TY - JOUR
T1 - EEG-based BCI for the linear control of an upper-limb neuroprosthesis
AU - Vidaurre, Carmen
AU - Klauer, Christian
AU - Schauer, Thomas
AU - Ramos-Murguialday, Ander
AU - Müller, Klaus Robert
N1 - Funding Information:
The authors thankfully acknowledge Javier Pascual for his help and dedication. They are also grateful to the reviewers for their constructive criticisms. The research leading to these results has received funding from the European Community’s Seventh Framework Programme under grant MUNDUS and HUMOUR-ICT-2008-231724, the European Union’s PASCAL 2 Network of Excellence (ICT-216886), the German Research Foundation DFG project KU 1453-1 , DFG SPP 1527 , MU 987/14-1 , as well as the by the Brain Korea 21 Plus Program of the National Research Foundation of Korea funded by the Ministry of Education, Republic of Korea . This publication only reflects the authors’ views. The authors declare not to have any conflicts of interest.
Publisher Copyright:
© 2016 IPEM
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/11/1
Y1 - 2016/11/1
N2 - Assistive technologies help patients to reacquire interacting capabilities with the environment and improve their quality of life. In this manuscript we present a feasibility study in which healthy users were able to use a non-invasive Motor Imagery (MI)-based brain computer interface (BCI) to achieve linear control of an upper-limb functional electrical stimulation (FES) controlled neuro-prosthesis. The linear control allowed the real-time computation of a continuous control signal that was used by the FES system to physically set the stimulation parameters to control the upper-limb position. Even if the nature of the task makes the operation very challenging, the participants achieved a mean selection accuracy of 82.5% in a target selection experiment. An analysis of limb kinematics as well as the positioning precision was performed, showing the viability of using a BCI–FES system to control upper-limb reaching movements. The results of this study constitute an accurate use of an online non-invasive BCI to operate a FES-neuroprosthesis setting a step toward the recovery of the control of an impaired limb with the sole use of brain activity.
AB - Assistive technologies help patients to reacquire interacting capabilities with the environment and improve their quality of life. In this manuscript we present a feasibility study in which healthy users were able to use a non-invasive Motor Imagery (MI)-based brain computer interface (BCI) to achieve linear control of an upper-limb functional electrical stimulation (FES) controlled neuro-prosthesis. The linear control allowed the real-time computation of a continuous control signal that was used by the FES system to physically set the stimulation parameters to control the upper-limb position. Even if the nature of the task makes the operation very challenging, the participants achieved a mean selection accuracy of 82.5% in a target selection experiment. An analysis of limb kinematics as well as the positioning precision was performed, showing the viability of using a BCI–FES system to control upper-limb reaching movements. The results of this study constitute an accurate use of an online non-invasive BCI to operate a FES-neuroprosthesis setting a step toward the recovery of the control of an impaired limb with the sole use of brain activity.
KW - Brain–computer interfacing
KW - Functional electrical stimulation
KW - Motor imagery
KW - Neuralprosthesis
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U2 - 10.1016/j.medengphy.2016.06.010
DO - 10.1016/j.medengphy.2016.06.010
M3 - Article
C2 - 27425203
AN - SCOPUS:84994493633
VL - 38
SP - 1195
EP - 1204
JO - Journal of Biomedical Engineering
JF - Journal of Biomedical Engineering
SN - 1350-4533
IS - 11
ER -