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Editorial
. 2020 Nov 30:1:602504.
doi: 10.3389/fnrgo.2020.602504. eCollection 2020.

Grand Challenges in Neurotechnology and System Neuroergonomics

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Editorial

Grand Challenges in Neurotechnology and System Neuroergonomics

Stephen H Fairclough et al. Front Neuroergon. .
No abstract available

Keywords: EEG; brain-computer interfaces; fNIRS; human-computer interaction; neuroergonomics; neurotechnologies.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
A graphic illustration of the three grand challenges (GC) for Neurotechnology and Systems Neuroergonomics.

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References

    1. Abu-Alqumsan M., Kapeller C., Hintermüller C., Guger C., Peer A. (2017). Invariance and variability in interaction error-related potentials and their consequences for classification. J. Neural Eng. 14:066015. 10.1088/1741-2552/aa8416 - DOI - PubMed
    1. Ahn M., Jun S. C. (2015). Performance variation in motor imagery brain-computer interface: a brief review. J. Neurosci. Methods 243, 103–110. 10.1016/j.jneumeth.2015.01.033 - DOI - PubMed
    1. Allanson J., Fairclough S. H. (2004). A research agenda for physiological computing. Interact. Comput. 16, 857–878. 10.1016/j.intcom.2004.08.001 - DOI
    1. Banville H., Falk T. (2016). Recent advances and open challenges in hybrid brain-computer interfacing: a technological review of non-invasive human research. Brain-Comput. Interfaces, 3, 9–46. 10.1080/2326263X.2015.1134958 - DOI
    1. Blankertz B., Kawanabe M., Tomioka R., Hohlefeld F., Müller K.-R., Nikulin V. V. (2008). “Invariant common spatial patterns: alleviating nonstationarities in brain-computer interfacing,” in Advances in Neural Information Processing Systems (Vancouver, BC: ), 113–120.

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