Methods Inf Med 2014; 53(03): 167-172
DOI: 10.3414/ME13-02-0010
Focus Theme – Original Articles
Schattauer GmbH

Communication Architecture for AAL

Supporting Patient Care by Health Care Providers in AAL-enhanced Living Quarters
T. Nitzsche
1   University of Applied Sciences, Zwickau, Germany
,
S. Thiele
1   University of Applied Sciences, Zwickau, Germany
,
A. Häber
1   University of Applied Sciences, Zwickau, Germany
,
A. Winter
2   University Leipzig, Institute of Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig, Germany
› Author Affiliations
Further Information

Publication History

received: 07 May 2013

accepted: 01 March 2014

Publication Date:
20 January 2018 (online)

Summary

Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Using Data from Ambient Assisted Living and Smart Homes in Electronic Health Records”.

Background: Concepts of Ambient Assisted Living (AAL) support a long-term health monitoring and further medical and other services for multi-morbid patients with chronic diseases. In Germany many AAL and telemedical applications exist. Synergy effects by common agreements for essential application components and standards are not achieved.

Objectives: It is necessary to define a communication architecture which is based on common definitions of communication scenarios, application components and communication standards.

Methods: The development of a communication architecture requires different steps. To gain a reference model for the problem area different AAL and telemedicine projects were compared and relevant data elements were generalized. The derived reference model defines standardized communication links.

Results: As a result the authors present an approach towards a reference architecture for AAL-communication. The focus of the architecture lays on the communication layer. The necessary application components are identified and a communication based on standards and their extensions is highlighted.

Conclusion: The exchange of patient in -dividual events supported by an event classification model, raw and aggregated data from the personal home area over a tele-medicine center to health care providers is possible.