Early detection of diseases causing dementia using digital navigation and gait measures: A systematic review of evidence.
Giedrė ČepukaitytėCharlotte Coco NewtonDennis ChanPublished in: Alzheimer's & dementia : the journal of the Alzheimer's Association (2024)
Wearable digital technologies capable of measuring everyday behaviors could improve the early detection of dementia-causing diseases. We conducted two systematic reviews following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines to establish the evidence base for measuring navigation and gait, two everyday behaviors affected early in AD and non-AD disorders and not adequately measured in current practice. PubMed and Web of Science databases were searched for studies on asymptomatic and early-stage symptomatic individuals at risk of dementia, with the Newcastle-Ottawa Scale used to assess bias and evaluate methodological quality. Of 316 navigation and 2086 gait records identified, 27 and 83, respectively, were included in the final sample. We highlight several measures that may identify at-risk individuals, whose quantifiability with different devices mitigates the risk of future technological obsolescence. Beyond navigation and gait, this review also provides the framework for evaluating the evidence base for future digital measures of behaviors considered for early disease detection.
Keyphrases
- meta analyses
- systematic review
- mild cognitive impairment
- early stage
- cerebral palsy
- cognitive impairment
- randomized controlled trial
- current status
- healthcare
- public health
- machine learning
- blood pressure
- radiation therapy
- lymph node
- adverse drug
- radiation induced
- big data
- loop mediated isothermal amplification
- disease virus