University of Bahrain
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PCA Based EEG Event Features Extraction for Robotics Dexterous Grasping

Show simple item record Mattar, Ebrahim Al-Junaid, Hessa Al-Seddiqi, Hamad 2018-07-09T07:14:26Z 2018-07-09T07:14:26Z 2017-09-01
dc.identifier.issn 2210-142X
dc.description.abstract The presented work is dedicated towards deep understanding of resulting Electroencephalography (EEG) brainwaves during a typical grasp and lift human grasping task. During grasping, forces are applied by fingertips dexterously, as observed through resulting EEG waves. For mirroring this to a dexterous robotic hand, methods have to be developed to find features for optimal forces, movements, and right finger joints displacements. Resulting EEG brainwaves during grasp and lift task are very useful, however these EEG waves are related, correlated, complicated, and raw. With the potential and analysis of Principal Components Analysis (PCA) of EEG, it indicated an overlap of valuable neural behaviors from various locations over the human skull, indicating interrelated and coupled events for robotic grasping. PCA has been used to unlock few main features of EEG waves during a grasp and lift task. The foremost grasping features are hence used in creating events for a robotic dexterous grasping. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-ShareAlike 4.0 International *
dc.rights.uri *
dc.subject Electroencephalography (EEG) en_US
dc.subject Robotics Learning en_US
dc.subject Grasping en_US
dc.subject PCA en_US
dc.title PCA Based EEG Event Features Extraction for Robotics Dexterous Grasping en_US
dc.type Article en_US
dc.volume 06
dc.issue 05
dc.pagestart 251
dc.pageend 260
dc.source.title International Journal of Computing and Digital Systems
dc.abbreviatedsourcetitle IJCDS

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