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A comparison of a broad range of EEG acquisition devices – is there any difference for SSVEP BCIs?

A comparison of a broad range of EEG acquisition devices – is there any difference for SSVEP BCIs? This study compared the signal quality of six commercially available electroencephalography (EEG) signal acquisition systems in order to evaluate their application in a brain-computer interface (BCI). This is one of the largest studies in terms of subjects and systems focusing on comparing different EEG systems, involving the whole variety in terms of amplifier (research grade, consumer grade), electrode type (gel-based, saline-based, dry, active, passive), transmission technique (wired, wireless), and cost. We established an approach to evaluate the signal quality by means of a steady-state visually evoked potentials (SSVEP) experiment. This demonstrated that although high-end traditional EEG equipment may be the best choice for clinical applications, low-end wireless research grade gel-based EEG systems are comparable in terms of signal quality and therefore may be an effective alternative to BCIs developed for real environments. Other factors, such as end user and application, should also be considered when deciding which EEG system is best suited for a BCI. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Brain-Computer Interfaces Taylor & Francis

A comparison of a broad range of EEG acquisition devices – is there any difference for SSVEP BCIs?

A comparison of a broad range of EEG acquisition devices – is there any difference for SSVEP BCIs?

Brain-Computer Interfaces , Volume 5 (4): 11 – Oct 2, 2018

Abstract

This study compared the signal quality of six commercially available electroencephalography (EEG) signal acquisition systems in order to evaluate their application in a brain-computer interface (BCI). This is one of the largest studies in terms of subjects and systems focusing on comparing different EEG systems, involving the whole variety in terms of amplifier (research grade, consumer grade), electrode type (gel-based, saline-based, dry, active, passive), transmission technique (wired, wireless), and cost. We established an approach to evaluate the signal quality by means of a steady-state visually evoked potentials (SSVEP) experiment. This demonstrated that although high-end traditional EEG equipment may be the best choice for clinical applications, low-end wireless research grade gel-based EEG systems are comparable in terms of signal quality and therefore may be an effective alternative to BCIs developed for real environments. Other factors, such as end user and application, should also be considered when deciding which EEG system is best suited for a BCI.

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References (38)

Publisher
Taylor & Francis
Copyright
© 2018 Informa UK Limited, trading as Taylor & Francis Group
ISSN
2326-2621
eISSN
2326-263x
DOI
10.1080/2326263X.2018.1550710
Publisher site
See Article on Publisher Site

Abstract

This study compared the signal quality of six commercially available electroencephalography (EEG) signal acquisition systems in order to evaluate their application in a brain-computer interface (BCI). This is one of the largest studies in terms of subjects and systems focusing on comparing different EEG systems, involving the whole variety in terms of amplifier (research grade, consumer grade), electrode type (gel-based, saline-based, dry, active, passive), transmission technique (wired, wireless), and cost. We established an approach to evaluate the signal quality by means of a steady-state visually evoked potentials (SSVEP) experiment. This demonstrated that although high-end traditional EEG equipment may be the best choice for clinical applications, low-end wireless research grade gel-based EEG systems are comparable in terms of signal quality and therefore may be an effective alternative to BCIs developed for real environments. Other factors, such as end user and application, should also be considered when deciding which EEG system is best suited for a BCI.

Journal

Brain-Computer InterfacesTaylor & Francis

Published: Oct 2, 2018

Keywords: Brain-computer interface; dry electrodes; wireless EEG; low-cost EEG; benchmark for EEG systems

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