請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65145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 | Yu-Chiao Huang | en |
| dc.contributor.author | 黃雨喬 | zh_TW |
| dc.date.accessioned | 2021-06-16T23:27:00Z | - |
| dc.date.available | 2012-12-10 | |
| dc.date.copyright | 2012-12-10 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-07-31 | |
| dc.identifier.citation | [1] U.S. Census Bureau, International Database.
http://www.census.gov/ipc/www/idbpyr.html [2] T. Ezzati-Rice, D. Kashihara, and S. Machlin, Health Care Expenses in the United Sates, 2000, Agency for Healthcare Research and Quality, Report No.04-0022, 2004. [3] Health, United States, 2005 with chartbook on trends in the health of Americans, National Center for Health Statistics, 2005. [4] M.R. Endsley, Design and Evaluation for Situation Awareness Enhancement, Proceedings of the Human Factors Society 32nd Annual Meeting, Volume 1, pp.97-101, 1988. [5] N. Bricon-Souf and C.R. Newman, Context awareness in health care: A review, International Journal of Medical Informatics 76, pp.2-12, 2007. [6] Health Care’s Reservations about Cloud Computing, http://www.cloudtweaks.com/2011/06/health-care%E2%80%99s-reservations-about-cloud-computing/ [7] J.E. Bardram, H. Baldus, and J. Favela, Pervasive Computing in Hospitals, in Pervasive Computing in Healthcare(eds. J.E. Bardram, A. Mihalidis, D. Wan), CRC Press, 2007. [8] C.H. Lu and L.C. Fu, Robust Location-Aware Activity Recognition Using Wireless Sensor Networks in an Attentive Home, IEEE Transactions on Automation Science and Engineering, April. 2008. [9] J. Dean and J. Ghemawat, MapReduce: Simplified Data Processing on Large Clusters, In the Proceedings of the 6th Symp. on Operating Systems Design and Implementation, Dec. 2004. [10] A.K. Dey and G.D. Abowd, Towards a Better Understanding of Context and Context-awareness, In the Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing, pp.304-307, 1999. [11] L. Chen and I. Khalil, Activity Recognition: Approaches, Practices and Trends. In: Activity Recognition in Pervasive Intelligent Environments, Atlantis Ambient and Pervasive Intelligence, pp. 1-32, 2011. [12] J. Bardram, Applications of context-aware computing in hospital work-examples and design principles, In the Proceedings of SAC, Cyprus, March 14-17, 2004. [13] J. Kjeldskov and M. Skov, Supporting work activities in healthcare by mobile electronic patient records, In the Proceedings of the 6th Asia-Pacific Conference on Human Computer Interaction, APCHI, 2004. [14] H. Neal, EHR vs EMR – What’s the Difference, http://blog.softwareadvice.com/articles/medical/ehr-vs-emr-whats-the-difference/ [15] http://www.hl7.org/ [16] http://www.nlm.nih.gov/research/umls/Snomed/snomed_main.html [17] L. Frank and S.K. Anderson, Evaluation of Different Database Designs for Integration of Heterogeneous Distributed Electronic Health Records, IEEE/ICME International Conference on Complex Medical Engineering, July 13-15. 2010. [18] M. Shankar and C. Tomkins-Tinch, Design and Implementation of an Extensible Annotation Scheme for Health Informatics Data, ACM SIGHIT International Health Informatics Symposium, Miami, South Dakota, January 28-30, 2012. [19] Requirements for an Electronic Health Record Reference Architecture, ISO/WD 18308. [20] H.SF. Fraser et al, Implementing Electronic Medical Record Systems in Developing Countries, Informatics in Primary Care, Volumn 13, pp.83-95, 2005. [21] Y. Jin, T. Deyu, and Z. Yi, A Distributed Storage Model for EHR Based on HBase, International Conference on Information Management, Innovation Management and Industrial Engineering, 2011. [22] P. Mell and T. Grance, The NIST Definition of Cloud Computing. [23] http://aws.amazon.com/ec2 [24] http://aws.amazon.com/s3 [25] O. Shimrat, Cloud Computing and Healthcare: Bad Weather or Sunny Broadcast, San Diego Physician.org, April 2009. [26] http://www.microsoft.com/en-gb/healthvault/default.aspx [27] http://www.google.com/health [28] S. Hisashi, S. Kenji, K. Takayuki, and N. Shoji, Realization of the High-density SaaS Infrastructure with a Fine-grained Multi-tenant Framework, NEC Technical Journal, Special Issue on Cloud Computing, No.2, June 2010. [29] F. Chang et al, Bigtable: A Distributed Storage System for Structured Data, ACM Transactions on Computer Systems (TOCS), Volume 26 Issue 2, June 2008. [30] http://hbase.apache.org/ [31] http://cassandra.apache.org/ [32] S. Aulbach, T. Grust, D. Jacobs, A. Kemper, and J. Rittinger, Multi-Tenant Databases for Software as a Service: Schema-Mapping Techniques, In the Proceedings of the 2008 ACM SIGMOD international conference on Management of data, pp.1195-1206, 2008. [33] G.P. Copeland and S.N. Khoshafian. A decomposition storage model. In the Proceedings of the 1985 ACM SIGMOD international conference on Management of data, pp.268–279, 1985. [34] D. Maier and J.D. Ullman. Maximal objects and the semantics of universal relation databases. In the Proceedings of ACM Transaction of Database Systems, Volumn 8, pp.1-14, 1983. [35] S.E. Brossette, A.P. Sprague, J.M. Hardin, K.B. Waites, W.T. Jones, and S.A. Moser, Association Rules and Data Mining in Hospital Infection Control and Public Health Surveillance, Journal of the American Medical Informatics Association, Volumn 5, No.4, July/August 1998. [36] K. Wang, L. Tang, J. Han, and J, Liu, Top Down FP-Growth for Association Rule Mining, Lecture Notes in Computer Science, Volume 2336/2002, pp. 334-340, 2002. [37] M. Baldauf, S. Dustdar, and F. Rosenberg, A Survey on Context-aware Systems, Journal of Ad-hoc abd Ubiquitous Computing, Volume 2, No.4, 2007. [38] S. Mitchell, M. Spiteri, J. Bates, and G. Coulouris, Context-aware Multimedia Computing in the Intelligent Hospital, In the Proceedings of the Ninth ACM SIGOPS European Workshop, September 2000. [39] M. Munoz, M. Rodriguez, J. Favela, A. Martinez-Garcia, and V. Gonzalez, Context-aware Mobile Communication in Hospitals, IEEE Journal of Computer, Volumn 36, Issue 9, pp. 38-46, September 2003. [40] T. Gu et al, A Pattern Mining Approach to Sensor-Based Human Activity Recognition, IEEE Transaction on Knowledge and Data Engineering, Volume 23, No.9, Sep. 2011. [41] Y.C. Yen, Human-centric and Situation-aware Pervasive Healthcare System in the Hospital for Elderly People, 2011. (Master thesis) [42] R. Zhang and L. Liu, Security Models and Requirements for Healthcare Application Clouds, IEEE 3rd International Conference on Cloud Computing, 2010. [43] J. Sun and Y. Fang, Cross-domain Data Sharing in Distributed Electronic Health Record Systems, IEEE Transactions on Parallel and Distributed Systems, Volume 21, No.6, June 2010. [44] D. Patra, S. Ray, J. Mukhopadhyay, B. Majumdar, and A.K. Majumdar, Achieving e-Health Care in a Distributed EHR System, IEEE 11th International Conference on Healthcom, pp.101-107, December 2009. [45] A. Agarwal, N. Henehan, V. Somashekarappa, A.S. Pandya, H. Kalva, and B. Furht, A Cloud Computing Based Patient Centric Medical Information System, Handbook of Cloud Computing (eds. B. Furht and A. Escalante), 2010. [46] T. Beale and S. Heard, openEHR Architecture: Architecture Overview. http://www.openehr.org/releases/1.0.1/architecture/overview.pdf [47] D.B. Hoang and L. Chen, Mobile Cloud for Assistive Healthcare (MoCAsH), In the Proceedings of APSCC, pp.325-332, 2010. [48] L. Fan, W. Buchanan, C. Thummler, O. Lo, A. Khedim, O. Uthmani, A. Lawson, and D. Bell, DACAR Platform for eHealth Service Cloud, IEEE 4th International Conference on Cloud Computing, pp.219-226, 2011. [49] G. Hohpe and B. Woolf, Enterprise Integration Patterns, Addison Wesley, 2004. [50] Roystonea, from National Taiwan University, http://roystonea.csie.ntu.edu.tw [51] T. Condie, N. Conway, P. Alvaro, M.J. Hellerstein, K. Elmeleegy and R. Sears, MapReduce Online, 7th USENIX Symposium on Networked Systems Design and Implementation, 2010. [52] E. Gamma, R. Helm, R. Johnson, and J. Vlissides, Design Patterns: Elements of Reusable Object-Oriented Software, Addison-Wesley, 1994. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65145 | - |
| dc.description.abstract | 健康照護產業正在經歷兩個突破性的技術發展整合：情境感知功能與雲端運算技術。情境感知的照護系統可獲取環境中物體與人員的情境資訊做為決策的輔助，但多數此類的研究並不重視真實世界中的實際性，當中的許多個案甚至因為使用的情境資訊的無結構性而造成與使用者的真實意圖背離。雲端運算技術則是另一個廣為人知的技術，用以將各式的資源抽象化至網際網路上的服務，並以此提供這些服務可規模性與可取得性。然而，雲端特性中的多租戶技術並不容易實作，要將雲端與電子健康紀錄(EHR)做良好的整合更不是一件易事。整體來看，同時兼顧這兩樣技術的健康照護研究就更加的少了。
在這篇論文中，我們將提出一個狀況感知的醫療雲架構。這個架構對於最終的醫療服務使用者(即病人與其看護者)而言是隱蔽的。整個醫療雲架構包括幾個主要區塊：狀況感知的智慧病房與其框架、多租戶的狀況/電子健康紀錄資訊的雲端資料庫，以及支持大規模資料分析並提供呵護服務的雲端平台。我們所提出的狀況感知醫療雲架構也將會處理許多在情境感知科技與雲端運算科技上數項仍存在的核心問題。此外，在本論文中所提出的醫療雲架構將會建置於真實世界中存在的環境(臺灣大學醫院病房)，該架構的可用性評估與效果分析也將會依存於這個以部屬的醫療雲原型上。 | zh_TW |
| dc.description.abstract | Healthcare IT is experiencing two main revolutionary changes: context-awareness and cloud computing. Context-aware healthcare systems gather nearby information of entities and determine their actions accordingly. But researches for these systems usually neglect the practicability issue in the real world, and many of them may have user intention deviation because of the unorganized information used. Cloud computing is another well-known technique that abstracts resources to web services, and offering greater scalability and availability. However, being an essential characteristic of cloud systems, multi-tenancy is not a trivial concept. Also there exist other difficulties that hinder further integration of electronic health record (EHR) systems and the cloud. There are even fewer healthcare-related works that take care of both characteristics.
In this thesis, we propose a situation-aware medical cloud architecture that is ambient to patients and caregivers, who are the ultimate healthcare service customers of the proposed medical cloud. The medical cloud includes deployed situation-aware smart wards, a multi-tenant database for situation/EHR information persistence, and a caring service cloud platform for large-scale data analysis and caring services delivering. The proposed architecture should address several central challenges of context-aware systems and cloud computing. Also the proposed solution will be backed up by a deployed prototype in real world, says, a National Taiwan University Hospital (NTUH) ward. Usability assessments and performance evaluation will also be done based on the same prototype to assess real-world usability of the proposed system. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T23:27:00Z (GMT). No. of bitstreams: 1 ntu-101-R99922061-1.pdf: 1827215 bytes, checksum: 2a1e75a710d482539139029bb37a1bdb (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | 誌謝 ii
中文摘要 iv Abstract v Relevant Publications vi Table of Contents viii List of Figures xi List of Tables xii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Challenges 3 1.2.1 Context-aware Healthcare IT 3 1.2.2 Cloud-based Healthcare IT 4 1.3 Objectives and Contributions 5 1.4 Thesis Organization 7 Chapter 2 Preliminaries and Related Works 9 2.1 Preliminaries 9 2.1.1 Situation-awareness 9 2.1.2 Activity Recognition 10 2.1.3 Electronic Health Records (EHR) 11 2.1.4 Cloud Computing 13 2.1.5 Data-layer Multi-tenancy 15 2.1.6 Association Rule Mining 16 2.2 Related Works 18 2.2.1 Context-aware Prototypes in Wards 18 2.2.2 EHR Systems and Data Layouts 21 2.2.3 Medical Cloud Researches 23 Chapter 3 Situation-aware Smart Ward Technology 25 3.1 Proposed Architecture 25 3.2 Deployed Prototype 30 3.3 Situation-enabled Caring Applications 34 3.3.1 Situation Alerting 34 3.3.2 Situation Reporting 35 3.4 Lessons Learned 36 Chapter 4 Medical Cloud Technologies 39 4.1 Hybrid EHR Database Design 39 4.1.1 Proposed Architecture 41 4.1.2 Query Types and Query Handling 44 4.2 Cloud-enabled Caring Applications 47 4.2.1 Community Health Quality Promotion 47 4.2.2 Chronic Illness Alerting 49 4.3 Infrastructure for Caring Service Cloud 50 4.3.1 Proposed Infrastructure 50 4.3.2 Sequence Diagram for Request Handling 53 Chapter 5 Experiments 55 5.1 Situation-aware Smart Wards 55 5.1.1 Assessment Context 56 5.1.2 Assessment Results 57 5.2 Medical Cloud Storage 58 5.2.1 Environmental Setting 58 5.2.2 Time Efficiency 60 5.2.3 Space Efficiency 63 5.3 Cloud-based Healthcare Applications 64 5.3.1 Usability Assessment 65 5.3.2 Economical Practicability 65 Chapter 6 Conclusion 67 6.1 Summary 67 6.2 Future Works 69 REFERENCE 71 | |
| dc.language.iso | en | |
| dc.subject | 非關聯式資料庫 | zh_TW |
| dc.subject | 資訊探勘 | zh_TW |
| dc.subject | 狀況感知 | zh_TW |
| dc.subject | 情境感知 | zh_TW |
| dc.subject | 普及健康照護 | zh_TW |
| dc.subject | 多租戶技術 | zh_TW |
| dc.subject | multi-tenancy | en |
| dc.subject | context-aware | en |
| dc.subject | situation-aware | en |
| dc.subject | NoSQL database | en |
| dc.subject | data mining | en |
| dc.subject | pervasive healthcare | en |
| dc.title | 真實環境中之整合式情境感知智慧照護醫療雲之實作 | zh_TW |
| dc.title | Situation-aware Medical Clouds:Towards a Real-World Integrated Contextual Healthcare Environment | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 馮明惠(Ming-Hui Feng),陳佳慧(Chia-Hui Chen),蘇木春(Mu-Chun Su),蘇雅韻(Ya-Yun Su) | |
| dc.subject.keyword | 普及健康照護,情境感知,狀況感知,非關聯式資料庫,資訊探勘,多租戶技術, | zh_TW |
| dc.subject.keyword | pervasive healthcare,context-aware,situation-aware,NoSQL database,data mining,multi-tenancy, | en |
| dc.relation.page | 76 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2012-07-31 | |
| 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 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-101-1.pdf 未授權公開取用 | 1.78 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。