Tools
Tools
Mahmoud, S.M., 2012. Identification and prediction of abnormal behaviour activities of daily living in intelligent environments. PhD, Nottingham Trent University.
|
Text
212198_Sawsan Mahmoud Thesis.pdf Download (13MB) | Preview |
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.
| Item Type: | Thesis |
|---|---|
| Creators: | Mahmoud, S.M. |
| Date: | 2012 |
| Divisions: | Schools > School of Science and Technology |
| Record created by: | EPrints Services |
| Date Added: | 09 Oct 2015 09:33 |
| Last Modified: | 09 Oct 2015 09:33 |
| URI: | https://irep.ntu.ac.uk/id/eprint/60 |
Actions (login required)
 |
Edit View |
Views
Views per month over past year
Downloads
Downloads per month over past year
