Garn Heinrich, Waser Markus, Lechner Manuel, Dorfer Matthias, Grossegger Dieter
Austrian Institute of Technology GmbH, Vienna, Austria.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:2227-31. doi: 10.1109/EMBC.2012.6346405.
We analyzed three different approaches to automatic real-time monitoring of the time course of individual alpha frequencies (IAFs) of the human electro-encephalograms. Fast Fourier transform and wavelet transform were compared to classical automated cycle counting in the time domain. With fast Fourier and wavelet transform, test results with healthy adult subjects, demented and psychiatric patients revealed typical short-term variations of the instantaneous IAFs of about ± 2 Hz. When cycles were counted in the time domain, however, variations of only ± 1 Hz were recorded. Thus, IAF measurement in the time domain appears to be particularly suitable. We also observed long-term IAF trends that typically amounted to about ± 0.5 to ± 1.0 Hz. Therefore, our hypothesis is that the IAF does not constitute an intra-individual constant but varies with time and cognitive state. Our fully automatic real-time signal-processing procedure includes pre-processing for artifact detection and for localization of segments with synchronized alpha oscillations where the IAF should preferably be measured.
我们分析了三种用于自动实时监测人类脑电图中个体阿尔法频率（IAF）时间进程的不同方法。将快速傅里叶变换和小波变换与传统的时域自动周期计数法进行了比较。通过快速傅里叶变换和小波变换，对健康成年受试者、痴呆患者和精神疾病患者的测试结果显示，瞬时IAF存在典型的短期变化，约为±2赫兹。然而，在时域中进行周期计数时，记录到的变化仅为±1赫兹。因此，时域中的IAF测量似乎特别合适。我们还观察到长期的IAF趋势，通常约为±0.5至±1.0赫兹。因此，我们的假设是，IAF并非个体内部的恒定值，而是随时间和认知状态而变化。我们的全自动实时信号处理程序包括用于伪迹检测的预处理，以及用于定位具有同步阿尔法振荡的片段的预处理，IAF最好在这些片段中进行测量。
