Clark I, Biscay R, Echeverría M, Virués T
Cuban Neurosciences Center, Ciudad Habana, Cuba.
Comput Biol Med. 1995 Jul;25(4):373-82. doi: 10.1016/0010-4825(95)00014-u.
Wavelet representation is a recent development in the analysis of non-stationary signals. Its possibilities for use in the description of time-frequency characteristics of both transients in spontaneous EEG and time-varying rhythms in event related brain activity are explored here. By way of illustration, multiresolution decompositions of a wide variety of EEG transients are carried out in this work, including spike-and-waves, single spikes, sharp waves, blink artifacts, frontal intermittent rhythmic delta activity (FIRDA) and paroxysmal delta activity. Also, the application of the wavelet representation to study related spectra perturbations is illustrated with data from psychophysical experiments on the perception of image motion. The results demonstrate the capabilities of the wavelet transform, as an alternative to the Fourier transform, for the representation and analysis of non-stationary EEG signals.
小波表示法是分析非平稳信号的一项最新进展。本文探讨了其在描述自发脑电图瞬变的时频特征以及事件相关脑活动中的时变节律方面的应用可能性。作为示例，本文对多种脑电图瞬变进行了多分辨率分解，包括棘波和慢波、单个棘波、锐波、眨眼伪迹、额叶间歇性节律性δ活动（FIRDA）和阵发性δ活动。此外，通过关于图像运动感知的心理物理学实验数据，说明了小波表示法在研究相关频谱扰动方面的应用。结果表明，小波变换作为傅里叶变换的替代方法，能够用于表示和分析非平稳脑电图信号。
