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EEG ANALYSIS FOR DIGIT RECOGNITION BY TACTILE AND VTBROTACTILE STIMULATIONS

机译:触觉和振动触觉刺激的数字识别的EEG分析

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Artificial rehabilitative aids to enable object recognition to the disabled as well as robot aided and telenavigating systems require sending feedback signals to the human operator to enable accurate control. This work is a preliminary step towards the development of such systems using a Brain Computer Interface. In this work Electroencephalography (EEG) responses to tactile and vibrotactile stimulations, as alternate sensory means than vision, for recognizing ten digits, 0 to 9, has been studied. During tactile stimulation subjects are instructed to palpate digits embossed on plain surfaces, while vibrotactile stimulus is provided by vibrating motors attached to the subjects' skin over their clothing in specific patterns resembling the seven segment display of digits. EEG analysis involves feature extraction and classification into the respective digit classes. Correlation between the EEG features from the two stimulations is investigated and a nonlinear correlation is found to exist between them. A maximum classification accuracy of 73.17%, average over ten digit classes and all subjects under experimentation is observed for vibrotactually stimulated EEG analysis.
机译:人工康复辅助设备能够使对象识别能够对残疾以及机器人辅助和电话连接系统需要向人类运营商发送反馈信号以实现准确的控制。这项工作是促进使用脑电脑界面开发此类系统的初步步骤。在该工作中,对触觉和振动刺激的反应是易于视觉的交替感觉刺激,对于识别10位,0至9,已经研究了0至9。在触觉刺激后,被指示在普通表面上压花的触诊数字,而振动刺激通过在类似于七个段显示的特定模式的特定模式上通过衣服附着在受试者皮肤上的振动电机提供。 EEG分析涉及特征提取和分类到相应的数字类别中。研究了来自两个刺激的EEG特征之间的相关性,并且发现它们之间存在非线性相关性。最大分类精度为73.17%,平均为10位数类,以及在实验下的所有受试者进行振凸刺激的脑电图分析。

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