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:
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.
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