Posts eeg12/25/2022 ![]() A cleaner separation also means that less brain activity will be removed when ocular components are eliminated. ICA can separate ocular components from brain components well if many EEG channels are available (which in turn requires a relatively large number of data samples). Instead, I will only list some important properties of both techniques.įirst, the regression-based approach requires EOG channels, whereas ICA works without any reference signal.īoth methods potentially remove brain activity in addition to ocular activity. ![]() ![]() (2000).Ī comprehensive comparison between the two methods is beyond the scope of this post. This approach is described in more detail in Jung et al. Components that represent ocular activity can be identified and eliminated to reconstruct artifact-free EEG signals. In a nutshell, ICA decomposes multi-channel EEG recordings into maximally independent components. A popular alternative to this approach is independent component analysis (ICA). ![]() In this previous post, we used linear regression to remove ocular artifacts from EEG signals. ![]()
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