20.500.12556/DiRROS-14767 Removal of movement-induced EEG artifacts : current state of the art and guidelines Electroencephalography (EEG) is a non-invasive technique used to record cortical neurons' electrical activity using electrodes placed on the scalp. It has become a promising avenue for research beyond state-of-the-art EEG research that is conducted under static conditions. EEG signals are always contaminated by artifacts and other physiological signals. Artifact contamination increases with the intensity of movement. In the last decade (since 2010), researchers have started to implement EEG measurements in dynamic setups to increase the overall ecological validity of the studies. Many different methods are used to remove non-brain activity from the EEG signal, and there are no clear guidelines on which method should be used in dynamic setups and for specific movement intensities. Currently, the most common methods for removing artifacts in movement studies are methods based on independent component analysis (ICA). However, the choice of method for artifact removal depends on the type and intensity of movement, which affects the characteristics of the artifacts and the EEG parameters of interest. When dealing with EEG under non-static conditions, special care must be taken already in the designing period of an experiment. Software and hardware solutions must be combined to achieve sufficient removal of unwanted signals from EEG measurements. We have provided recommendations for the use of each method depending on the intensity of the movement and highlighted the advantages and disadvantages of the methods. However, due to the current gap in the literature, further development and evaluation of methods for artifact removal in EEG data during locomotion is needed. MoBI EEG elektroencefalografija lokomocija artefakti gibanja analiza neodvisnih komponent Mobile brain/body imaging locomotion movement artifacts independent component analysis true false true Angleški jezik Ni določen © 2022 The Author(s) Neznano 2022-03-01 09:19:57 2022-03-01 09:19:59 2022-09-06 12:02:45 0000-00-00 00:00:00 2022 0 0 Nasl. z nasl. zaslona; Soavtorji: Klaus Gramann, Kevin De Pauw, Uros Marusic; Opis vira z dne 14. 2. 2022; Članek št. 011004; str. 1-12 no. 1 Vol. 19 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 2022-02-08 2022-02-28 612.82:616-07 1741-2552 10.1088/1741-2552/ac52d2 97228035 ZRSKP_Gorjan_Dasa_i2022.pdf ZRSKP_Gorjan_Dasa_i2022.pdf 1 FB3040AE29F9146980574BFD8C3EFFA0 6cdc4dfe8d90a3f971493e6e216ad78fdce8237c2f3c7b85caf5506e49ac3c73 d310a28f-17b6-11ed-b6b8-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=19024 https://iopscience.iop.org/article/10.1088/1741-2552/ac52d2 1 https://dirros.openscience.si/Dokument.php?lang=slv&id=19023 Znanstveno-raziskovalno središče Koper / Centro di Ricerche Scientifiche Capodistria 0 0 0