Smart Solutions for Detecting, Predicting, Monitoring, and Managing Dementia in the Elderly: A Survey

Abstract

Dementia, a syndrome which is characterized by a decline in cognitive abilities such as memory, thinking, behavior, and the ability to perform daily living activities, is prevalent in people aged 60 and above. However, detecting it early enough can possibly slow its continuous degeneration and lessen the toll on families and caregivers alike. Due to its mortality within 10 years of onset as well as its enormous socioeconomic burden, there have been active efforts by researchers to find smart and innovative solutions for its early detection, prediction, monitoring, and management. These efforts are driven by the recent advancements in the Internet of Things (IoT), wearable technologies, and machine learning algorithms. The solutions are modeled around the modifiable risk factors of dementia. In this study, we conducted a survey of smart solutions developed or implemented to assist caregivers and clinicians in managing the health of these affected individuals. We then looked at the issues and limitations of these solutions, and argued that integrated solutions comprising wearable and non-wearable technologies modeled around multiple risk factors of dementia are necessary and should be the direction of future studies.

Keywords

• Dementia
• wearable technology
• Internet of Things (IoT)
• non-wearable technology
• machine learning
• activities of daily living (ADL)