The artifact subspace reconstruction (ASR) for EEG signal correction. A comparative study

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Abstract

The paper presents the results of a comparative study of the artifact subspace re-construction (ASR) method and two other popular methods dedicated to correct EEG artifacts: independent component analysis (ICA) and principal component analysis (PCA). The comparison is based on automatic rejection of EEG signal epochs performed on a dataset of motor imagery data. ANOVA results show a significantly better level of artifact correction for the ASR method. What is more, the ASR method does not cause serious signal loss compared to other methods.

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Plechawska-Wojcik, M., Kaczorowska, M., & Zapala, D. (2019). The artifact subspace reconstruction (ASR) for EEG signal correction. A comparative study. In Advances in Intelligent Systems and Computing (Vol. 853, pp. 125–135). Springer Verlag. https://doi.org/10.1007/978-3-319-99996-8_12

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