An intervention framework for cognitively impaired patients

Priyanka Chaurasia, Bryan Scotney, Sally McClean, Chris Nugent

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

People suffering from memory impairments experience decreased concentration, with difficulty in recalling and thinking. Inhabitants in a smart home are surrounded by multiple sensors and the sensor data collected provide information about the inhabitant’s interaction with the environment. Sensor data can be used to monitor the cognitive disabilities of the person by studying their behaviour in relation to carrying out Activity of Daily Living (ADLs). In this paper we propose an intervention framework for assistance that incorporates duration information along with the partially observed low-level sensor information and time. The framework learns probabilistically about the user and the ongoing activity and then provides decision support to monitor and assist in completing the ADLs. Our results verify that adding duration information consistently improves the accuracy in predictions from partial observation of sensor activations. ].
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherAssociation for Computing Machinery
Number of pages4
ISBN (Print)978-1-4503-0283-8
Publication statusPublished - 26 Sep 2010
Event5thtern’l Workshop on Ubiquitous Health and Wellness - Copenhagen
Duration: 26 Sep 2010 → …

Workshop

Workshop5thtern’l Workshop on Ubiquitous Health and Wellness
Period26/09/10 → …

Keywords

  • Activity recognition
  • partially observed data
  • smart homes
  • duration

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    Chaurasia, P., Scotney, B., McClean, S., & Nugent, C. (2010). An intervention framework for cognitively impaired patients. In Unknown Host Publication Association for Computing Machinery.