【摘要】 近红外光谱技术(Near-infrared spectroscopy,NIRS)已被广泛应用于无损大脑功能检测,然而传统时频分析方法并不适用于非稳态、非线性的血氧信号。在视觉刺激实验中,采集被试前额叶的血氧信号,分别比较了傅里叶谱分析法、小波谱分析法和希尔伯特黄变换(Hilbert-Huang transform,HHT)方法在近红外脑功能成像信号分析中应用的结果。实验表明基于希尔伯特黄变换的谱分析方法优于其它两种方法,并且使近红外光谱研究可以采用事件相关设计的实验,为形成近红外光谱信号分析的标准方法开辟了新的途径。更多还原

【Abstract】 Near-infrared spectroscopy(NIRS) has been widely used to access the brain functional activity non-invasively,but traditional signal analysis methods are unsuitable for non-linear and non-stationary data.A novel signal processing method is developed by using Hilbert-Huang transform (HHT) to perform spectral analysis of functional NIRS signals sampled in a vision stimulation experiment based on event-related design.Compared with wavelet based multi-resolution analysis(MRA) and Fourier spectral analysis,we demonstrate that the HHT method is better in the extraction of task related signal for observation of activation in the prefrontal cortex.This method indicates a new analytical tool for functional NIRS signals and enables us to understand the episode of functional NIRS more precisely.更多还原