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Updated: Jan 9, 2026

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

人类内EEG生物识别识别

Benjamin M Belay, Stamos Katsigiannis

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|December 3, 2025

概括

内脑电图 (iEEG) 显示出人类生物识别的前景,在同一会话识别中达到95.84%的准确性. 这种新的方法克服了传统EEG生物识别的局限性,证明了对模板老化的弹性.

科学领域:

神经科学是一个神经科学.
生物识别信息生物识别信息
信号处理信号处理

背景情况:

传统的脑电图 (EEG) 生物识别技术面临诸如模板老化等挑战.
内脑电图 (iEEG) 提供了一个强大的生物识别的潜在替代方案.

研究的目的:

调查使用iEEG信号用于人类生物识别的可行性.
开发和评估基于iEEG的生物识别的处理管道.
评估iEEG生物识别在同一会话和跨会话场景中的性能.

主要方法:

开发了一个全面的管道来处理原始iEEG信号.
使用了由78名受试者组成的重新设计的iEEG数据集.
通过同一会期和跨会期的识别测试来评估绩效.

主要成果:

实现了95.84%的同一会话识别准确度.
在跨会话分析中,iEEG信号对模板衰老的证明弹性.
展示了iEEG生物识别系统的增量学习能力.

结论:

内脑电图 (iEEG) 信号是人类生物识别的可行和有效方式.

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与传统的EEG方法相比,iEEG生物识别技术具有优势,特别是在克服模板老化方面.

这项概念验证研究为安全可靠的生物识别解决方案开辟了新的途径.