# single channel visual inspection - automated process

**URL:** <https://mne.discourse.group/t/single-channel-visual-inspection-automated-process/6601>\
**Category:** Support & Discussions\
**Tags:** preprocessing, visualization, emg\
**Created:** [March 27, 2023, 8:45am UTC](https://mne.discourse.group/t/single-channel-visual-inspection-automated-process/6601 "2023-03-27T08:45:05Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![evastone97](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/evastone97/32/2387_2.png) [@evastone97](https://mne.discourse.group/u/evastone97)\
**Post date:** [March 27, 2023, 8:45am UTC](https://mne.discourse.group/t/single-channel-visual-inspection-automated-process/6601/1 "2023-03-27T08:45:05Z")

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Hello, I am interested in using ASR (Artifact Subspace Reconstruction) from eeglab, and I want to know if there is something similar in MNEpython for single channel visual inspection and cleaning. I have EMG data, and according to my pipeline, I have to visually inspect each of the channels (16 different muscles + sides) and I want to do it more automatically in Python instead of using eeglab and applying ASR. Is there a way to do it in MNE?!  
Thank you for any suggestions!

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**Author:** ![sappelhoff](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/sappelhoff/32/3276_2.png) [@sappelhoff](https://mne.discourse.group/u/sappelhoff)\
**Post date:** [March 29, 2023, 12:01pm UTC](https://mne.discourse.group/t/single-channel-visual-inspection-automated-process/6601/2 "2023-03-29T12:01:48Z")

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I recommend that you have a look at these two sections in the documentation (tutorials and examples on preprocessing):

- [Preprocessing — MNE 1.3.1 documentation](https://mne.tools/stable/auto_tutorials/preprocessing/index.html)
- [Preprocessing — MNE 1.3.1 documentation](https://mne.tools/stable/auto_examples/preprocessing/index.html)

And in particular the tutorial on repairing artifacts using ICA. To the best of my knowledge, ASR as in EEGLAB is not implemented in MNE-Python.