Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot.

Autor:	Robinson N; School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore., Chouhan T; School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.; Future Health Technologies, Singapore-ETH Centre, Singapore, Singapore., Mihelj E; Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland., Kratka P; Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland., Debraine F; Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland., Wenderoth N; Future Health Technologies, Singapore-ETH Centre, Singapore, Singapore.; Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland., Guan C; School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.; Future Health Technologies, Singapore-ETH Centre, Singapore, Singapore., Lehner R; Future Health Technologies, Singapore-ETH Centre, Singapore, Singapore.; Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland.
Jazyk:	angličtina
Zdroj:	Frontiers in human neuroscience [Front Hum Neurosci] 2021 Jun 15; Vol. 15, pp. 648275. Date of Electronic Publication: 2021 Jun 15 (Print Publication: 2021).
DOI:	10.3389/fnhum.2021.648275
Abstrakt:	Several studies in the recent past have demonstrated how Brain Computer Interface (BCI) technology can uncover the neural mechanisms underlying various tasks and translate them into control commands. While a multitude of studies have demonstrated the theoretic potential of BCI, a point of concern is that the studies are still confined to lab settings and mostly limited to healthy, able-bodied subjects. The CYBATHLON 2020 BCI race represents an opportunity to further develop BCI design strategies for use in real-time applications with a tetraplegic end user. In this study, as part of the preparation to participate in CYBATHLON 2020 BCI race, we investigate the design aspects of BCI in relation to the choice of its components, in particular, the type of calibration paradigm and its relevance for long-term use. The end goal was to develop a user-friendly and engaging interface suited for long-term use, especially for a spinal-cord injured (SCI) patient. We compared the efficacy of conventional open-loop calibration paradigms with real-time closed-loop paradigms, using pre-trained BCI decoders. Various indicators of performance were analyzed for this study, including the resulting classification performance, game completion time, brain activation maps, and also subjective feedback from the pilot. Our results show that the closed-loop calibration paradigms with real-time feedback is more engaging for the pilot. They also show an indication of achieving better online median classification performance as compared to conventional calibration paradigms ( p = 0.0008). We also observe that stronger and more localized brain activation patterns are elicited in the closed-loop paradigm in which the experiment interface closely resembled the end application. Thus, based on this longitudinal evaluation of single-subject data, we demonstrate that BCI-based calibration paradigms with active user-engagement, such as with real-time feedback, could help in achieving better user acceptability and performance. Competing Interests: BrainProducts has provided EEG equipment and Rehaklinik Zihlschlacht has financially supported the CYBATHLON BCI team for participating in the CYBATHLON 2020 event. 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. (Copyright © 2021 Robinson, Chouhan, Mihelj, Kratka, Debraine, Wenderoth, Guan and Lehner.)
Databáze:	MEDLINE
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