WearGait-PD: An Open-Access Wearables Dataset for Gait in Parkinson’s Disease and Age-Matched Controls

Read full text
Authors: Anthony Anderson, David Eguren, Michael Gonzalez, Michael J. Caiola, Naima Khan, Sophia A. Watkinson, Isabella Zuccaroli, Siegfried S. Hirczy, Cyrus P. Zabetian, Kelly Mills, Emile Sami Moukheiber, Laureano Moro-Velázquez
+5 more Najim Dehak, Chelsie S. Motley, Brittney C. Muir, Ankur Butala, Kimberly L. Kontson
Cited by: 7
References: 28

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).

Fields of Study & Subjects

Balance Gait and Falls Prevention Prosthetics and Rehabilitation Robotics Parkinson's Disease Mechanisms and Treatments

Publication details

Journal / source
Scientific Data
Publisher
Springer Science and Business Media LLC
Volume
13
Issue
1
Publication date
12 February 2026
Language
EN