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app-notch-filter
- Aurore Bussalb (Unlicensed)
app under development Private app on bl
This App aims at apply to MEG/EEG signals notch filtering to filter power line noise and its harmonics for instance. To do so, the MNE Python functions raw.notch_filter is used.
Unlike
app-temporal-filteringandapp-resampling, this app can be run only on continuous data.This App can be applied on EEG data when it is stored in a .fif.
GitHub repository
https://github.com/AuroreBussalb/app-notch-filtering
Brainlife datatype used:
For input: neuro/meg/fif
For outputs: neuro/meg/fif and report/html
Inputs of the App
Files | Format | Datatype | Description | Optional |
|---|---|---|---|---|
MEG signals | .fif | meg/fif | The data must be continuous. Temporal filtering and resampling can have been applied beforehand. | No |
Outputs of the App:
Files | Format | Datatype | Description |
|---|---|---|---|
MEG signals | .fif | meg/fif | Data after filtering |
Report | .html | html | Visualization in time and frequency domains |
Besides, in the output directory, there are the optional files that can be used in a next App (see How to run Apps one after another).
Parameters of the App
The parameters of the App correspond to the parameters passed to the Python functions used in the App. Their default values proposed in Brainlife or in config.json.example correspond to the default values of MNE Python 0.23.
Next improvements
See if possible to apply a notch filter on epoch data?
Allow user to change the plot parameters for the plots in the HTML report?