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      Prediction of arm movement trajectories from ECoG-recordings in humans.

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          Abstract

          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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          Author and article information

          Journal
          J Neurosci Methods
          Journal of neuroscience methods
          Elsevier BV
          0165-0270
          0165-0270
          Jan 15 2008
          : 167
          : 1
          Affiliations
          [1 ] Bernstein Center for Computational Neuroscience, Albert-Ludwigs-University, Freiburg, Germany. tobias.pistohl@biologie.uni-freiburg.de
          Article
          S0165-0270(07)00484-0
          10.1016/j.jneumeth.2007.10.001
          18022247
          b2d713f1-8fe9-4bfa-8f6d-c674f30a9d18
          History

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