cff-version: 1.2.0
abstract: "<p>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:</p><p><br></p><ol><li><strong>All-Activities and FOG</strong>: Includes data from various activities along with FOG episodes.</li><li><strong>Walking-Turning and FOG</strong>: Includes data specifically from walking, turning, and FOG episodes.</li></ol><p>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.</p>"
authors:
  - family-names: Delgado-Terán
    given-names: Juan Daniel
    orcid: "https://orcid.org/0000-0001-9072-0404"
title: "Ankle Sensor Data from Parkinson&#39;s Disease Patients in Semi-Free Living Conditions for Freezing of Gait Detection"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/40e06061-f441-43b5-9235-006829206509.v1
license: CC0
date-released: 2025-01-14