An Ambient Assisted Living System for Telemedicine with Detection of Symptoms

  • Authors:
  • A. J. Jara;M. A. Zamora-Izquierdo;A. F. Gomez-Skarmeta

  • Affiliations:
  • Faculty of Computer Science, Univ. Murcia, DIIC, Murcia, Spain 30100;Faculty of Computer Science, Univ. Murcia, DIIC, Murcia, Spain 30100;Faculty of Computer Science, Univ. Murcia, DIIC, Murcia, Spain 30100

  • Venue:
  • IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
  • Year:
  • 2009

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Abstract

Elderly people have a high risk of health problems. Hence, we propose an architecture for Ambient Assisted Living (AAL) that supports pre-hospital health emergencies, remote monitoring of patients with chronic conditions and medical collaboration through sharing of health-related information resources (using the European electronic health records CEN/ISO EN13606). Furthermore, it is going to use medical data from vital signs for, on the one hand, the detection of symptoms using a simple rule system (e.g. fever), and on the other hand, the prediction of illness using chronobiology algorithms (e.g. prediction of myocardial infarction eight days before). So this architecture provides a great variety of communication interfaces to get vital signs of patients from a heterogeneous set of sources, as well as it supports the more important technologies for Home Automation. Therefore, we can combine security, comfort and ambient intelligence with a telemedicine solution, thereby, improving the quality of life in elderly people.