[Mne_analysis] Automatic artifact rejection on continuous data

Nico Adelhöfer nico.adelhoefer at st.ovgu.de
Wed Jul 27 11:36:00 EDT 2016
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Thanks! I got it working so far with Jean-Remi's method, but using  
_segment_raw gives me an attribute error.

I read that the "reject" parameter is the peak-to-peak amplitude. Are  
there other rejection parameters such as maximum allowed voltage step,  
or lowest allowed activity?




Quoting Mikołaj Magnuski <mmagnuski at swps.edu.pl>:

> Just adding to Jean-Remi’s answer:
> you can quickly and easily chop data into segments using _segment_raw:
>
> from mne.epochs import _segment_raw
> epochs = _segment_raw(raw_eeg, segment_length=2.)
>
> This chops the data into 2-s long segments.
>>
> 2016-07-25 15:30 GMT+02:00 JR KING <jeanremi.king at gmail.com>:
>
>> Hi Nico,
>>
>> To reject chunks of continuous data, the best is probably to first chop it
>> into small segments, which comes down to creating adjacent events/epoch and
>> apply your favorite rejection threshold, i.e.
>>
>> chunk_size = 1000
>> chunk_starts = np.arange(0, raw.n_times, chunk_size)
>> events = np.c_[chunk_starts, np.zeros((len(chunk_starts), 2))].astype(int)
>> epochs = mne.Epochs(raw, events, dict(chunk=0), tmin=0, tmax=chunk_size *
>> raw.info['sfreq'], reject=dict(mag=5e-12))
>>
>> Don't forget to check out the artefact correction tutorial:
>> http://martinos.org/mne/stable/auto_tutorials/plot_artifacts_detection.htm
>>
>> the gallery examples:
>>
>> http://martinos.org/mne/stable/auto_examples/preprocessing/plot_find_eog_artifacts.html
>>
>> http://martinos.org/mne/stable/auto_examples/preprocessing/plot_find_ecg_artifacts.html
>>
>> http://martinos.org/mne/stable/auto_examples/preprocessing/plot_interpolate_bad_channels.html
>>
>> as well as Jas' autoreject repository:
>> https://github.com/jasmainak/autoreject
>>
>> Hope that helps,
>>
>> Jean-Rémi
>>
>> On 25 July 2016 at 08:44, Nico Adelhöfer <nico.adelhoefer at st.ovgu.de>
>> wrote:
>>
>>> Is there a way to set parameters for automatic artifact rejection on
>>> continuous data in MNE? I'm especially interested in setting
>>> parameters such as "maximum allowed voltage step" or "maximum and
>>> minimum amplitude". Is there a command that achieves this on raw data?
>>>
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