Annual Conference of KIPS (한국정보처리학회:학술대회논문집)

  • 2009.04a
  • /
  • Pages.399-400
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  • 2009
  • /
  • 2005-0011(pISSN)
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  • 2671-7298(eISSN)
Korea Information Processing Society (한국정보처리학회)
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An Interactive e-HealthCare Framework Utilizing Online Hierarchical Clustering Method

온라인 계층적 군집화 기법을 활용한 양방향 헬스케어 프레임워크

  • Musa, Ibrahim Musa Ishag (Database/Bioinformatics Laboratory, Chungbuk National University) ;
  • Jung, Sukho (Database/Bioinformatics Laboratory, Chungbuk National University) ;
  • Shin, DongMun (Database/Bioinformatics Laboratory, Chungbuk National University) ;
  • Yi, Gyeong Min (Database/Bioinformatics Laboratory, Chungbuk National University) ;
  • Lee, Dong Gyu (Database/Bioinformatics Laboratory, Chungbuk National University) ;
  • Sohn, Gyoyong (Database/Bioinformatics Laboratory, Chungbuk National University) ;
  • Ryu, Keun Ho (Database/Bioinformatics Laboratory, Chungbuk National University)
  • ;
  • 정석호 (충북대학교 데이터베이스연구실) ;
  • 신동문 (충북대학교 데이터베이스연구실) ;
  • 이경민 (충북대학교 데이터베이스연구실) ;
  • 이동규 (충북대학교 데이터베이스연구실) ;
  • 손교용 (충북대학교 데이터베이스연구실) ;
  • 류근호 (충북대학교 데이터베이스연구실)
  • Published : 2009.04.23
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Abstract

As a part of the era of human centric applications people started to care about their well being utilizing any possible mean. This paper proposes a framework for real time on-body sensor health-care system, addresses the current issues in such systems, and utilizes an enhanced online divisive agglomerative clustering algorithm (EODAC); an algorithm that builds a top-down tree-like structure of clusters that evolves with streaming data to rationally cluster on-body sensor data and give accurate diagnoses remotely, guaranteeing high performance, and scalability. Furthermore it does not depend on the number of data points.

Keywords