Independent Component Analysis (ICA) is a computational technique used to separate a multivariate signal into additive, independent non-Gaussian components. It is particularly useful in the context of brain-machine interfaces (BMIs) as it helps to extract meaningful signals from mixed sources, enabling better control and interpretation of neural data for assistive devices.
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