ArticleScientific data2026
WearGait-PD: An Open-Access Wearables Dataset for Gait in Parkinson's Disease and Age-Matched Controls.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A Dual-Task Gait Fusion Framework for Classifying Parkinson's Disease Severity from Wearable Sensor Data.Diagnostics (Basel, Switzerland) · 2026Article
- Multi-Task Wearable Parkinson's Disease Detection with a Pretrained Spatio-Temporal Graph Encoder and Task-Level Token Aggregation.Bioengineering (Basel, Switzerland) · 2026Article
- A comprehensive survey on diagnosis and assessment of Parkinson's disease via plantar pressure analysis.NPJ Parkinson's disease · 2026Article
- WearGait-PD: An Open-Access Wearables Dataset for Gait in Parkinson's Disease and Age-Matched Controls.Scientific data · 2026Article
- A multi-level annotated sensor dataset of gait freezing manifestations and severity in Parkinson's disease.Scientific data · 2026Article
- Deep Convolutional Neural Network-Based Detection of Gait Abnormalities in Parkinson's Disease Using Fewer Plantar Sensors in a Smart Insole.Biosensors · 2026Article
- Multi-Domain CoP Feature Analysis of Functional Mobility for Parkinson's Disease Detection Using Wearable Pressure Insoles.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Wearable movement sensors are powerful tools for objectively characterizing and quantifying movement. They enhance the precise characterization of gait, balance, and motor symptoms in Parkinson's disease and related disorders, facilitating in-clinic and remote assessments, disease management, and therapeutic intervention development. Access to high-quality data from these sensors can accelerate discoveries in this clinical population. The WearGait-PD open-access dataset contains raw inertial measurement unit (IMU) and sensorized insole data from 100 individuals with PD and 85 age-matched controls, synchronized to a gait walkway reference system. IMU data include 3-degree of freedom (DOF) acceleration, rotational velocity, magnetic field strength, and orientation for each of 13 sensors on the participant's body. Sensor insole data include absolute pressure from 16 sensors in each insole and 3-DOF acceleration and rotational velocity. Walkway data include 2D position and relative pressure for each active sensor during every footfall. Frame-by-frame annotation of participant actions during gait and balance tasks was incorporated using synchronized video cameras. All data were associated with demographic information and clinical evaluations (e.g., medications, DBS-status, MDS-UPDRS scores).
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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.