Technology-Facilitated Detection of Mild Cognitive Impairment: A Review

Abstract

Early diagnosis and management of dementia require accurate detection of symptoms and incidents in the pre-dementia stage of mild cognitive impairment (MCI). With the recent development of smart sensing technologies and machine learning algorithms, researchers have started exploring the possibility of automatically detecting symptoms of MCI based on home activity distributions. In this paper, we provide a brief review of the current state of the art in this line of research. We first present an overview of clinical studies on MCI. We then describe various technologies that have been used to collect data regarding patients cognitive levels and behaviors, and methods used to detect patterns and the deviation from these patterns. We also highlight the limitations of the current research work and outline future research tasks, including the development of cheaper and easily portable solutions, as well as personalized tracking technologies.