Managing sensor systems for early detection of mild cognitive impairment in community elderly: Lessons learned and future work
The aging population is a pertinent issue faced by governments globally. One of the most common and costly health issues associated with the aging population is cognitive decline, leading up to dementia. In this paper, we describe a non-intrusive, continuous and scalable system for early detection o...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2017
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/4139 https://ink.library.smu.edu.sg/context/sis_research/article/5142/viewcontent/IRC_SET_2017_paper_S1_5.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | The aging population is a pertinent issue faced by governments globally. One of the most common and costly health issues associated with the aging population is cognitive decline, leading up to dementia. In this paper, we describe a non-intrusive, continuous and scalable system for early detection of Mild Cognitive Impairment (MCI) in the elderly, which enables early medical interventions to be provided. We focus on the system design and feature extraction of the sensor system, to validate our hypothesis of the use of sensor systems for early detection of MCI. Lessons learned from deploying the sensor system is presented, together with the solutions that are implemented to improve system reliability |
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