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一种基于ICEEMDAN和SAX的方法,使用功能近红外光谱信号来确定英语阅读理解状态

Ural Akincioglu^1,2, Onder Aydemir^2,3, Ahmet Cil^1,2

¹Electronics and Communication Engineering Department of Faculty of Technology, Karadeniz Technical University, Trabzon, Türkiye.

|July 23, 2025

概括

这项研究引入了一种使用大脑信号来评估英语阅读理解的新方法. 该技术结合了改进的互补集合体实证模式分解与适应性噪声 (ICEEMDAN) 和符号总量近似 (SAX) 进行准确的评估.

科学领域:

神经科学是一个神经科学.
认知科学认知科学
生物医学工程生物医学工程

背景情况:

准确的阅读理解评估对于教育和日常生活至关重要.
传统的方法可能是主观和耗时的.
脑信号分析为客观评估提供了一个有希望的途径.

研究的目的:

开发和评估一个客观的方法来评估全文阅读理解使用功能近红外光谱 (fNIRS) 信号.
为此目的,研究一种结合ICEEMDAN和SAX的新信号处理技术的有效性.
为了比较不同的标签策略来训练分类模型.

主要方法:

利用功能近红外光谱 (fNIRS) 来记录15名参与者阅读英语文本的脑活动.
应用了改进的互补集体实证模式分解与自适应噪声 (ICEEMDAN) 进行信号预处理.
采用符号总和近似 (SAX) 进行特征提取,其次是k-NN分类.
评估了三个标签策略:多选题,自我评估分数和双验证方法.

主要成果:

拟议的方法实现了分类准确率为74.67% (多选项),66.37% (自我评估) 和89.02% (双验证).
双验证标签策略获得了最高的准确性,证明了可靠的理解评估.
基于ICEEMDAN和SAX的方法有效地从fNIRS信号中识别了阅读理解状态.

结论:

开发的基于ICEEMDAN和SAX的方法为评估全文阅读理解提供了准确和客观的手段.
使用fNIRS进行脑信号分析,对实时教育和诊断应用具有重大潜力.
双验证标签策略提高了基于大脑的理解评估的可靠性.

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