Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Robinson, Neethu, Chouhan, Tushar, Mihelj, Ernest, Kratka, Paulina, Debraine, Frédéric, Wenderoth, Nicole, Guan, Cuntai, Lehner, Rea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8239283/
https://www.ncbi.nlm.nih.gov/pubmed/34211380
http://dx.doi.org/10.3389/fnhum.2021.648275
_version_ 1783715043977723904
author Robinson, Neethu
Chouhan, Tushar
Mihelj, Ernest
Kratka, Paulina
Debraine, Frédéric
Wenderoth, Nicole
Guan, Cuntai
Lehner, Rea
author_facet Robinson, Neethu
Chouhan, Tushar
Mihelj, Ernest
Kratka, Paulina
Debraine, Frédéric
Wenderoth, Nicole
Guan, Cuntai
Lehner, Rea
author_sort Robinson, Neethu
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8239283
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-82392832021-06-30 Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot Robinson, Neethu Chouhan, Tushar Mihelj, Ernest Kratka, Paulina Debraine, Frédéric Wenderoth, Nicole Guan, Cuntai Lehner, Rea Front Hum Neurosci Human Neuroscience 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. Frontiers Media S.A. 2021-06-15 /pmc/articles/PMC8239283/ /pubmed/34211380 http://dx.doi.org/10.3389/fnhum.2021.648275 Text en Copyright © 2021 Robinson, Chouhan, Mihelj, Kratka, Debraine, Wenderoth, Guan and Lehner. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Human Neuroscience
Robinson, Neethu
Chouhan, Tushar
Mihelj, Ernest
Kratka, Paulina
Debraine, Frédéric
Wenderoth, Nicole
Guan, Cuntai
Lehner, Rea
Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot
title Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot
title_full Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot
title_fullStr Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot
title_full_unstemmed Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot
title_short Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot
title_sort design considerations for long term non-invasive brain computer interface training with tetraplegic cybathlon pilot
topic Human Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8239283/
https://www.ncbi.nlm.nih.gov/pubmed/34211380
http://dx.doi.org/10.3389/fnhum.2021.648275
work_keys_str_mv AT robinsonneethu designconsiderationsforlongtermnoninvasivebraincomputerinterfacetrainingwithtetraplegiccybathlonpilot
AT chouhantushar designconsiderationsforlongtermnoninvasivebraincomputerinterfacetrainingwithtetraplegiccybathlonpilot
AT miheljernest designconsiderationsforlongtermnoninvasivebraincomputerinterfacetrainingwithtetraplegiccybathlonpilot
AT kratkapaulina designconsiderationsforlongtermnoninvasivebraincomputerinterfacetrainingwithtetraplegiccybathlonpilot
AT debrainefrederic designconsiderationsforlongtermnoninvasivebraincomputerinterfacetrainingwithtetraplegiccybathlonpilot
AT wenderothnicole designconsiderationsforlongtermnoninvasivebraincomputerinterfacetrainingwithtetraplegiccybathlonpilot
AT guancuntai designconsiderationsforlongtermnoninvasivebraincomputerinterfacetrainingwithtetraplegiccybathlonpilot
AT lehnerrea designconsiderationsforlongtermnoninvasivebraincomputerinterfacetrainingwithtetraplegiccybathlonpilot