Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1195-1204 |
| Number of pages | 10 |
| Journal | Medical Engineering and Physics |
| Volume | 38 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 2016 Nov 1 |
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Keywords
- Brain–computer interfacing
- Functional electrical stimulation
- Motor imagery
- Neuralprosthesis
ASJC Scopus subject areas
- Biophysics
- Biomedical Engineering
Cite this
EEG-based BCI for the linear control of an upper-limb neuroprosthesis. / Vidaurre, Carmen; Klauer, Christian; Schauer, Thomas; Ramos-Murguialday, Ander; Muller, Klaus.
In: Medical Engineering and Physics, Vol. 38, No. 11, 01.11.2016, p. 1195-1204.Research output: Contribution to journal › Article
}
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 - Muller, Klaus
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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UR - http://www.scopus.com/inward/citedby.url?scp=84994493633&partnerID=8YFLogxK
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 - Medical Engineering and Physics
JF - Medical Engineering and Physics
SN - 1350-4533
IS - 11
ER -