Mobile Mining and Information Management in HealthNet Scenarios

  • Authors:
  • Philipp Kranen;David Kensche;Saim Kim;Nadine Zimmermann;Emmanuel Müller;Christoph Quix;Xiang Li;Thomas Gries;Thomas Seidl;Matthias Jarke;Steffen Leonhardt

  • Affiliations:
  • -;-;-;-;-;-;-;-;-;-;-

  • Venue:
  • MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
  • Year:
  • 2008

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Abstract

Health and mobility of elderly people is gaining importance in aging societies. New communication-based methods to provide health services with personal health care devices are considered promising elements of first-class medical care services for everybody. To achieve this vision, several technological issues have to be solved: (i) body sensors to monitor vital functions have to be developed; (ii) these sensors should be integrated into textile structures to guarantee ease of use and patient acceptance; (iii)the collected sensor data has to be analyzed to detect emergency situations and to reduce the data volume; (iv) relevant data has to be integrated with other information systems in the work environment of medical experts. These challenges are addressed within the HealthNet project at RWTH Aachen University. The goal of the project is to develop a framework in which health professional scan remotely monitor and diagnose mobile patients. The described demonstration presents our results of the first three issues mentioned above while focusing on the employed data mining and management techniques.