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Exp Neurol. 2017 Jan;287(Pt 4):473-478. doi: 10.1016/j.expneurol.2016.05.013. Epub 2016 May 16.

Flight simulation using a Brain-Computer Interface: A pilot, pilot study.

Author information

1
Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
2
The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
3
Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA; Center for the Neural Basis of Cognition, Pittsburgh, PA, USA; Department of Veterans Affairs Medical Center, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
4
Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA, USA. Electronic address: Elizabeth.Tyler-Kabara@chp.edu.

Abstract

As Brain-Computer Interface (BCI) systems advance for uses such as robotic arm control it is postulated that the control paradigms could apply to other scenarios, such as control of video games, wheelchair movement or even flight. The purpose of this pilot study was to determine whether our BCI system, which involves decoding the signals of two 96-microelectrode arrays implanted into the motor cortex of a subject, could also be used to control an aircraft in a flight simulator environment. The study involved six sessions in which various parameters were modified in order to achieve the best flight control, including plane type, view, control paradigm, gains, and limits. Successful flight was determined qualitatively by evaluating the subject's ability to perform requested maneuvers, maintain flight paths, and avoid control losses such as dives, spins and crashes. By the end of the study, it was found that the subject could successfully control an aircraft. The subject could use both the jet and propeller plane with different views, adopting an intuitive control paradigm. From the subject's perspective, this was one of the most exciting and entertaining experiments she had performed in two years of research. In conclusion, this study provides a proof-of-concept that traditional motor cortex signals combined with a decoding paradigm can be used to control systems besides a robotic arm for which the decoder was developed. Aside from possible functional benefits, it also shows the potential for a new recreational activity for individuals with disabilities who are able to master BCI control.

KEYWORDS:

Brain-Computer Interface; Flight

PMID:
27196543
DOI:
10.1016/j.expneurol.2016.05.013
[Indexed for MEDLINE]

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