MOTOR IMAGERY FOR EEG BIOMETRICS USING CONVOLUTIONAL NEURAL NETWORK

被引：0
|
作者：
Das, Rig [1 ]
Maiorana, Emanuele [1 ]
Campisi, Patrizio [1 ]
机构：
[1] Roma Tre Univ, Sect Appl Elect, Dept Engn, Via Vito Volterra 62, I-00146 Rome, Italy
来源：
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2018年
关键词：
Electroencephalography; Motor imagery; Convolutional neural network; RECOGNITION;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
This paper deals with electroencephalography (EEG)-based biometric identification, using a motor imagery task, specifically performing imaginary arms and legs movements. Deep learning methods such as convolutional neural network (CNN) is used for automatic discriminative feature extraction and person identification. An extensive set of experimental tests, performed on a large database comprising EEG data collected from 40 subjects over two different sessions taken at a week distance, shows the existence of repeatable discriminative characteristics in individuals' brain signals.
引用
收藏
页码：2062 / 2066
页数：5
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