Observational studySensors (Basel, Switzerland)2024
Wearable Sensor-Based Assessments for Remotely Screening Early-Stage Parkinson's Disease.
Observational study in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Predicting disease outcomes from remote monitoring using machine learning: a systematic review.BMC medical informatics and decision making · 2026Pooled it
- Evaluating the Utility of Wearable Sensors for the Early Diagnosis of Parkinson Disease: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Wearable-sensor based walking and non-walking measures as progression markers in early to mid-stage Parkinson's disease.NPJ Parkinson's disease · 2026Article
- AI-Enabled Flexible Sensing Ecosystems for Parkinson's Disease: Advancing Digital Biomarkers and Closed-Loop Interventions.Sensors (Basel, Switzerland) · 2026Review
- Speech and Language Changes During Rapid Eye Movement (REM) Sleep with Potential Diagnostic Markers: A Systematic Review.Brain sciences · 2026Review
- Innovative Sensor-Based Approaches for Assessing Neurodegenerative Diseases: A Brief State-of-the-Art Review.Sensors (Basel, Switzerland) · 2025Review
- Writing the Future: Artificial Intelligence, Handwriting, and Early Biomarkers for Parkinson's Disease Diagnosis and Monitoring.Biomedicines · 2025Review
- Wearable Sensors and Artificial Intelligence for the Diagnosis of Parkinson's Disease.Journal of clinical medicine · 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
- Artificial Intelligence in the Diagnosis of Neurological Diseases Using Biomechanical and Gait Analysis Data: A Scopus-Based Bibliometric Analysis.Neurology international · 2025Review
- Assessing Parkinson's Rest Tremor from the Wrist with Accelerometry and Gyroscope Signals in Patients with Deep Brain Stimulation: An Observational Study.Journal of clinical medicine · 2025Article
- Stage-specific digital health technology biomarkers enhance diagnostic and early progression detection in Parkinson's disease.Frontiers in neurologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prevalence estimates of Parkinson's disease (PD)-the fastest-growing neurodegenerative disease-are generally underestimated due to issues surrounding diagnostic accuracy, symptomatic undiagnosed cases, suboptimal prodromal monitoring, and limited screening access. Remotely monitored wearable devices and sensors provide precise, objective, and frequent measures of motor and non-motor symptoms. Here, we used consumer-grade wearable device and sensor data from the WATCH-PD study to develop a PD screening tool aimed at eliminating the gap between patient symptoms and diagnosis. Early-stage PD patients (
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What Socratic 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 Socratic graph.