprint arXiv:1804.02767, 2018. [52] Y. S. W. a. H. P. Huang, "Human-Robot Interaction through Emotions and Eyes Gaze," Master, Graduate Institute of Mechanical Engineering, National Taiwan University, 2019. [53] T.-Y. Yang, Y.-T. Chen, Y.-Y. Lin, and Y.-Y. Chuang, "Fsa-Net: Learning Fine-Grained Structure Aggregation for Head Pose Estimation from a Single Image," Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA, pp. 1087-1096, 2019. [54] C. Feichtenhofer, H. Fan, J. Malik, and K. He, "Slowfast Networks for Video Recognition," Proceedings of the IEEE/CVF International Conference on Computer Vision, Seoul, Korea, pp. 6202-6211, 2019. [55] E. L. Brown, N. Ruggiano, J. Li, P. J. Clarke, E. S. Kay, and V. Hristidis, "Smartphone-Based Health Technologies for Dementia Care: Opportunities, Challenges, and Current Practices," Journal of Applied Gerontology, vol. 38, no. 1, pp. 73-91, 2019. [56] K. Hackett, S. Lehman, R. Divers, M. Ambrogi, L. Gomes, C. C. Tan, and T. Giovannetti, "Remind Me to Remember: A Pilot Study of a Novel Smartphone Reminder Application for Older Adults with Dementia and Mild Cognitive Impairment," Neuropsychological Rehabilitation, vol. 32, no. 1, pp. 22-50, 2022. [57] S. Fox, L. J. Brown, S. Antrobus, D. Brough, R. J. Drake, F. Jury, I. Leroi, A. R. Parry-Jones, and M. Machin, "Co-Design of a Smartphone App for People Living with Dementia by Applying Agile, Iterative Co-Design Principles: Development and Usability Study," JMIR mHealth and uHealth, vol. 10, no. 1, p. e24483, 2022. [58] K. Yousaf, Z. Mehmood, I. A. Awan, T. Saba, R. Alharbey, T. Qadah, and M. A. Alrige, "A Comprehensive Study of Mobile-Health Based Assistive Technology for the Healthcare of Dementia and Alzheimer’s Disease (Ad)," Health Care Management Science, vol. 23, no. 2, pp. 287-309, 2020. [59] B. Y. Zhang and M. Chignell, "A Person-Centered Design Framework for Serious Games for Dementia," Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 64, no. 1, pp. 18-22, 2020. [60] H. Ning, R. Li, X. Ye, Y. Zhang, and L. Liu, "A Review on Serious Games for Dementia Care in Ageing Societies," IEEE Journal of Translational Engineering in Health and Medicine, vol. 8, no. 1, pp. 1400411-1400411, 2020. [61] C. Hongmei, E. Agama, and Z. G. Prodanoff, "Developing Serious Games to Promote Cognitive Abilities for the Elderly," 2017 IEEE 5th International Conference on Serious Games and Applications for Health (SeGAH), Perth, WA, Australia, pp. 1-8, 2017. [62] K. Bojan, T. G. Stavropoulos, I. Lazarou, S. Nikolopoulos, I. Kompatsiaris, M. Tsolaki, E. Mukaetova-Ladinska, and A. Christogianni, "The Effects of Playing the Cosma Cognitive Games in Dementia," International Journal of Serious Games, vol. 8, no. 1, pp. 45-58, 2021. [63] S. Lehman, J. Graves, C. McAleer, T. Giovannetti, and C. C. Tan, "A Mobile Augmented Reality Game to Encourage Hydration in the Elderly," Human Interface and the Management of Information. Information in Applications and Services, Vancouver, Canada, S. Yamamoto and H. Mori, Eds., vol. 10905: Springer, Cham, pp. 98-107, 2018. [64] K. Han, K. Park, K.-H. Choi, and J. Lee, "Mobile Augmented Reality Serious Game for Improving Old Adults’ Working Memory," Applied Sciences, vol. 11, no. 17, p. 7843, 2021. [65] B. Aruanno and F. Garzotto, "Memholo: Mixed Reality Experiences for Subjects with Alzheimer’s Disease," Multimedia Tools and Applications, vol. 78, no. 10, pp. 13517-13537, 2019. [66] M. Leng, P. Liu, P. Zhang, M. Hu, H. Zhou, G. Li, H. Yin, and L. Chen, "Pet Robot Intervention for People with Dementia: A Systematic Review and Meta-Analysis of Randomized Controlled Trials," Psychiatry Res, vol. 271, no. 1, pp. 516-525, 2019. [67] A. Sampaio, E. A. Marques, J. Mota, and J. Carvalho, "Effects of a Multicomponent Exercise Program in Institutionalized Elders with Alzheimer's Disease," Dementia (London), vol. 18, no. 2, pp. 417-431, 2019. [68] Y. S. Kwak, S. Y. Um, T. G. Son, and D. J. Kim, "Effect of Regular Exercise on Senile Dementia Patients," Int J Sports Med, vol. 29, no. 6, pp. 471-4, 2008. [69] L. C. Lam, R. C. Chau, B. M. Wong, A. W. Fung, V. W. Lui, C. C. Tam, G. T. Leung, T. C. Kwok, H. F. Chiu, S. Ng, and W. M. Chan, "Interim Follow-up of a Randomized Controlled Trial Comparing Chinese Style Mind Body (Tai Chi) and Stretching Exercises on Cognitive Function in Subjects at Risk of Progressive Cognitive Decline," Int J Geriatr Psychiatry, vol. 26, no. 7, pp. 733-40, 2011. [70] A. Vreugdenhil, J. Cannell, A. Davies, and G. Razay, "A Community-Based Exercise Programme to Improve Functional Ability in People with Alzheimer's Disease: A Randomized Controlled Trial," Scand J Caring Sci, vol. 26, no. 1, pp. 12-9, 2012. [71] A. Sampaio, I. Marques-Aleixo, A. Seabra, J. Mota, and J. Carvalho, "Physical Exercise for Individuals with Dementia: Potential Benefits Perceived by Formal Caregivers," BMC Geriatrics, vol. 21, no. 1, p. 6, 2021. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/85000 | - |
| dc.description.abstract | 異常的認知功能退化，如失智症，是常見的發生於老年人的病症之一，近年來社會對其的研究與關注日益提升。而本論文針對輕度的認知功能障礙長者，開發了一個基於運動輔助與認知訓練遊戲的互動系統，旨在維持長者的認知能力。為實現輔助運動之功能，論文提出了四個核心模組，分別為：基於雙六軸機械手臂軌跡規劃的示範模組、基於3D人體姿態估計、模糊邏輯與最長公共子序列的姿態評分模組、基於多種卷積神經網路模型的專注度估測模組與增強人機互動性的回饋模組。以上四個模組整合於一台有雙六軸機械手臂的移動型機器人平台上，用於輔助使用者進行運動。另外，論文基於嚴肅遊戲的概念，結合擴增實境技術，在移動裝置上開發了一款無標記輔助的基於擴增實境的認知訓練遊戲，以用於長者的認知功能訓練。 為驗證系統的可行性與有效性，研究亦招募了十八位年齡在六十五歲以上的長者進行了一個為期八週的實驗。長者在實驗中需利用論文中提出的互動系統完成一系列的運動與認知訓練遊戲，完成蒙特利爾認知評估-台灣版(MoCA-T)的評估，及關於系統易用性及可接受度的問卷填寫。最終利用相關的統計學方法對實驗結果進行分析與討論。 | zh_TW |
| dc.description.abstract | Abnormal cognitive degeneration, such as dementia, is a common syndrome in older adults, which has also become a significant issue in aged society. Thus, an interaction system based on exercise assistance and cognitive training game is proposed for older adults with mild cognitive impairment to maintain their cognitive function. To accomplish exercise assistance, four significant modules are proposed in the thesis: A demonstration module based on trajectory planning of dual 6-DoF arms, a posture grading module based on 3D human pose estimation, fuzzy logic, and longest common subsequence, an engagement assessment module based on multiple CNN-based learning models, and a feedback module for enhancing the interactivity of the system. Four modules are integrated into a mobile robot with dual 6-DoF arms, which is utilized as an exercise coach. Besides, a markerless augmented-reality cognitive training game is developed on mobile devices for training the cognitive function of older adults. To verify the feasibility and efficacy of the system, eighteen older adults aging beyond sixty-five years old were recruited to an experiment lasting for eight weeks. In the experiment, the participants were required to accomplish an exercise program and cognitive training game with the assistance of the robot. Montreal Cognitive Assessment-Taiwanese (MoCA-T) was utilized as a cognitive testing tool for the participants. Also, some questionnaires are designed to be finished for assessment of system usability and acceptability. At the end of the thesis, the results of the experiment were analyzed by statistical methods and discussed. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T22:37:22Z (GMT). No. of bitstreams: 1 U0001-1108202217440400.pdf: 6448353 bytes, checksum: 0d58a93359cbd9b45ff33163a67ece06 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 誌謝 i 摘要 iii Abstract v List of Tables xi List of Figures xiii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Contributions 2 1.3 Organization of Thesis 3 Chapter 2 Relevant Research and Background Knowledge 5 2.1 Dementia Care with Robots 5 2.1.1 Companion Robot System 5 2.1.2 Assistance Robot System 6 2.1.3 Rehabilitation Robot System 7 2.2 Posture Recognition 9 2.2.1 Wearable-sensor-based Approaches 10 2.2.2 Non-wearable-sensor-based Approaches 11 2.3 Augmented Reality 15 2.3.1 Introduction 15 2.3.2 Applications 16 Chapter 3 Exercise Assistance System 19 3.1 Introduction 19 3.2 Demonstration Module 22 3.3 Posture Grading Module 25 3.3.1 Feature Extraction 25 3.3.2 Grading Mechanism 33 3.4 Engagement Assessment Module 44 3.5 Feedback Module 49 Chapter 4 Application Development on Mobile Device 51 4.1 Introduction 51 4.2 System Overview 51 4.3 Exercise Mode 54 4.4 Game Mode 57 4.4.1 Introduction to Serious Games 57 4.4.2 “Play with the Puppy” 62 Chapter 5 Simulations and Experiments 71 5.1 Hardware and Software 71 5.1.1 Hardware 71 5.1.2 Software 75 5.2 Implementations 77 5.2.1 Demonstration Module 78 5.2.2 Posture Grading Module 85 5.2.3 Engagement Assessment Module 99 5.2.4 Feedback Module 100 5.3 Applications 103 5.3.1 Introduction to Experiments 103 5.3.2 Discussion 108 Chapter 6 Conclusions and Future Works 113 6.1 Conclusions 113 6.2 Future Works 114 References 115 | - |
| dc.language.iso | en | - |
| dc.subject | 雙手臂機器人系統 | zh_TW |
| dc.subject | 姿態辨識 | zh_TW |
| dc.subject | 專注度 | zh_TW |
| dc.subject | 失智症 | zh_TW |
| dc.subject | 輕度認知功能障礙 | zh_TW |
| dc.subject | 人機互動 | zh_TW |
| dc.subject | 擴增實境 | zh_TW |
| dc.subject | 輕度認知功能障礙 | zh_TW |
| dc.subject | 失智症 | zh_TW |
| dc.subject | 雙手臂機器人系統 | zh_TW |
| dc.subject | 姿態辨識 | zh_TW |
| dc.subject | 專注度 | zh_TW |
| dc.subject | 人機互動 | zh_TW |
| dc.subject | 擴增實境 | zh_TW |
| dc.subject | Augmented-reality | en |
| dc.subject | Mild cognitive impairment | en |
| dc.subject | Dementia | en |
| dc.subject | Dual-Arm robot system | en |
| dc.subject | Posture recognition | en |
| dc.subject | Engagement | en |
| dc.subject | Human-robot interactions | en |
| dc.subject | Augmented-reality | en |
| dc.subject | Mild cognitive impairment | en |
| dc.subject | Dementia | en |
| dc.subject | Dual-Arm robot system | en |
| dc.subject | Posture recognition | en |
| dc.subject | Engagement | en |
| dc.subject | Human-robot interactions | en |
| dc.title | 基於運動輔助與認知訓練遊戲之面向輕度認知功能障礙長者的互動系統 | zh_TW |
| dc.title | Interaction System Based on Exercise Assistance and Cognitive Training Game for Older Adults with Mild Cognitive Impairment | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 110-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 程蘊菁;傅楸善;陳人豪;林峻永;蔣本基 | zh_TW |
| dc.contributor.oralexamcommittee | Yen-Ching Chen;Chiou-Shann Fuh;Jen-Hau Chen;Chun-Yeon Lin;Pen-Chi Chiang | en |
| dc.subject.keyword | 輕度認知功能障礙,失智症,雙手臂機器人系統,姿態辨識,專注度,人機互動,擴增實境, | zh_TW |
| dc.subject.keyword | Mild cognitive impairment,Dementia,Dual-Arm robot system,Posture recognition,Engagement,Human-robot interactions,Augmented-reality, | en |
| dc.relation.page | 121 | - |
| dc.identifier.doi | 10.6342/NTU202202307 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2022-08-19 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 機械工程學系 | - |
| dc.date.embargo-lift | 2024-08-20 | - |
| 顯示於系所單位： | 機械工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-110-2.pdf 授權僅限NTU校內IP使用（校園外請利用VPN校外連線服務） | 6.3 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。