Cargando…
Zapline‐plus: A Zapline extension for automatic and adaptive removal of frequency‐specific noise artifacts in M/EEG
Removing power line noise and other frequency‐specific artifacts from electrophysiological data without affecting neural signals remains a challenging task. Recently, an approach was introduced that combines spectral and spatial filtering to effectively remove line noise: Zapline. This algorithm, ho...
Autores principales: | Klug, Marius, Kloosterman, Niels A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9120550/ https://www.ncbi.nlm.nih.gov/pubmed/35278015 http://dx.doi.org/10.1002/hbm.25832 |
Ejemplares similares
-
Automatic Classification of Artifactual ICA-Components for Artifact Removal in EEG Signals
por: Winkler, Irene, et al.
Publicado: (2011) -
“Picture-in-Picture” Artifact: Introduction and Characterization of a Hitherto Unrecognized Imaging Artifact in Creating Perfusion Defects in Myocardial Perfusion Single-Photon Emission Computed Tomography
por: Qutbi, Mohsen, et al.
Publicado: (2021) -
Automatic Removal of Physiological Artifacts in EEG: The Optimized Fingerprint Method for Sports Science Applications
por: Stone, David B., et al.
Publicado: (2018) -
Practical Ranges of Loudness Levels of Various Types of Environmental Noise, Including Traffic Noise, Aircraft Noise, and Industrial Noise
por: Salomons, Erik M., et al.
Publicado: (2011) -
An automated artifact detection and rejection system for body surface gastric mapping
por: Calder, Stefan, et al.
Publicado: (2022)