TY - GEN
T1 - Functional connectivity analysis of motor imagery EEG signal for brain-computer interfacing application
AU - Ghosh, Poulami
AU - Mazumder, Ankita
AU - Bhattacharyya, Saugat
AU - Tibarewala, D. N.
AU - Hayashibe, Mitsuhiro
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/1
Y1 - 2015/7/1
N2 - The human brain can be considered as a graphical network having different regions with specific functionality and it can be said that a virtual functional connectivity are present between these regions. These regions are regarded as nodes and the functional links are regarded as the edges between them. The intensity of these functional links depend on the activation of the lobes while performing a specific task(e.g. motor imagery tasks, cognitive tasks and likewise). The main aim of this study is to understand the activation of the parts of the brain while performing three types of motor imagery tasks with the help of graph theory. Two indices of the graph, namely Network Density and Node Strength are calculated for 32 electrodes placed on the subject's head covering all the brain lobes and the nodes having higher intensity are identified.
AB - The human brain can be considered as a graphical network having different regions with specific functionality and it can be said that a virtual functional connectivity are present between these regions. These regions are regarded as nodes and the functional links are regarded as the edges between them. The intensity of these functional links depend on the activation of the lobes while performing a specific task(e.g. motor imagery tasks, cognitive tasks and likewise). The main aim of this study is to understand the activation of the parts of the brain while performing three types of motor imagery tasks with the help of graph theory. Two indices of the graph, namely Network Density and Node Strength are calculated for 32 electrodes placed on the subject's head covering all the brain lobes and the nodes having higher intensity are identified.
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U2 - 10.1109/NER.2015.7146597
DO - 10.1109/NER.2015.7146597
M3 - Conference contribution
AN - SCOPUS:84940366627
T3 - International IEEE/EMBS Conference on Neural Engineering, NER
SP - 210
EP - 213
BT - 2015 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
PB - IEEE Computer Society
T2 - 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
Y2 - 22 April 2015 through 24 April 2015
ER -