Toggle Main Menu Toggle Search

Open Access padlockePrints

Prediction of arm movement trajectories from ECoG-recordings in humans

Lookup NU author(s): Dr Tobias Pistohl

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


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.


Publication metadata

Author(s): Pistohl T, Ball T, Schulze-Bonhage A, Aertsen A, Mehring C

Publication type: Article

Publication status: Published

Journal: Journal of Neuroscience Methods

Year: 2008

Volume: 167

Issue: 1

Pages: 105-114

ISSN (print): 0165-0270

ISSN (electronic): 1872-678X

Publisher: Elsevier

URL: http://dx.doi.org/10.1016/j.jneumeth.2007.10.001

DOI: 10.1016/j.jneumeth.2007.10.001


Altmetrics

Altmetrics provided by Altmetric


Share