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Nottingham Trent University

Identification and prediction of abnormal behaviour activities of daily living in intelligent environments

Abstract

dc:description.abstract

The aim of this research is to investigate efficient mining of useful information from a sensor network forming an Ambient Intelligence (AmI) environment. In this thesis, we investigate methods for supporting independent living of the elderly (and specifically patients who are suffering from dementia) by means of equipping their home with a simple sensor network to monitor their behaviour and identify their Activities of Daily Living (ADL). Dementia is considered to be one of the most important causes of disability in the elderly. Mostpatients would prefer to use non-intrusive technology to help them tomaintain their independence. Such monitoring and prediction would allow the caregiver to see any trend in the behaviour of the elderly person and to be informed of any abnormal behaviour.

Degree

thesis:*
Name dc:type.qualificationname
phd
Level dc:type.qualificationlevel
doctoral
Grantor dc:publisher.institution
Nottingham Trent University
Year dc:date.issued
2012

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Mahmoud, SM

Rights

Language dc:language
en

Chain of custody

source
Harvested from
Nottingham Trent University
Base URL
irep.ntu.ac.uk/cgi/oai2
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Mahmoud, SM. Identification and prediction of abnormal behaviour activities of daily living in intelligent environments. doctoral thesis, Nottingham Trent University, 2012.