from ..signal import signal_formatpeaks
from .eog_findpeaks import eog_findpeaks
[docs]
def eog_peaks(veog_cleaned, sampling_rate=None, method="mne", **kwargs):
"""**Locate EOG eye blinks**
Parameters
----------
veog_cleaned : Union[list, np.array, pd.Series]
The cleaned vertical EOG channel. Note that it must be positively oriented, i.e., blinks
must appear as upward peaks.
sampling_rate : int
The signal sampling rate (in Hz, i.e., samples/second). Needed for method ``"blinker"`` or
``"jammes2008"``.
method : str
The peak detection algorithm. Can be one of ``"neurokit"``, ``"mne"`` (requires the MNE
package to be installed), or ``"brainstorm"`` or ``"blinker"``.
sampling_rate : int
The sampling frequency of the EOG signal (in Hz, i.e., samples/second). Needs to be
supplied if the method to be used is ``"blinker"``, otherwise defaults to ``None``.
**kwargs
Other arguments passed to functions.
Returns
-------
array
Vector containing the samples at which EOG-peaks occur,
See Also
--------
eog_clean
Examples
--------
.. ipython:: python
import neurokit2 as nk
# Get data
eog_signal = nk.data('eog_100hz')
eog_cleaned = nk.eog_clean(eog_signal, sampling_rate=100)
* **Example 1:** NeuroKit method
.. ipython:: python
signals, info_nk = nk.eog_peaks(eog_cleaned,
sampling_rate=100,
method="neurokit",
threshold=0.33,
show=True)
@savefig p_eog_peaks1.png scale=100%
nk.events_plot(info_nk["EOG_Blinks"], eog_cleaned)
@suppress
plt.close()
* **Example 2:** MNE-method
.. ipython:: python
signals, info_mne = nk.eog_peaks(eog_cleaned, method="mne")
@savefig p_eog_peaks2.png scale=100%
nk.events_plot(info_mne["EOG_Blinks"], eog_cleaned)
@suppress
plt.close()
* **Example 3:** brainstorm method
.. ipython:: python
signals, info_brainstorm = nk.eog_peaks(eog_cleaned, method="brainstorm")
@savefig p_eog_peaks3.png scale=100%
nk.events_plot(info_brainstorm["EOG_Blinks"], eog_cleaned)
@suppress
plt.close()
* **Example 4:** blinker method
.. ipython:: python
signals, info_blinker = nk.eog_peaks(eog_cleaned, sampling_rate=100, method="blinker")
@savefig p_eog_peaks4.png scale=100%
nk.events_plot(info_blinker["EOG_Blinks"], eog_cleaned)
@suppress
plt.close()
References
----------
* Agarwal, M., & Sivakumar, R. (2019). Blink: A Fully Automated Unsupervised Algorithm for
Eye-Blink Detection in EEG Signals. In 2019 57th Annual Allerton Conference on Communication,
Control, and Computing (Allerton) (pp. 1113-1121). IEEE.
* Kleifges, K., Bigdely-Shamlo, N., Kerick, S. E., & Robbins, K. A. (2017). BLINKER: automated
extraction of ocular indices from EEG enabling large-scale analysis. Frontiers in neuroscience, 11, 12.
"""
peaks = eog_findpeaks(veog_cleaned, sampling_rate=sampling_rate, method=method, **kwargs)
info = {"EOG_Blinks": peaks}
instant_peaks = signal_formatpeaks(info, desired_length=len(veog_cleaned), peak_indices=peaks)
signals = instant_peaks
info["sampling_rate"] = sampling_rate # Add sampling rate in dict info
return signals, info
