Artificial Intelligence for Detection of Dementia Using Motions Data: A Scoping Review

Abstract

Background: Dementia is a neurodegenerative disease resulting in the loss of cognitive and psychological functions. Artificial Intelligence (AI) may help in detection and screening of dementia; however, little is known in this area. Summary: The objective of this study is to identify and evaluate artificial intelligence interventions for detection of dementia using motion data. The review followed the Joanna Briggs Institute framework and adhered to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist for reporting the results. Patients with dementia and other neurodegenerative diseases were included. Studies were excluded if they focused on diagnosing Parkinson’s or Huntington’s disease. A comprehensive search was conducted across five databases. AI interventions, which were implemented or tested in health care settings, were included. Two independent reviewers screened the abstracts, titles, and then full texts. The reference lists of included studies were also screened. Articles in English from date of inception to September 2020 were included. Any outcome related to patients, health care providers and the health care system. After removing duplicates, 2,632 articles were obtained. After title and abstract screening and full-text screening, 839 articles were included. The authors categorized the included papers into six categories and data synthesis was performed on 20 papers from the sensors tracking movement category. Key Messages: We presented evidence of AI systems being employed in the detection of dementia, showcasing the promising potential of motion tracking within this domain. Although much progress has been made in this field recently, there remain notable research gaps that require further exploration and investigation.