Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

12-2019

Abstract

Singapore has the fastest ageing population in the Asia Pacific region, with an estimated 82,000 seniors living with dementia. These figures are projected to increase to more than 130,000 by 2030. The challenge is to identify more community dwelling seniors with Mild Cognitive Impairment (MCI), a prodromal state, as it provides an opportunity for evidence-based early intervention to delay the onset of dementia. In this paper, we explore the use of Internet of Things (IoT) systems in detecting MCI symptoms in seniors who are living alone, and accurately grouping them into MCI positive and negative subjects. We present feature extraction methods and findings from real data captured via selected sensors installed in the homes of 49 seniors for up to two months. Performance evaluation shows that the sleep state variability, as measured through bed sensors, yields a recall of over 70% in predicting MCI in these community dwelling seniors.

Keywords

Internet of Things (IoT), Senior monitoring, Mild cognitive impairment, Early detection, Eldercare, Dementia, MITB student

Discipline

Databases and Information Systems | Gerontology | Health Information Technology

Research Areas

Data Science and Engineering

Publication

2019 IEEE International Conference on Big Data: Los Angeles, December 9-12: Proceedings

First Page

1619

Last Page

1624

ISBN

9781728108582

Identifier

10.1109/BigData47090.2019.9005629

Publisher

IEEE

City or Country

Piscataway, NJ

Embargo Period

4-28-2020

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/BigData47090.2019.9005629

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