UWB Indoor Location for Monitoring Dementia Patients: The Challenges and Perception of a Real-Life Deployment

UWB Indoor Location for Monitoring Dementia Patients: The Challenges and Perception of a Real-Life Deployment

Agnes Grünerbl (German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany), Gernot Bahle (German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany), Friedrich Hanser (Institute of Biomedical and Technical Engineering, University of Health Sciences (UMIT), Hall in Tirol, Austria) and Paul Lukowicz (German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany)
Copyright: © 2013 |Pages: 15
DOI: 10.4018/ijaci.2013100104
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Abstract

Monitoring the activities of daily living is a common form of assessing the progression of dementia. Yet so far, this mostly can only be done by visual observations, which is time and cost expensive and therefore only done on a short scale. Even though the technology for automatic monitoring exists, it is still seldom used in real life environments. Key problems are the effort involved in sensor deployment and the extraction of relevant activity information from simple sensor data. In the following article the authors describe a long-term real-life monitoring of dementia patients using an easy to deploy UWB-location system. The authors describe the system-concept, discuss practical deployment and maintenance experience, and present monitoring results.
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2. Objectives And Contributions

The main objective of the work presented here was to investigate the potential of pervasive sensing technology to monitor and asses the progress of dementia with the focus on the feasibility of deploying and operating a system over a long period of time in a real nursing environment. Thus, the main contributions of this article are:

  • 1.

    Analysis of the suitability of different sensing modalities.

  • 2.

    Deployment of a system in a real-world nursing environment. In this article we discuss a collection of practical issues we have encountered from which future work could significantly benefit.

  • 3.

    The collection of a large-scale data set.

  • 4.

    Analysis of the data that demonstrates the potential of the system for reliable state assessment.

  • 5.

    Analysis of the perception of the system by the stuff as a way to understand factors that need to be considered in successful real life deployments of pervasive technology in nursing environments.

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