Abstract

In this paper an ambient intelligent-based framework is proposed for the monitoring of dementia patients living in their own homes. Within this framework groups of unobtrusive wireless sensor devices can be deployed at specific locations within a patient’s home and accessed via standardized interfaces provided through an open middleware platform. For each sensor group intelligent agents are used to learn fuzzy rules, which model the patient’s habitual behaviours in the environment. An online rule adaptation technique is applied to facilitate short-term tuning of the learnt behaviours, and long-term tracking of behaviour changes which could be due to the effects of cognitive decline caused from dementia. The proposed system reports behaviour changes to care providers to enable them to make better-informed assessments of the patient’s cognitive abilities and changing care needs.

Highlights

  • Ubiquitous and pervasive computing is a paradigm in which computing technology becomes virtually invisible by being embedded in our environments

  • For each Local Sensor Groups (LSG) we propose using an intelligent agent learning and adaptation technique that learns fuzzy rules modelling the particularbehaviours of the patient in the environment

  • We propose a framework for an ambient intelligent system to monitor and track the disease progression of dementia patients

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Summary

INTRODUCTION

Ubiquitous and pervasive computing is a paradigm in which computing technology becomes virtually invisible by being embedded in our environments. Whereas in moderate stages the patient may exhibit a lack of awareness in the time of day leading to pronounced changes in behaviour from day to day, or impaired communication (PDE-3193-2004) It can be difficult for relatives and carers to continually observe a patient and recognise the subtle changes in a patient’s behaviour and daily activities, which may signal progressively worsening stages of the disease. It can be difficult for health professionals to accurately track the patterns of a patient’s cognitive impairment and the impact this is having on daily living and wellbeing.

LITERATURE REVIEW
FUZZY AGENT APPROACH FOR DEMENTIA MONITORING
Generation of FLS Modelling Patient
Passive Monitoring and Short-Term Online Tuning of Behaviour Rules
Findings
CONCLUSION

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