Abstract
Brain-computer interfaces (BCIs) have been employed to provide different patient groups with communication and control that does not require the use of limbs that have been damaged. In this study, we explored BCI-based navigation in three long term amputees. Each participant attempted motor execution with the affected limb, and performed motor execution with the intact limb, while fMRI activity was recorded. Participants attempted, and executed, one of four tasks to direct the movement of an avatar on a monitor. Classification accuracy was very high across both cue-based and free-choice conditions. Results support the use of this fMRI BCI approach for virtual navigation, which could improve BCIs based on fMRI as well as other approaches such as EEG.
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Acknowledgements
This research was supported by the European Union FP7 Integrated Project VERE (No. 657295), http://www.vereproject.eu. We would like to thank the subjects for their participation, and the Weizmann Institute fMRI scanner staff Edna Furman-Haran, Nachum Stern and Fanny Attar for their help in this experiment.
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Cohen, O., Doron, D., Koppel, M., Malach, R., Friedman, D. (2019). High Performance BCI in Controlling an Avatar Using the Missing Hand Representation in Long Term Amputees. In: Guger, C., Mrachacz-Kersting, N., Allison, B. (eds) Brain-Computer Interface Research. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-05668-1_9
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