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Limited By:	Author = Kocijan, Jus;

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An exploration of EEG features during recovery following stroke – implications for BCI-mediated neurorehabilitation therapy (2014)

Leamy, Darren J.; Kocijan, Jus; Domijan, Katarina; Duffin, Joseph; Roche, Richard; Comm...

An exploration of EEG features during recovery following stroke – implications for BCI-mediated neurorehabilitation therapy (2014)

Leamy, Darren J.; Kocijan, Jus; Domijan, Katarina; Duffin, Joseph; Roche, Richard; Commins, Sean; Collins, Ronan; Ward, Tomas E.

Abstract:

Background: Brain-Computer Interfaces (BCI) can potentially be used to aid in the recovery of lost motor control in a limb following stroke. BCIs are typically used by subjects with no damage to the brain therefore relatively little is known about the technical requirements for the design of a rehabilitative BCI for stroke. Methods: 32-channel electroencephalogram (EEG) was recorded during a finger-tapping task from 10 healthy subjects for one session and 5 stroke patients for two sessions approximately 6 months apart. An off-line BCI design based on Filter Bank Common Spatial Patterns (FBCSP) was implemented to test and compare the efficacy and accuracy of training a rehabilitative BCI with both stroke-affected and healthy data. Results: Stroke-affected EEG datasets have lower 10-fold cross validation results than healthy EEG datasets. When training a BCI with healthy EEG, average classification accuracy of stroke-affected EEG is lower than the average for healthy EEG. Classificati...

http://mural.maynoothuniversity.ie/6074/

Marked Mark

An exploration of EEG features during recovery following stroke - implications for BCI-mediated neurorehabilitation therapy (2014)

Leamy, Darren J; Kocijan, Juš; Domijan, Katarina; Duffin, Joseph; Roche, Richard AP; Co...

An exploration of EEG features during recovery following stroke - implications for BCI-mediated neurorehabilitation therapy (2014)

Leamy, Darren J; Kocijan, Juš; Domijan, Katarina; Duffin, Joseph; Roche, Richard AP; Commins, Sean; Collins R; Ward, Tomas E

Abstract:

Abstract Background Brain-Computer Interfaces (BCI) can potentially be used to aid in the recovery of lost motor control in a limb following stroke. BCIs are typically used by subjects with no damage to the brain therefore relatively little is known about the technical requirements for the design of a rehabilitative BCI for stroke. Methods 32-channel electroencephalogram (EEG) was recorded during a finger-tapping task from 10 healthy subjects for one session and 5 stroke patients for two sessions approximately 6 months apart. An off-line BCI design based on Filter Bank Common Spatial Patterns (FBCSP) was implemented to test and compare the efficacy and accuracy of training a rehabilitative BCI with both stroke-affected and healthy data. Results Stroke-affected EEG datasets have lower 10-fold cross validation results than healthy EEG datasets. When training a BCI with healthy EEG, average classification ...

http://dx.doi.org/10.1186/1743-0003-11-9

Marked Mark

Using Gaussian Process Models for Near-Infrared Spectroscopy Data Interpolation (2010)

Leamy, Darren J.; Ward, Tomas E.; Kocijan, Jus

Using Gaussian Process Models for Near-Infrared Spectroscopy Data Interpolation (2010)

Leamy, Darren J.; Ward, Tomas E.; Kocijan, Jus

Abstract:

Gaussian Process (GP) model interpolation is used extensively in geostatistics. We investigated the effectiveness of using GP model interpolation to generate maps of cortical activity as measured by Near Infrared Spectroscopy (NIRS). GP model interpolation also produces a variability map, which indicates the reliability of the interpolated data. For NIRS, cortical hemodynamic activity is spatially sampled. When generating cortical activity maps, the data must be interpolated. Popular NIRS imaging software HomER uses Photon Migration Imaging (PMI) and Diffuse Optical Imaging (DOI) techniques based on models of light behaviour to generate activity maps. Very few non-parametric methods of NIRS imaging exist and none of them indicate the reliability of the interpolated data. Our GP model interpolation algorithm and HomER produced activity maps based on data generated from typical functional NIRS responses. Image results in HomER were taken as the bench mark as the images produced are co...

http://mural.maynoothuniversity.ie/3861/

Displaying Results 1 - 3 of 3 on page 1 of 1