`mne_features.univariate`.compute_hjorth_mobility_spect¶

mne_features.univariate.compute_hjorth_mobility_spect(sfreq, data, normalize=False, psd_method='welch', psd_params=None)¶

Hjorth mobility (per channel).

Hjorth mobility parameter computed from the Power Spectrum of the data.

Parameters

sfreqfloat: Sampling rate of the data.
datandarray, shape (n_channels, n_times)
normalizebool (default: False): Normalize the result by the total power.
psd_methodstr (default: ‘welch’): Method used for the estimation of the Power Spectral Density (PSD). Valid methods are: 'welch', 'multitaper' or 'fft'.
psd_paramsdict or None (default: None): If not None, dict with optional parameters (welch_n_fft, welch_n_per_seg, welch_n_overlap) to be passed to mne_features.utils.power_spectrum(). If None, default parameters are used (see doc for mne_features.utils.power_spectrum()).

Returns

Notes

Alias of the feature function: hjorth_mobility_spect. See [1] and [2].

References

1: Mormann, F. et al. (2006). Seizure prediction: the long and winding road. Brain, 130(2), 314-333.
2: Teixeira, C. A. et al. (2011). EPILAB: A software package for studies on the prediction of epileptic seizures. Journal of Neuroscience Methods, 200(2), 257-271.

mne_features.univariate.compute_hjorth_mobility_spect¶