Description

This report provides a snapshot of your EEG recording's signal quality, highlighting individual channels using topographic plots. The report measures key metrics, including line noise, high frequency noise, channel artifacts, and channel correlation, and pinpoints the channels, and in some cases time points, where these are detected.

File information

filename	C:\Users\CGX\Desktop\Q32 Multiple Artifacts Example.edf
file size in Mb	6.36
file modification time	Oct 10, 2025, 13:11:49
num channels	29
channel labels	AF7, FPz, F7, Fz, T7, FC6, Fp1, F4, C4, Oz, CP6, Cz, PO8, CP5, O2, O1, P3, P4, P7, P8, Pz, PO7, T8, C3, Fp2, F3, F8, FC5, AF8
num timepoints	82500
file length in seconds	165.0
sampling rate	500.0
metadata	(none found)

Summary

Good/Bad channel Overview

This metric combines channel correlation and high-frequency noise measurements, to classify the average signal quality captured by a given channel (electrode) as "good" or "bad".

Red channels indicate the EEG signal was poor quality.
Green channels indicate the EEG signal was good.

Artifacts

Artifact to clean EEG ratio

This measure shows the level of artifacts, computed as the ratio of artifact amplitude to clean EEG amplitude a given channel, averaged across the session.

Low (green, smaller disks): Minimal artifacts.
High (red, larger disks): Significant artifacts.
Percentage of session containing artifacts: 44.6%

Artifacts (over time)

This plot shows differences between the raw EEG data and the clean EEG (after removing artifacts). Spikes in this plot indicate times where there were significant artifacts. If artifacts are present at the beginning and end of the session (i.e., adjusting or removing the headset) and that data will not be used, use the trim settings in the plugin to re-run this report with those portions removed to compute the signal quality of the remaining data.

This is the data on which the Artifact Ratio (as shown in the earlier topoplot) is computed for the session. Note that the differences are trimmed at 20 standard deviations.