Ankle Sensor Data from Parkinson's Disease Patients in Semi-Free Living Conditions for Freezing of Gait Detection

doi:10.4121/40e06061-f441-43b5-9235-006829206509.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/40e06061-f441-43b5-9235-006829206509
Datacite citation style:
Delgado-Terán, Juan Daniel (2025): Ankle Sensor Data from Parkinson's Disease Patients in Semi-Free Living Conditions for Freezing of Gait Detection. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/40e06061-f441-43b5-9235-006829206509.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This dataset contains preprocessed accelerometer and gyroscope data collected from ankle-mounted sensors worn on the right ankle of people with Parkinson's Disease. The measurements were conducted in a semi-free living environment, enabling the analysis of real-world movement patterns. The data is structured into tensors for machine learning research on freezing of gait (FOG) detection. Two distinct datasets are provided:


  1. All-Activities and FOG: Includes data from various activities along with FOG episodes.
  2. Walking-Turning and FOG: Includes data specifically from walking, turning, and FOG episodes.

Each dataset includes time-series data and corresponding binary labels indicating the presence or absence of FOG. Associated metadata provides additional descriptive information for each sample.

history
  • 2025-01-14 first online, published, posted
publisher
4TU.ResearchData
format
compressed_IMU_data/npz
funding
  • INTENSE (grant code 17619) NWO
organizations
University of Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Department of Electrical Engineering

DATA

files (43)