[Mne_analysis] Automatic artifact rejection on continuous data

[Eric Larson]

Have you tried:

http://mne-tools.github.io/stable/generated/mne.io.Raw.html#mne.io.Raw.set_channel_types

Eric


On Wed, Jul 27, 2016 at 2:51 PM, Nico Adelhöfer <nico.adelhoefer at st.ovgu.de>
wrote:

> Thanks again!
>
> Is there a way to adjust the info of my raw data? The "reject"
> parameter expects certain channel types.
> I created an info instance:
>
>      inf =
>
> mne.create_info(12,512,['misc','misc','eog','eog','eeg','eeg','eeg','eeg','eeg','eeg'])
>
> but I don't know how to change this information in my raw variable. I
> tried to change it manually like
>
>      raw.info['chs'][2]['kind'] == 'eog'
>
> but then I get an error that this type is not found. Changing the
> pick.py file (e.g. line 46 to: elif kind == FIFF.FIFFV_EOG_CH or
> 'eog') before the command above did not change the kind and is also
> not the preferable way I guess. I could not find a solution on the MNE
> website.
>
>
>
>
> Quoting Mainak Jas <mainakjas at gmail.com>:
>
> > On Wed, Jul 27, 2016 at 5:36 PM, Nico Adelhöfer <
> nico.adelhoefer at st.ovgu.de>
> > wrote:
> >
> >> 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?
> >>
> >
> > You also have the parameter "flat" which will remove epochs with too low
> a
> > peak-to-peak amplitude.
> >
> > Mainak
> >
> >
> >> 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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