Improving motor imagery classification during induced motor perturbations

Date

2021

Authors

Ramos Murguialday, Ander
Müller, Klaus Robert
Nikulin, Vadim V.

Director

Publisher

IOP Publishing
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión publicada / Argitaratu den bertsioa

Project identifier

MINECO//RYC-2014-15671/ES/ recolecta
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-118829RB-I00/ES/ recolecta
European Commission/Horizon 2020 Framework Programme/951910 openaire
Impacto

Abstract

Objective. Motor imagery is the mental simulation of movements. It is a common paradigm to design brain-computer interfaces (BCIs) that elicits the modulation of brain oscillatory activity similar to real, passive and induced movements. In this study, we used peripheral stimulation to provoke movements of one limb during the performance of motor imagery tasks. Unlike other works, in which induced movements are used to support the BCI operation, our goal was to test and improve the robustness of motor imagery based BCI systems to perturbations caused by artificially generated movements. Approach. We performed a BCI session with ten participants who carried out motor imagery of three limbs. In some of the trials, one of the arms was moved by neuromuscular stimulation. We analysed 2-class motor imagery classifications with and without movement perturbations. We investigated the performance decrease produced by these disturbances and designed different computational strategies to attenuate the observed classification accuracy drop. Main results. When the movement was induced in a limb not coincident with the motor imagery classes, extracting oscillatory sources of the movement imagination tasks resulted in BCI performance being similar to the control (undisturbed) condition; when the movement was induced in a limb also involved in the motor imagery tasks, the performance drop was significantly alleviated by spatially filtering out the neural noise caused by the stimulation. We also show that the loss of BCI accuracy was accompanied by weaker power of the sensorimotor rhythm. Importantly, this residual power could be used to predict whether a BCI user will perform with sufficient accuracy under the movement disturbances. Significance. We provide methods to ameliorate and even eliminate motor related afferent disturbances during the performance of motor imagery tasks. This can help improving the reliability of current motor imagery based BCI systems.

Description

Keywords

Motor imagery, Brain-computer interfacing, Induced movements, Neuro-muscular electrical stimulation, Motor disturbances, Afferent signals, Feedback contingency

Department

Estadística, Informática y Matemáticas / Estatistika, Informatika eta Matematika

Faculty/School

Degree

Doctorate program

item.page.cita

item.page.rights

© 2021 The Author(s). Creative Commons Attribution 4.0 International

Licencia

Los documentos de Academica-e están protegidos por derechos de autor con todos los derechos reservados, a no ser que se indique lo contrario.