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

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:<br><strong>All-Activities and FOG</strong>: Includes data from various activities along with FOG episodes.<strong>Walking-Turning and FOG</strong>: 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.

本数据集包含经预处理的加速度计与陀螺仪传感数据，采集自帕金森病患者右踝佩戴的踝部传感器。本次数据采集于半自由生活环境中，可支持真实场景下运动模式的分析。本数据集已整理为张量格式，适用于步态冻结（freezing of gait, FOG）检测相关的机器学习研究。本次共提供两类独立数据集：
**全活动与步态冻结数据集（All-Activities and FOG）**：涵盖各类活动数据及步态冻结发作数据。
**行走-转身与步态冻结数据集（Walking-Turning and FOG）**：仅包含行走、转身及步态冻结发作相关数据。
两类数据集均包含时序数据与对应的二分类标签，用于标注是否存在步态冻结。配套元数据可为每个样本提供额外的描述性信息。