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EEG identification and differentiation for left-handedness

机译:EEG识别和左撇子的分化

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In this paper, we investigated a new left-handedness identification module to identify the handedness of a person. The Electroencephalogram (EEG) data were obtained to detect the features and characteristics of left-handers. The subjects were required to relax and view the video clips provided. The handedness of the subject can be identified from the EEG data obtained using the left-handedness module. These EEG signals were obtained from A1, O1 and O2 locations and dassified into four different frequency bands, namely: Alpha, Beta, Delta and Theta, to determine the Mean EEG Coherence (MEC). Based on our observations, the left handed subject has higher Mean EEG Coherence, reflecting significant communications and relationship between the right and left hemisphere of cerebrums in the corpus callosum. From our analysis, the left-handers have been discovered with increased functional interaction between cerebral hemispheres and increased corpus callosum size. Therefore, the left-handedness is identified based on the increased size of corpus callosum, that allows greater inter-hemispheric linkage and communication. The developed handedness identification system has shown significant performance to identify subjects with left-handedness.
机译:在本文中,我们调查了一个新的左撇子识别模块来识别人的手中。获得脑电图(EEG)数据以检测左撇子的特征和特征。需要对象来放松和查看所提供的视频剪辑。可以从使用左撇子模块获得的EEG数据识别对象的手性。这些EEG信号是从A1,O1和O2位置获得的,并将其分配成四种不同的频带,即:α,β,Δ和θ,以确定平均EEG相干性(MEC)。基于我们的观察,左手受试者平均脑电图一致性较高,反映了语料库胼um脑左右半球之间的显着通信和关系。从我们的分析中,已经发现左撇子在脑半球之间的功能相互作用增加和胼call病变增加。因此,基于胼um的增加的尺寸来鉴定左撇子,这允许更大的半球连杆和通信。发达的负责人识别系统显示出具有左手的主体的显着性能。

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