Introducing SPECTER 2.0 - an Enhanced Version of the Tensor Based Eye Blink Removal Algorithm

SPECTER (the Signal sPECtrum Tensor decomposition and Eye blink Removal) is a novel algorithm designed to detect and elimininate eye blink-related artifacts from electroencephalogram (EEG) recordings. Our previous study [1] demonstrated its superior performance compared to established regression-based methods or independent component analysis, especially in situations where these approaches failed to accurately detect eye blinks or introduced spurious oscillations into the signal. In this study, we introduce SPECTER 2.0, an improved version that addresses the limitations of the original algorithm, and we demonstrate its improved performance on a real EEG dataset affected by eye blinks.