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Newcombe, LS, Yang, P, Carter, C, Hanneghan, M and Qi, J (2019) Experimental Analysis of Cost-Effective Mobile Sensing Technologies for Activity Analytics in Elderly Care. In: 2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS) . (The 16th International Conference on Smart City, 28 June 2018 - 30 June 2018, Exeter, UK).
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Abstract
Advancements in sensor technology has provided new ways for researchers to monitor the elderly in uncontrolled environments. Sensors have become smaller, cheaper and can now be worn on the body. Smart phones are also more common in the average household and can provide some analysis of behaviour. Because of this, researchers are able to monitor behaviours in a more natural setting, which can produce useful data. For those suffering with a mental illness, this is important as it allows for continuous, non-invasive monitoring in order to diagnose symptoms from different behaviours. However, issues with the sensors and the involvement of human factors are challenges that need to be addressed. These challenges must be taken into consideration in addition to the behavioural symptoms of Dementia that can appear in the elderly. The application of sensor technologies can aid in improving the quality of life of an elderly person with Dementia and monitor the progression of the disease through behavioural analysis. This paper will provide an experiment protocol that can be used to monitor those with mild cognitive impairment in a natural environment. We will also provide data and results from an initial experiment and discuss our plans for future experimentation.
| Item Type: | Conference or Workshop Item (Paper) |
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| Additional Information: | © 2019 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. |
| Uncontrolled Keywords: | Internet of Things; Healthcare; Behaviour Analytics |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Computer Science & Mathematics |
| Publisher: | IEEE |
| Date Deposited: | 18 Jul 2018 10:30 |
| Last Modified: | 12 Jun 2024 14:20 |
| DOI or ID number: | 10.1109/HPCC/SmartCity/DSS.2018.00238 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/8972 |
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