Visualization of raw (gray), reference (red), CLEEGN (blue) EEG waveforms with offline methods by ICLabel, ASR-32, ASR-32-ICLabel, ASR-16, ASR-16-ICLabel, ASR-8, ASR-8-ICLabel, ASR-4, ASR-4-ICLabel. Each segment plots a five-second segment of signals at Fp1, T7, Cz, T8, and O2.

Visualization of raw (gray), reference (red), CLEEGN (blue) EEG waveforms with offline methods by ICLabel, ASR-32, ASR-32-ICLabel, ASR-16, ASR-16-ICLabel, ASR-8, ASR-8-ICLabel, ASR-4, ASR-4-ICLabel. Each segment plots a five-second segment of signals at Fp1, T7, Cz, T8, and O2.

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Human electroencephalography (EEG) is a brain monitoring modality that senses cortical neuroelectrophysiological activity in high-temporal resolution. One of the greatest challenges posed in applications of EEG is the unstable signal quality susceptible to inevitable artifacts during recordings. To date, most existing techniques for EEG artifact re...

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... ICLabel, ASR, and the hybrid ASR-ICLabel are employed to automatically generate large-scale noiseless reference EEG data offline, it is of our interest to investigate what type of reference EEG serves as the best noiseless reference data for the CLEEGN model training. Figure 5 presents the EEG waveforms sampled from Subject 2 in the ERN dataset. The EEG time series from top to bottom represent the recording of Fp1, T7, Cz, T8, and O2 channels. ...

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