[Eeglablist] Using ICA for labelling artifacts

[Velu Prabhakar Kumaravel]

Dear EEGLABers,

As we know, it is rare to find data labeled for artifacts which makes it
hard to develop or validate artifacts detection algorithms. My colleagues
and I wonder if we could use ICA followed by ICLabel to label the segments
of data as "Artifact" or "Clean". The steps are as follows:

0) To facilitate reliable ICA decomposition for short windows of data, only
4 channels are kept (known apriori)
1) Bandpass filter (1-45 Hz)
2) Segment data into 4s non-overlapping windows (sampling rate = 256 Hz,
1024 samples)
3) Perform ICA
4) Classify components using ICLabel
5) If there exists at least 1 eye or muscle Component with probability >
0.95, the given window of data is "Artifact". Otherwise, "Clean".

Do we see any potential problems in the approach? From our preliminary
analysis, more than 50% of windows are labeled for Artifact, hence the
concern.

I appreciate your feedback.

Thanks and regards,

Velu Prabhakar Kumaravel, Ph.D. Student
Center for Mind/Brain Sciences,
University of Trento, Italy