Recognizing brain activities by functional near-infrared spectroscope signal analysis.

Nonlinear biomedical physics Pub Date : 2008-07-01 DOI:10.1186/1753-4631-2-3

Truong Quang Dang Khoa, Masahiro Nakagawa

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引用次数: 22

Abstract

Background: Functional Near-Infrared Spectroscope (fNIRs) is one of the latest technologies which utilize light in the near-infrared range to determine brain activities. Near-infrared technology allows design of safe, portable, wearable, non-invasive and wireless qualities monitoring systems. This indicates that fNIRs signal monitoring of brain hemodynamics can be value in helping to understand brain tasks. In this paper, we present results of fNIRs signal analysis to show that there exist distinct patterns of hemodynamic responses which recognize brain tasks toward developing a Brain-Computer interface.

Results: We applied Higuchi's fractal dimension algorithms to analyse irregular and complex characteristics of fNIRs signals, and then Wavelets transform is used to analysis for preprocessing as signal filters and feature extractions and Neural networks is a module for cognition brain tasks.

Conclusion: Throughout two experiments, we have demonstrated the feasibility of fNIRs analysis to recognize human brain activities.

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功能近红外光谱信号分析识别脑活动。

背景:功能近红外光谱仪(fNIRs)是利用近红外范围内的光来测定大脑活动的最新技术之一。近红外技术允许设计安全、便携、可穿戴、非侵入性和无线质量监测系统。这表明fNIRs信号监测脑血流动力学可以帮助理解大脑任务的价值。在本文中，我们展示了fNIRs信号分析的结果，表明存在不同的血流动力学响应模式，以识别大脑任务，以开发脑机接口。结果:应用Higuchi分形维数算法分析近红外信号的不规则和复杂特征，然后利用小波变换进行分析预处理作为信号滤波和特征提取，神经网络作为认知脑任务的模块。结论:通过两个实验，我们证明了fNIRs分析识别人脑活动的可行性。

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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Nonlinear biomedical physics

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