An Approach to and Evaluations of Assisted Living Systems Using Ambient Intelligence for Emergency Monitoring and Prevention

Authors:
Thomas Kleinberger;Andreas Jedlitschka;Holger Storf;Silke Steinbach-Nordmann;Stephan Prueckner
Affiliations:
Fraunhofer Institute Experimental Software Engineering, Kaiserslautern, Germany 67663;Fraunhofer Institute Experimental Software Engineering, Kaiserslautern, Germany 67663;Fraunhofer Institute Experimental Software Engineering, Kaiserslautern, Germany 67663;Fraunhofer Institute Experimental Software Engineering, Kaiserslautern, Germany 67663;Department of Anaesthesiology and Emergency Medicine, Kaiserslautern, Germany 67655
Venue:
UAHCI '09 Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments
Year:
2009

Citing 2
Cited 4

Living assistance systems: an ambient intelligence approach

Proceedings of the 28th international conference on Software engineering
Inventing Wellness Systems for Aging in Place

Computer

An Event-Driven Approach to Activity Recognition in Ambient Assisted Living

AmI '09 Proceedings of the European Conference on Ambient Intelligence
Informatics as semiotics engineering: lessons learned from design, development and evaluation of ambient assisted living applications for elderly people

UAHCI'11 Proceedings of the 6th international conference on Universal access in human-computer interaction: context diversity - Volume Part III
Dependability analysis in the Ambient Assisted Living Domain: An exploratory case study

Journal of Systems and Software
Data and Information Quality Issues in Ambient Assisted Living Systems

Journal of Data and Information Quality (JDIQ)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Ambient Assisted Living (AAL) is currently one of the important research and development areas, where software engineering aspects play a significant role. The goal of AAL solutions is to apply ambient intelligence technologies to enable people with specific needs to continue to live in their preferred environments. This paper presents an approach and several evaluations for emergency monitoring applications. Experiments in a laboratory setting were performed to evaluate the accuracy of recognizing Activities of Daily Living (ADL). The results show that it is possible to detect ADLs with an accuracy of 92% on average. Hence, we conclude that it is possible to support elderly people in staying longer in their homes by autonomously detecting emergencies on the basis of ADL recognition.