Investigating the impact of visual perspective in a motor imagery-based brain-robot interaction: A pilot study with healthy participants

Andrea Farabbi; Patricia Figueiredo; Fabiola Ghiringhelli; Luca Mainardi; Joao Miguel Sanches; Plinio Moreno; Jose Santos-Victor; Athanasios Vourvopoulos

doi:10.3389/fnrgo.2023.1080794

Investigating the impact of visual perspective in a motor imagery-based brain-robot interaction: A pilot study with healthy participants

Front Neuroergon. 2023 Mar 30:4:1080794. doi: 10.3389/fnrgo.2023.1080794. eCollection 2023.

Authors

Andrea Farabbi¹, Patricia Figueiredo², Fabiola Ghiringhelli¹, Luca Mainardi¹, Joao Miguel Sanches², Plinio Moreno², Jose Santos-Victor², Athanasios Vourvopoulos²

Affiliations

¹ B3Lab, Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy.
² Institute for Systems and Robotics-Lisboa, Instituto Superior Tecnico, Lisbon, Portugal.

Abstract

Introduction: Motor Imagery (MI)-based Brain Computer Interfaces (BCI) have raised gained attention for their use in rehabilitation therapies since they allow controlling an external device by using brain activity, in this way promoting brain plasticity mechanisms that could lead to motor recovery. Specifically, rehabilitation robotics can provide precision and consistency for movement exercises, while embodied robotics could provide sensory feedback that can help patients improve their motor skills and coordination. However, it is still not clear whether different types of visual feedback may affect the elicited brain response and hence the effectiveness of MI-BCI for rehabilitation.

Methods: In this paper, we compare two visual feedback strategies based on controlling the movement of robotic arms through a MI-BCI system: 1) first-person perspective, with visual information that the user receives when they view the robot arms from their own perspective; and 2) third-person perspective, whereby the subjects observe the robot from an external perspective. We studied 10 healthy subjects over three consecutive sessions. The electroencephalographic (EEG) signals were recorded and evaluated in terms of the power of the sensorimotor rhythms, as well as their lateralization, and spatial distribution.

Results: Our results show that both feedback perspectives can elicit motor-related brain responses, but without any significant differences between them. Moreover, the evoked responses remained consistent across all sessions, showing no significant differences between the first and the last session.

Discussion: Overall, these results suggest that the type of perspective may not influence the brain responses during a MI- BCI task based on a robotic feedback, although, due to the limited sample size, more evidence is required. Finally, this study resulted into the production of 180 labeled MI EEG datasets, publicly available for research purposes.

Keywords: Brain-ComputerInterfaces; electroencephalography; human-robot interaction; motor-imagery; neurorehabilitation.

Grants and funding

This work was supported by the Fundação para a Ciência e Tecnologia (FCT) through CEECIND/01073/2018, the LARSyS-FCT Project UIDB/50009/2020, the NeurAugVR PTDC/CCI-COM/31485/2017, and the NOISyS 2022.02283.PTDC project.