EEG based biometrics using emotional stimulation data

Raihan Khalil, A. Arasteh, A. K. Sarkar
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引用次数: 3

Abstract

EEG based biometrics using linear Support Vector Machine (SVM) is proposed in this paper. Human identification using electroencephalographic signal was done in this research. Reliability of most of the biometrics systems is not up to the mark because of the possibility of being faked or duplicated. Here, the brain signatures were used as a possible biometric identifier. A Database for Emotion Analysis using Physiological Signals containing 40 trials from each participant was used. International 10–20 system of EEG electrode placement was employed and data from Cz electrode was taken for this research. Some researches showed nice performance with few subjects. Here, 20 subjects were used from the dataset for the system. With this, the system gives 77% mean precision and at the same time 100% detection accuracy.
基于情绪刺激数据的脑电图生物识别技术
提出了一种基于脑电图的线性支持向量机(SVM)生物特征识别方法。本研究利用脑电图信号进行人体识别。由于存在伪造或复制的可能性,大多数生物识别系统的可靠性都达不到标准。在这里,大脑特征被用作可能的生物识别标识。使用了包含每个参与者40个试验的生理信号情绪分析数据库。采用国际10-20 EEG电极放置系统,采用Cz电极数据进行研究。一些研究表明,在少数受试者中表现良好。在这里,从系统的数据集中使用了20名受试者。因此,该系统的平均精度为77%,同时检测精度为100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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