Prediction of arm movement trajectories from ECoG-recordings in humans

T Pistohl, T Ball, A Schulze-Bonhage, A Aertsen…�- Journal of neuroscience�…, 2008 - Elsevier
Journal of neuroscience methods, 2008Elsevier
Electrocorticographic (ECoG) signals have been shown to contain reliable information about
the direction of arm movements and can be used for on-line cursor control. These findings
indicate that the ECoG is a potential basis for a brain-machine interface (BMI) for application
in paralyzed patients. However, previous approaches to ECoG-BMIs were either based on
classification of different movement patterns or on a voluntary modulation of spectral
features. For a continuous multi-dimensional BMI control, the prediction of complete�…
Electrocorticographic (ECoG) signals have been shown to contain reliable information about the direction of arm movements and can be used for on-line cursor control. These findings indicate that the ECoG is a potential basis for a brain-machine interface (BMI) for application in paralyzed patients. However, previous approaches to ECoG-BMIs were either based on classification of different movement patterns or on a voluntary modulation of spectral features. For a continuous multi-dimensional BMI control, the prediction of complete movement trajectories, as it has already been shown for spike data and local field potentials (LFPs), would be a desirable addition for the ECoG, too. Here, we examined ECoG signals from six subjects with subdurally implanted ECoG-electrodes during continuous two-dimensional arm movements between random target positions. Our results show that continuous trajectories of 2D hand position can be approximately predicted from the ECoG recorded from hand/arm motor cortex. This indicates that ECoG signals, related to body movements, can directly be transferred to equivalent controls of an external effector for continuous BMI control.
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