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ACSSC
2015

A cortical activity localization approach for decoding finger movements from human electrocorticogram signal

7 years 11 months ago
A cortical activity localization approach for decoding finger movements from human electrocorticogram signal
—A novel approach for decoding the finger flexion and extension from the human electrocorticogram is proposed. First, for different finger movements, we use projected MUltiple SIgnal Classification (projected MUSIC) as a source localization technique to estimate the active areas in the primary motor cortex. Next, in order to distinguish between the flexion and extension, the results of the single-trial-based source localizations are fed as the input features to a classifier for decoding. The performance of different techniques such as Support Vector Machine (SVM), Perceptron, and the k-Nearest-Neighbor (kNN) are investigated and the resulting classification accuracies are
Seyede Mahya Safavi, Alireza Shahan Behbahani, Ahm
Added 13 Apr 2016
Updated 13 Apr 2016
Type Journal
Year 2015
Where ACSSC
Authors Seyede Mahya Safavi, Alireza Shahan Behbahani, Ahmed M. Eltawil, Zoran Nenadic, An H. Do
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