ArticleNPJ Parkinson's disease2021
A real-world study of wearable sensors in Parkinson's disease.
Article in NPJ Parkinson's disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 3 syntheses or guidelines pooled it, 85 citations in OpenAlex.
- Wearable Sensors in Gait Assessment for Parkinson Disease and Stroke in Real-World Environments: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Real-world gait study of Parkinson's disease using wearable sensors: a systematic review.Journal of neuroengineering and rehabilitation · 2026Pooled it
- Objective Measurement of Walking Activity Using Wearable Technologies in People with Parkinson Disease: A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Real-world data capture of daily limb loading using force-sensing insoles: Feasibility and lessons learned.Journal of biomechanics · 2024Trial
- Digital Health Approaches to Geriatric Rehabilitation: A Narrative Paper.Annals of rehabilitation medicine · 2026Article
- Flexible and Self-Powered Wearable Sensors for Tremor Monitoring in Parkinson'S Disease: Recent Advances in Materials and Device Architectures.Advanced healthcare materials · 2026Review
- Bilateral DLPFC transcranial direct current stimulation for mood and motor symptoms in Parkinson's disease: a preliminary study.Acta neuropsychiatrica · 2026Article
- Wearable-sensor based walking and non-walking measures as progression markers in early to mid-stage Parkinson's disease.NPJ Parkinson's disease · 2026Article
- Automatic and explainable assessment for Parkinson's disease by video-based human motion understanding.Journal of neuroengineering and rehabilitation · 2026Article
- Digital Technologies for Symptom Monitoring in Parkinson Disease.Current neurology and neuroscience reports · 2026Review
- AI-Enabled Wearables for Motor Function Assessment and Rehabilitation in Parkinson Disease: Scoping Review.Journal of medical Internet research · 2026Review
- Scoping review of AI-driven wearable technologies for rehabilitation and functional assessment in Parkinson's disease: a protocol.BMJ open · 2026Article
- Accessible assessment of motor and cognitive symptoms in Parkinson's disease: integrating large datasets, machine-learning, and videoconferencing.NPJ digital medicine · 2026Article
- Wavelet-Based Tremor Quantification From Wrist-Worn Sensor Data in Home-Dwelling People With Parkinson's Disease.IEEE journal of translational engineering in health and medicine · 2026Article
- Clinical Validity of Wrist- and Trunk-Worn Sensor-Derived Data Models in Parkinson's Disease.Parkinson's disease · 2026Article
- Characterizing motor-cognitive associations in Parkinson's disease using digital assessments.Frontiers in aging neuroscience · 2026Article
- Association between wrist-worn actigraphy and the MDS-UPDRS Parkinson's disease rating scale through machine learning: an exploratory study.Frontiers in digital health · 2026Article
- Identifying and predicting fast versus slow Parkinson's disease motor progressors using clinical and digital data.BMJ neurology open · 2026Article
- L-Dopa Comparably Improves Gait and Limb Movements in Parkinson's Disease: A Wearable Sensor Analysis.Biomedicines · 2025Article
- A systematic review of real-world gait-related digital mobility outcomes in Parkinson's disease.NPJ digital medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
Most wearable sensor studies in Parkinson's disease have been conducted in the clinic and thus may not be a true representation of everyday symptoms and symptom variation. Our goal was to measure activity, gait, and tremor using wearable sensors inside and outside the clinic. In this observational study, we assessed motor features using wearable sensors developed by MC10, Inc. Participants wore five sensors, one on each limb and on the trunk, during an in-person clinic visit and for two days thereafter. Using the accelerometer data from the sensors, activity states (lying, sitting, standing, walking) were determined and steps per day were also computed by aggregating over 2 s walking intervals. For non-walking periods, tremor durations were identified that had a characteristic frequency between 3 and 10 Hz. We analyzed data from 17 individuals with Parkinson's disease and 17 age-matched controls over an average 45.4 h of sensor wear. Individuals with Parkinson's walked significantly less (median [inter-quartile range]: 4980 [2835-7163] steps/day) than controls (7367 [5106-8928] steps/day; P = 0.04). Tremor was present for 1.6 [0.4-5.9] hours (median [range]) per day in most-affected hands (MDS-UPDRS 3.17a or 3.17b = 1-4) of individuals with Parkinson's, which was significantly higher than the 0.5 [0.3-2.3] hours per day in less-affected hands (MDS-UPDRS 3.17a or 3.17b = 0). These results, which require replication in larger cohorts, advance our understanding of the manifestations of Parkinson's in real-world settings.
Identifiers
What OpenQuestion holds
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.