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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 劉佩玲 | |
| dc.contributor.author | Li-Li Wang | en |
| dc.contributor.author | 王力立 | zh_TW |
| dc.date.accessioned | 2021-06-13T01:08:55Z | - |
| dc.date.available | 2016-08-10 | |
| dc.date.copyright | 2011-08-10 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-08-03 | |
| dc.identifier.citation | [1] 梁煙純. (2006) 12招預防老人跌倒. 康健雜誌.
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Anderson, et al., 'Recognizing Falls from Silhouettes,' in Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE, 2006, pp. 6388-6391. [10] N. Thome and S. Miguet, 'A HHMM-Based Approach for Robust Fall Detection,' in Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on, 2006, pp. 1-8. [11] C. Rougier, et al., 'Monocular 3D Head Tracking to Detect Falls of Elderly People,' in Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE, 2006, pp. 6384-6387. [12] M. Alwan, et al., 'A Smart and Passive Floor-Vibration Based Fall Detector for Elderly,' in Information and Communication Technologies, 2006. ICTTA '06. 2nd, 2006, pp. 1003-1007. [13] L. Klack, et al., 'Future Care Floor: A sensitive floor for movement monitoring and fall detection in home environments,' presented at the Wireless Mobile Communication and Healthcare-MobiHealth, 2010. [14] R. Henry, et al., 'Human tracking using near field imaging,' in Pervasive Computing Technologies for Healthcare, 2008. PervasiveHealth 2008. Second International Conference on, 2008, pp. 148-151. [15] H. Rimminen, et al., 'Detection of Falls Among the Elderly by a Floor Sensor Using the Electric Near Field,' Information Technology in Biomedicine, IEEE Transactions on, vol. 14, pp. 1475-1476, 2010. [16] A. Sixsmith and N. Johnson, 'A smart sensor to detect the falls of the elderly,' Pervasive Computing, IEEE, vol. 3, pp. 42-47, 2004. [17] A. Sixsmith, et al., 'Pyroelectric IR sensor arrays for fall detection in the older poplation,' J. Phys. IV France, pp. 153-160, 2005. [18] M. Popescu, et al., 'An acoustic fall detector system that uses sound height information to reduce the false alarm rate,' in Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE, 2008, pp. 4628-4631. [19] C. Doukas and I. Maglogiannis, 'Advanced patient or elder fall detection based on movement and sound data,' in Pervasive Computing Technologies for Healthcare, 2008. PervasiveHealth 2008. Second International Conference on, 2008, pp. 103-107. [20] O. Almeida, et al., 'Dynamic Fall Detection and Pace Measurement in Walking Sticks,' presented at the Proceedings of the 2007 Joint Workshop on High Confidence Medical Devices, Software, and Systems and Medical Device Plug-and-Play Interoperability, 2007. [21] 劉德明, et al., '遠距居家照護之跌倒昏迷偵測系統研究,' presented at the 臺灣國際醫學資訊聯合研討會, 台北,臺灣, 2008. [22] C. Yung-Chin and L. Yi-Wen, 'Indoor RFID gait monitoring system for fall detection,' in Aware Computing (ISAC), 2010 2nd International Symposium on, 2010, pp. 207-212. [23] N. Noury, et al., 'A smart sensor based on rules and its evaluation in daily routines,' in Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE, 2003, pp. 3286-3289 Vol.4. [24] N. Noury, et al., 'Fall detection - Principles and Methods,' in Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, 2007, pp. 1663-1666. [25] A. M. Tabar, et al., 'Smart home care network using sensor fusion and distributed vision-based reasoning,' presented at the Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks, Santa Barbara, California, USA, 2006. [26] K. Pahlavan, et al., 'Indoor geolocation science and technology,' Communications Magazine, IEEE, vol. 40, pp. 112-118, 2002. [27] P. Prasithsangaree, et al., 'On indoor position location with wireless LANs,' in Personal, Indoor and Mobile Radio Communications, 2002. The 13th IEEE International Symposium on, 2002, pp. 720-724 vol.2. [28] P. Bahl and V. N. Padmanabhan, 'RADAR: an in-building RF-based user location and tracking system,' in INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies. 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[34] 葉建宏, '觸動開關之觸感測試機開發,' 碩士論文, 機械工程研究所, 國立大同大學, 2008. [35] http://www.dribin.org/dave/keyboard/one_html/ [36] http://insight.ntu.edu.tw/VROpenlab/Demo_0202.htm [37] C. L. Vaughan, et al., Dynamics of Human Gait: Kiboho, 1992. [38] U. Lindemann, et al., 'Evaluation of a fall detector based on accelerometers: A pilot study,' Medical and Biological Engineering and Computing, vol. 43, pp. 548-551, 2005. [39] http://www.mech.utah.edu/ergo/pages/Educational/safety_modules/ctd- anthropometry/index.html | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/29507 | - |
| dc.description.abstract | 由於現今醫療衛生技術日新月異，使得人類平均壽命越來越長，高齡人口快速增加，在高齡人口越來越多的情況下，老人照護的課題也備受重視。跌倒意外對於老年人而言，是危害健康的主要來源之一，尤其是對於獨居老年人來說，跌倒意外所造成的損傷更是嚴重。因此，如何防止老年人跌倒或降低跌倒所造成的損傷也成為國內外重要的研究議題。
本論文針對老人跌倒之議題，提出一個室內跌倒偵測系統的架構實作，希望開發出一種無需額外攜帶物品、適合使用於不同室內環境，且可讓使用者自行佈置之定位系統，並透過此系統偵測老人是否發生跌倒之意外事故，以便在老人跌倒時能夠提供最及時的幫助，得以將傷害降到最低。 在硬體方面，本研究利用開發的定位地板模組以及微處理器來實現室內定位方法中的實體接觸形式之概似法(proximity method)，此方法是利用使用者自身重量去觸動地板下的開關，並藉由微處理器去進行定位掃描法來得知其所在位置。另外，本研究開發之模組具備能讓使用者可依各自需求而能自由拆裝之功能、系統架設成本不會太過高昂且易佈置於各樣環境等特性。 在軟體方面，本研究使用MATLAB撰寫應用程式，包含即時定位監控以及定位歷程調閱兩大功能。其中即時定位監控可讓使用者進行即時室內定位，並會偵測室內人員是否發生跌倒事故，即時定位監控之功能包含控制微處理器的指令下達、定位掃描碼的分析、跌倒辨識以及定位和偵測結果的呈現。定位歷程調閱則是將之前定位的資料取出並做定位呈現，此功能可拿來做個人行為分析。 系統進行跌倒意外之辨識方法是先利用不同時間下定位結果的相關係數來判斷被定位者是否處在靜止狀態，當被定位者處在靜止狀態時，除了分析靜止的特徵之外，還一併分析靜止前兩秒之運動狀態，藉此來判斷其靜止狀態是否有可能是個案發生嚴重的跌倒所致。 本研究最後將系統架設於一室內空間，實際測試其定位以及跌倒辨識之性能。實驗證實了此定位系統的可行性，並找出會造成定位誤差之原因，例如地板的開關會因彈性疲勞而失去彈力，無法回復至斷路的狀態，造成系統誤判。在跌倒辨識的實驗裡，發現雖然定位系統的空間解析度不佳，無法從靜止時的靜態特徵得知個案確切的姿勢，但與動態特徵相比對後，仍然可以將跌倒事件偵測出來。 總結來說，本系統具備架設容易、成本合理以及定位功能無須額外攜帶物品等優點，若能有效改善地板模組的缺點，例如：開關彈性疲乏、地板與地板之間電路的連通等，便可實際應用於居家照護以及智慧家庭中。 關鍵詞：室內定位、實體接觸式概似法、跌倒偵測、老年人居家照護 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-06-13T01:08:55Z (GMT). No. of bitstreams: 1 ntu-100-R97543050-1.pdf: 11637343 bytes, checksum: 2e4424304d6d999defb8603ef00a61fb (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 致謝 I
摘要 II 目錄 IV 圖目錄 VI 表目錄 X 第一章 前言 1 1.1 研究動機與目的 1 1.2 文獻回顧 3 1.2.1跌倒辨識系統 3 1.2.2位置追蹤 6 1.3 內容大綱 9 第二章 定位方法與系統 14 2.1 定位方法 16 2.2 系統硬體開發 17 2.2.1微處理器 (MCU) 17 2.2.2定位地板模組 20 2.3 系統軟體 25 2.3.1即時定位(Real Time Tracking Display) 26 2.3.2定位歷程(Trace History Display) 30 2.4 定位系統測試 32 2.5 定位系統擴充性 33 第三章 姿態特徵擷取及辨識 61 3.1 站立、步行及跌倒之特徵 61 3.1.1 靜態特徵 62 3.1.2 動態特徵 69 3.2 辨識法則 72 3.2.1運動狀態判斷 73 3.2.2靜止姿態判斷 73 3.2.3行走判斷 74 3.2.4靜止前動作緩急判斷 74 4.1 實驗架設 103 4.1.1 實驗環境 103 4.1.2 實驗規劃 103 4.2 實驗結果與討論 104 第五章 結論與未來展望 121 5.1結論 121 5.2未來展望 123 參考文獻 126 | |
| dc.language.iso | zh-TW | |
| dc.subject | 老年人居家照護 | zh_TW |
| dc.subject | 跌倒偵測 | zh_TW |
| dc.subject | 室內定位 | zh_TW |
| dc.subject | 實體接觸式概似法 | zh_TW |
| dc.subject | position monitoring | en |
| dc.subject | fall detection | en |
| dc.subject | pattern recognition | en |
| dc.subject | sensor floor | en |
| dc.title | 室內定位及跌倒辨識系統之開發 | zh_TW |
| dc.title | The development of the indoor localization and fall-detection system | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 吳文中 | |
| dc.contributor.oralexamcommittee | 林光華 | |
| dc.subject.keyword | 室內定位,實體接觸式概似法,跌倒偵測,老年人居家照護, | zh_TW |
| dc.subject.keyword | fall detection,sensor floor,position monitoring,pattern recognition, | en |
| dc.relation.page | 128 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2011-08-03 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 應用力學研究所 | zh_TW |
| 顯示於系所單位： | 應用力學研究所 | |
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| ntu-100-1.pdf 未授權公開取用 | 11.36 MB | Adobe PDF |
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