load_daphnet_s06r02e0¶

load_daphnet_s06r02e0() → tuple[ndarray, ndarray][source]¶

Load the Daphnet S06R02E0 multivariate time series dataset.

Returns:

Xnp.ndarray: Multivariate time series with shape (28800,9).
ynp.ndarray: Binary anomaly labels with shape (28800,).

Notes

The Daphnet collection [1] contains unsupervised datasets with multivariate time series. Each dataset contains the annotated readings of 3 acceleration sensors at the hip and leg of Parkinson’s disease patients that experience freezing of gait (FoG) during walking tasks. FoG occureances are annotated as anomalies.

Dimensionality: multivariate (9 channels) Series length: 7040 Frequency: around 256 Hz Learning Type: unsupervised (no training data)

References

[1]

Roggen, Daniel, Plotnik, Meir, and Hausdorff,Jeff. (2013). Daphnet Freezing of Gait. UCI Machine Learning Repository. https://doi.org/10.24432/C56K78.

Examples

>>> from aeon.datasets import load_daphnet_s06r02e0
>>> X, y = load_daphnet_s06r02e0()