Remove Channel Artefact

Module name: RemoveChannelArtefact

Package: CEAMSModules 7.4.0

Version: 2.0.0

Overview

Remove full-channel artefacts from signals and events.

This module accepts one or multiple artefact group/name pairs to identify channel-level artefacts. It removes any SignalModel whose channel matches these artefacts (after warning if the artefact does not span the full signal) and drops the corresponding events from the DataFrame.

Inputs

Input	Format	Default	Description
`signals`	list of SignalModel	—	List of SignalModel objects, each with attributes: .samples (numpy array), .sample_rate (Hz), .channel (str), .start_time (s), .end_time (s) and .duration (s).
`events`	pandas.DataFrame	—	DataFrame of events with columns [‘group’,’name’,’start_sec’,’duration_sec’,’channels’].
`artefact_group`	str	—	Comma-separated artefact event groups (e.g. ‘art_inspector’).
`artefact_name`	str	—	Comma-separated artefact event names (e.g. ‘non_brain,art_channel’). If only one group is given but multiple names, that group is applied to all names.

Outputs

Output	Format	Description
`clean_signals`	list of SignalModel	Signals with any full-channel artefacts removed.
`clean_events`	pandas.DataFrame	Events DataFrame with specified artefact rows removed.

Usage in a process

Open Dev Tools -> New process in Snooz.
In the Module Library, find Remove Channel Artefact under the Signal Processing category.
Drag the module onto the process canvas.
Connect the required inputs from upstream modules (or set values in the Settings tab).
Connect outputs to downstream modules as needed.
Double-click the module to configure parameters in the Settings tab.
Run the process and inspect results in the Results tab.

Note

For general guidance on building processes with modules, see Explore examples.