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  Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion

Symeonidou, E.-R., Nordin, A., Hairston, W., & Ferris, D. (2018). Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion. Sensors, 18(4): 1073, pp. 1-13. doi:10.3390/s18041073.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-7CD6-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-7FC3-5
Genre: Journal Article

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Symeonidou, E-R1, 2, Author              
Nordin, AD, Author
Hairston, WD, Author
Ferris, DP, Author
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1Research Group Space and Body Perception, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528693              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: More neuroscience researchers are using scalp electroencephalography (EEG) to measure electrocortical dynamics during human locomotion and other types of movement. Motion artifacts corrupt the EEG and mask underlying neural signals of interest. The cause of motion artifacts in EEG is often attributed to electrode motion relative to the skin, but few studies have examined EEG signals under head motion. In the current study, we tested how motion artifacts are affected by the overall mass and surface area of commercially available electrodes, as well as how cable sway contributes to motion artifacts. To provide a ground-truth signal, we used a gelatin head phantom with embedded antennas broadcasting electrical signals, and recorded EEG with a commercially available electrode system. A robotic platform moved the phantom head through sinusoidal displacements at different frequencies (0–2 Hz). Results showed that a larger electrode surface area can have a small but significant effect on improving EEG signal quality during motion and that cable sway is a major contributor to motion artifacts. These results have implications in the development of future hardware for mobile brain imaging with EEG.

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 Dates: 2018-04
 Publication Status: Published in print
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 Identifiers: DOI: 10.3390/s18041073
BibTex Citekey: SymeonidouNHF2018
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Title: Sensors
Source Genre: Journal
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Pages: - Volume / Issue: 18 (4) Sequence Number: 1073 Start / End Page: 1 - 13 Identifier: -