ArticleScientific reports2024
Home-based monitoring of persons with advanced Parkinson's disease using smartwatch-smartphone technology.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.
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Who cites it
18 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Continuous Movement Monitoring at Home Through Wearable Devices: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Clinical Outcomes of Passive Sensors in Remote Monitoring: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Movement Disorders and Smart Wrist Devices: A Comprehensive Study.Sensors (Basel, Switzerland) · 2025Pooled it
- Rethinking the concept of disease modification in an evolving Parkinson's disease treatment landscape.Journal of Parkinson's disease · 2026Review
- In-clinic validation of a smartphone-based finger tapping test for use in neurodegenerative and neurological populations.medRxiv : the preprint server for health sciences · 2026Article
- Bridging the global Parkinson's divide: Technology as a structural solution for equitable and brain health-integrated care.Journal of Parkinson's disease · 2026Review
- Harnessing artificial intelligence: Revolutionizing clinical care for Parkinson's disease.Journal of Parkinson's disease · 2026Review
- Digital Technologies for Symptom Monitoring in Parkinson Disease.Current neurology and neuroscience reports · 2026Review
- Added value of a wrist-worn device for assessing tremor in Parkinson's disease: reliability and validity of tremor evaluation at home.NPJ Parkinson's disease · 2025Article
- L-Dopa Comparably Improves Gait and Limb Movements in Parkinson's Disease: A Wearable Sensor Analysis.Biomedicines · 2025Article
- Advancing the Integration of Digital Health Technologies in the Drug Development Ecosystem.Journal of medical Internet research · 2025Article
- Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait.Journal of medical Internet research · 2025Article
- Wearables research for continuous monitoring of patient outcomes: A scoping review.PLOS digital health · 2025Article
- Evaluating Heart Rate Variability as a Biomarker for Autonomic Function in Parkinson's Disease Rehabilitation: A Clustering-Based Analysis of Exercise-Induced Changes.Medicina (Kaunas, Lithuania) · 2025Article
- Usage Trends and Data Sharing Practices of Healthcare Wearable Devices Among US Adults: Cross-Sectional Study.Journal of medical Internet research · 2025Article
- Accelerated symptom improvement in Parkinson's disease via remote internet-based optimization of deep brain stimulation therapy: a randomized controlled multicenter trial.Communications medicine · 2025Article
- Genetic analyses identify circulating genes related to brain structures associated with Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Inter-rater reliability of hand motor function assessment in Parkinson's disease: Impact of clinician training.Clinical parkinsonism & related disorders · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Movement deterioration is the hallmark of Parkinson's disease (PD), characterized by levodopa-induced motor-fluctuations (i.e., symptoms' variability related to the medication cycle) in advanced stages. However, motor symptoms are typically too sporadically and/or subjectively assessed, ultimately preventing the effective monitoring of their progression, and thus leading to suboptimal treatment/therapeutic choices. Smartwatches (SW) enable a quantitative-oriented approach to motor-symptoms evaluation, namely home-based monitoring (HBM) using an embedded inertial measurement unit. Studies validated such approach against in-clinic evaluations. In this work, we aimed at delineating personalized motor-fluctuations' profiles, thus capturing individual differences. 21 advanced PD patients with motor fluctuations were monitored for 2 weeks using a SW and a smartphone-dedicated app (Intel Pharma Analytics Platform). The SW continuously collected passive data (tremor, dyskinesia, level of activity using dedicated algorithms) and active data, i.e., time-up-and-go, finger tapping, hand tremor and hand rotation carried out daily, once in OFF and once in ON levodopa periods. We observed overall high compliance with the protocol. Furthermore, we observed striking differences among the individual patterns of symptoms' levodopa-related variations across the HBM, allowing to divide our participants among four data-driven, motor-fluctuations' profiles. This highlights the potential of HBM using SW technology for revolutionizing clinical practices.
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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 OpenQuestion graph.