Mohamedali, Fehmida and Matoorianpour, Nasser (2016) Support dementia: using wearable assistive technology and analysing real-time data. In: Interactive Technologies and Games (ITAG) 2016 Conference, 26-27 Oct 2016, Nottingham, UK.
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Abstract
Support provided to sufferers of Dementia by the National Health Service (NHS) is mainly in the form of personal attendants such as nurses and social workers. The main focus of this paper is to present how the use of assistive technologies can help early sufferers of Dementia patients to overcome barriers in achieving their daily activities and to illustrate how data analytics, such as Complex Event Processing (CEP) in real-time can allow better monitoring of these patients. This activity will contribute to research work which is to provide a suitable framework to accurately analyse real-time data from assistive technology and wearable devices for remote healthcare, particularly monitoring early sufferers of dementia in order to promote good quality independent living.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| ISBN: | 9781509037391 |
| Page Range: | pp. 50-54 |
| Identifier: | 10.1109/iTAG.2016.15 |
| Additional Information: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Keywords: | Dementia, Real-time systems, Biomedical monitoring, Assistive technology, Semantics, Wearable sensors |
| Subjects: | Computing Medicine and health |
| Date Deposited: | 15 Feb 2017 |
| Dates: | Date Publication status 27 October 2016 Published |
| School, department or research centre: | School of Computing and Engineering |
| Keywords: | Dementia, Real-time systems, Biomedical monitoring, Assistive technology, Semantics, Wearable sensors |
| URI: | https://repository.uwl.ac.uk/id/eprint/3158 |
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