ArticleAlzheimer's research & therapy2021
Remote monitoring technologies in Alzheimer's disease: design of the RADAR-AD study.
Article in Alzheimer's research & therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Stage-Wise IoT Solutions for Alzheimer's Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies.Sensors (Basel, Switzerland) · 2025Pooled it
- Screening for Alzheimer's disease in the community using an AI-driven screening platform: design of the PREDICTOM study.The journal of prevention of Alzheimer's disease · 2026Article
- Which activity tracker features matter to you? Older Black participants living with memory challenges and care partner preferences.Innovation in aging · 2026Article
- End User and Primary Care Physicians' Perspectives on Digital Innovations in Dementia Risk Detection: Focus on a Digital Sleep Biomarker.JMIR aging · 2025Article
- A scoping review of remote and unsupervised digital cognitive assessments in preclinical Alzheimer's disease.NPJ digital medicine · 2025Article
- RADAR-AD: assessment of multiple remote monitoring technologies for early detection of Alzheimer's disease.Alzheimer's research & therapy · 2025Article
- Alzheimer's Disease: Exploring Pathophysiological Hypotheses and the Role of Machine Learning in Drug Discovery.International journal of molecular sciences · 2025Review
- A decision-analytic method to evaluate the cost-effectiveness of remote monitoring technology for chronic depression.International journal of technology assessment in health care · 2025Article
- Dream content influences daily spirituality.Frontiers in psychology · 2025Article
- Digital Phenotyping of Mental and Physical Conditions: Remote Monitoring of Patients Through RADAR-Base Platform.JMIR mental health · 2024Article
- Regulatory considerations for developing remote measurement technologies for Alzheimer's disease research.NPJ digital medicine · 2024Article
- The usability and reliability of a smartphone application for monitoring future dementia risk in ageing UK adults.The British journal of psychiatry : the journal of mental science · 2024Article
- A Semantic Framework to Detect Problems in Activities of Daily Living Monitored through Smart Home Sensors.Sensors (Basel, Switzerland) · 2024Article
- Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research.Journal of the American Heart Association · 2024Review
- Assessing the cognitive decline of people in the spectrum of AD by monitoring their activities of daily living in an IoT-enabled smart home environment: a cross-sectional pilot study.Frontiers in aging neuroscience · 2024Article
- Augmented reality versus standard tests to assess cognition and function in early Alzheimer's disease.NPJ digital medicine · 2023Article
- Data-driven care for patients with neurodegenerative disorders.Nature reviews. Neurology · 2023Article
- Article
- Free-Living Motor Activity Monitoring in Ataxia-Telangiectasia.Cerebellum (London, England) · 2022Article
- Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint.Journal of medical Internet research · 2022Article
Corrections and comments
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Authors and funding
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFunctional 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.
methodsThis 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.
resultsFirst results are expected to be disseminated in 2022.
conclusionOur 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.