Person Identification Using Evoked Potentials and Peak Matching

G. K. Singhal, Pavan Ramkumar
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引用次数: 47

Abstract

In this paper, we explore visually evoked potentials (VEPs) as a potential tool for biometric identification. Using a clinical stimulation paradigm, single channel pattern onset VEPs are recorded from raw EEG from 10 healthy male subjects aged between 20 and 24. Following this, two feature extraction techniques are employed to characterize the signals. Specifically, a novel, physiologically relevant peak matching algorithm is proposed and its performance is compared to features obtained from multi-resolution wavelet analysis. Once suitably characterized, the VEPs from different individuals are classified using a standard distance-measure based algorithm.
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基于诱发电位和峰值匹配的人物识别
在本文中,我们探索视觉诱发电位(VEPs)作为生物特征识别的潜在工具。采用临床刺激模式,记录了10例20 ~ 24岁健康男性受试者的原始脑电图单通道模式vep。随后,采用两种特征提取技术对信号进行表征。具体而言,提出了一种新的生理相关峰值匹配算法,并将其性能与多分辨率小波分析获得的特征进行了比较。一旦适当的特征,来自不同个体的vep使用基于标准距离测量的算法进行分类。
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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