Tools
Tools
Chalmers, C, Hurst, W, MacKay, M and Fergus, P (2019) Identifying Behavioural Changes for Health Monitoring Applications using the Advanced Metering Infrastructure. Behaviour and Information Technology. ISSN 1362-3001
|
Text
TF_Behaviour&InformationTechnology.pdf - Accepted Version Download (904kB) | Preview |
Abstract
The rising demand for health and social care, and around the clock monitoring services, is increasing and are unsustainable under current care provisions and legislation. Consequently, a safe and independent living environment is hard to achieve; yet the detection of sudden or worsening changes in a patient’s condition is vital for early intervention. The use of smart technologies in primary care delivery is increasing significantly. However, substantial research gaps remain in non-invasive and cost effective monitoring technologies. Where such technologies are used, they are considered too intrusive and often incapable of being personalised to the individual needs of patients. The inability to learn the unique characteristics of patients and their conditions seriously limits the effectiveness of most current solutions. The smart metering infrastructure provides new possibilities for a variety of emerging applications that are unachievable using the traditional energy grid. Between now and 2020, UK energy suppliers will install and configure of 50 million smart meters therefore providing access to a highly accurate sensing network. Each smart meter records accurately the electrical load for a given property at 30 minute intervals, 24 hours a day. This granular data captures detailed habits and routines through the occupant’s interactions with electrical devices, enabling the detection and identification of alterations in behaviour. The research presented in this paper explores how this data could be used to achieve a safe living environment for people living with progressive neurodegenerative disorders, such as Dementia.
| Item Type: | Article |
|---|---|
| Additional Information: | This is an Accepted Manuscript of an article published by Taylor & Francis in Behaviour and Information Technology on 7 Feb 2019 available online: http://www.tandfonline.com/10.1080/0144929X.2019.1574900 |
| Uncontrolled Keywords: | 08 Information and Computing Sciences, 17 Psychology and Cognitive Sciences |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine |
| Divisions: | Computer Science & Mathematics |
| Publisher: | Taylor & Francis |
| Date Deposited: | 25 Jan 2019 15:51 |
| Last Modified: | 04 Sep 2021 09:46 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/10032 |
 |
View Item |