Abstract
The objective of our ongoing work is to develop an algorithm for detecting and eliminating artifacts from the EEG polysomnographic signals thus helping practitioners in their diagnostic. The EEG signals play an important role in the identification of brain activity and thus in the sleep stage classification. However, it is well known that the recorded EEG signals may be contaminated with artifacts that affect the analysis of EEG signal. Our short paper proposes methods for detecting and eliminating non-physiological and physiological artifacts using filtering for the first and a mixed method based on ICA and wavelets for the second.
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Sekkal, R.N., Bereksi-Reguig, F., Dib, N., Ruiz-Fernandez, D. (2020). An Approach to Detecting and Eliminating Artifacts from the Sleep EEG Signals. In: Rojas, I., Valenzuela, O., Rojas, F., Herrera, L., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2020. Lecture Notes in Computer Science(), vol 12108. Springer, Cham. https://doi.org/10.1007/978-3-030-45385-5_14
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DOI: https://doi.org/10.1007/978-3-030-45385-5_14
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