Název:
Automatic Removal of Sparse Artifacts in Electroencephalogram
Autoři:
Zima, Miroslav ; Tichavský, Petr ; Krajča, V. Typ dokumentu: Výzkumné zprávy
Rok:
2010
Jazyk:
eng
Edice: Research Report , svazek: 2289
Abstrakt: This report presents an algorithm for removing artifacts from EEG signal, which is based on the method of independent component analysis utilizing the signal nonstationarity or sparsity of the artifacts. The algorithm is computationally very fast, enables online processing of long data records with excellent separation accuracy. The algorithm also incorporates using wavelet denoising of the artifact components, recently proposed by Castellanos and Makarov, which reduces distortion of the cleaned data.
Klíčová slova:
artifact removal; electroencephalogram; independent component analysis; wavelet denoising Číslo projektu: CEZ:AV0Z10750506 (CEP), 1M0572 (CEP), GA102/09/1278 (CEP) Poskytovatel projektu: GA MŠk, GA ČR