ArticleSensors (Basel, Switzerland)2022
Metadata Framework to Support Deployment of Digital Health Technologies in Clinical Trials in Parkinson's Disease.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Software Reference Architecture for Real-Time Mobile Digital Phenotyping: Evaluation of System Designs.JMIR formative research · 2026Article
- From past to future: Digital approaches to success of clinical drug trials for Parkinson's disease.Journal of Parkinson's disease · 2026Review
- Advancing the Integration of Digital Health Technologies in the Drug Development Ecosystem.Journal of medical Internet research · 2025Article
- Digital Health in Parkinson's Disease and Atypical Parkinsonism-New Frontiers in Motor Function and Physical Activity Assessment: Review.Journal of clinical medicine · 2025Review
- Developing digital health technologies for frontotemporal degeneration.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Implementing sensor-based digital health technologies in clinical trials: Key considerations from the eCOA Consortium.Clinical and translational science · 2024Review
- Wearable Sensor-Based Assessments for Remotely Screening Early-Stage Parkinson's Disease.Sensors (Basel, Switzerland) · 2024Observational
- Identifying Subtle Motor Deficits Before Parkinson's Disease is Diagnosed: What to Look for?Journal of Parkinson's disease · 2024Review
- Metadata recommendations for light logging and dosimetry datasets.BMC digital health · 2024Article
- Toward Personalized Medicine Approaches for Parkinson Disease Using Digital Technologies.JMIR formative research · 2023Review
- Empowering drug development: Leveraging insights from imaging technologies to enable the advancement of digital health technologies.Clinical and translational science · 2023Review
- Identifying and characterising sources of variability in digital outcome measures in Parkinson's disease.NPJ digital medicine · 2022Article
Corrections and comments
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sensor data from digital health technologies (DHTs) used in clinical trials provides a valuable source of information, because of the possibility to combine datasets from different studies, to combine it with other data types, and to reuse it multiple times for various purposes. To date, there exist no standards for capturing or storing DHT biosensor data applicable across modalities and disease areas, and which can also capture the clinical trial and environment-specific aspects, so-called metadata. In this perspectives paper, we propose a metadata framework that divides the DHT metadata into metadata that is independent of the therapeutic area or clinical trial design (concept of interest and context of use), and metadata that is dependent on these factors. We demonstrate how this framework can be applied to data collected with different types of DHTs deployed in the WATCH-PD clinical study of Parkinson's disease. This framework provides a means to pre-specify and therefore standardize aspects of the use of DHTs, promoting comparability of DHTs across future studies.
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Registered trials
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 OpenQuestion graph.