Remote monitoring technologies in Alzheimer’s disease: design of the RADAR-AD study

Abstract

Background Functional decline in Alzheimer’s disease (AD) is typically measured using single-time point subjective rating scales, which rely on direct observation or (caregiver) recall. Remote monitoring technologies (RMTs), such as smartphone applications, wearables, and home-based sensors, can change these periodic subjective assessments to more frequent, or even continuous, objective monitoring. The aim of the RADAR-AD study is to assess the accuracy and validity of RMTs in measuring functional decline in a real-world environment across preclinical-to-moderate stages of AD compared to standard clinical rating scales. Methods This study includes three tiers. For the main study, we will include participants (n = 220) with preclinical AD, prodromal AD, mild-to-moderate AD, and healthy controls, classified by MMSE and CDR score, from clinical sites equally distributed over 13 European countries. Participants will undergo extensive neuropsychological testing and physical examination. The RMT assessments, performed over an 8-week period, include walk tests, financial management tasks, an augmented reality game, two activity trackers, and two smartphone applications installed on the participants’ phone. In the first sub-study, fixed sensors will be installed in the homes of a representative sub-sample of 40 participants. In the second sub-study, 10 participants will stay in a smart home for 1 week. The primary outcome of this study is the difference in functional domain profiles assessed using RMTs between the four study groups. The four participant groups will be compared for each RMT outcome measure separately. Each RMT outcome will be compared to a standard clinical test which measures the same functional or cognitive domain. Finally, multivariate prediction models will be developed. Data collection and privacy are important aspects of the project, which will be managed using the RADAR-base data platform running on specifically designed biomedical research computing infrastructure. Results First results are expected to be disseminated in 2022. Conclusion Our study is well placed to evaluate the clinical utility of RMT assessments. Leveraging modern-day technology may deliver new and improved methods for accurately monitoring functional decline in all stages of AD. It is greatly anticipated that these methods could lead to objective and real-life functional endpoints with increased sensitivity to pharmacological agent signal detection.

2022 Alzheimer's disease facts and figures

“…601 A systematic review of telehealth for dementia care, 639 biomarkers of MCI. 640,641 Similarly, technologies that identify speech patterns 642 and retinal blood vessel changes 643 may help flag the earliest stages of cognitive decline.…”

“…In the future, technology may also have a role in expanding biomarkers and in dementia screening and diagnosis. Studies of remote monitoring techniques, such as activity data from wrist‐worn devices or game‐like assessments on mobile phones, may produce digital biomarkers of MCI 640,641 . Similarly, technologies that identify speech patterns 642 and retinal blood vessel changes 643 may help flag the earliest stages of cognitive decline.…”

Free-Living Motor Activity Monitoring in Ataxia-Telangiectasia

“…The use of wearable sensors for passive measurement of motor activity in real-world settings has yet to be investigated in A-T; however, it has shown potential in other neurodegenerative diseases including Parkinson’s disease[ 8 ], multiple sclerosis[ 9 ], and Huntington’s disease [ 10 ]. Assessments of balance[ 11 , 12 ], gai [ 13 ], functional decline [ 14 ], and sleep quality [ 15 ] have been demonstrated, including applications of a paired sensor and vibro-tactile feedback system in neurorehabilitation [ 16 ]. Prior work in A-T has employed wearable sensors[ 17 , 18 ] and computer mice[ 19 ] to measure limb motor activity during in-person administered tasks[ 20 ].…”

Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study)

“…RADAR-base is a general mHealth data collection platform that has been used in several RMT studies [ 14 , 23 , 24 ]. It comprises several modular applications.…”