ArticleJournal of medical Internet research2021
Exploring Test-Retest Reliability and Longitudinal Stability of Digital Biomarkers for Parkinson Disease in the m-Power Data Set: Cohort Study.
Article in Journal of medical Internet research, 2021. 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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Who cites it
12 citing papers in PubMed.
- From phenotype to biology: a multi-modal roadmap of biofluid, tissue, imaging, and digital biomarkers in Parkinson's disease.Translational neurodegeneration · 2026Review
- Engagement of Users in Digital Health Applications: Scoping Review.JMIR mHealth and uHealth · 2026Article
- Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait.Journal of medical Internet research · 2025Article
- Modernizing the Staging of Parkinson Disease Using Digital Health Technology.Journal of medical Internet research · 2025Article
- Definitions of digital biomarkers: a systematic mapping of the biomedical literature.BMJ health & care informatics · 2024Review
- Multidimensional digital biomarker phenotypes for mild cognitive impairment: considerations for early identification, diagnosis and monitoring.Frontiers in digital health · 2024Article
- Impacts on study design when implementing digital measures in Parkinson's disease-modifying therapy trials.Frontiers in digital health · 2024Article
- Assessment of Upper Extremity Function in Multiple Sclerosis: Feasibility of a Digital Pinching Test.JMIR formative research · 2023Article
- A smartphone-based tapping task as a marker of medication response in Parkinson's disease: a proof of concept study.Journal of neural transmission (Vienna, Austria : 1996) · 2023Article
- Smartphone accelerometer data as a proxy for clinical data in modeling of bipolar disorder symptom trajectory.NPJ digital medicine · 2022Article
- Classification of Parkinson's disease and its stages using machine learning.Scientific reports · 2022Article
- System Comparison for Gait and Balance Monitoring Used for the Evaluation of a Home-Based Training.Sensors (Basel, Switzerland) · 2022Article
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4 authors.
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Abstract
backgroundDigital biomarkers (DB), as captured using sensors embedded in modern smart devices, are a promising technology for home-based sign and symptom monitoring in Parkinson disease (PD).
objectiveDespite extensive application in recent studies, test-retest reliability and longitudinal stability of DB have not been well addressed in this context. We utilized the large-scale m-Power data set to establish the test-retest reliability and longitudinal stability of gait, balance, voice, and tapping tasks in an unsupervised and self-administered daily life setting in patients with PD and healthy controls (HC).
methodsIntraclass correlation coefficients were computed to estimate the test-retest reliability of features that also differentiate between patients with PD and healthy volunteers. In addition, we tested for longitudinal stability of DB measures in PD and HC, as well as for their sensitivity to PD medication effects.
resultsAmong the features differing between PD and HC, only a few tapping and voice features had good to excellent test-retest reliabilities and medium to large effect sizes. All other features performed poorly in this respect. Only a few features were sensitive to medication effects. The longitudinal analyses revealed significant alterations over time across a variety of features and in particular for the tapping task.
conclusionsThese results indicate the need for further development of more standardized, sensitive, and reliable DB for application in self-administered remote studies in patients with PD. Motivational, learning, and other confounders may cause variations in performance that need to be considered in DB longitudinal applications.
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