Thuraisingham Ranjit A, Tran Yvonne, Craig Ashley, Nguyen Hung
Rehabilitation Studies Unit, University of Sydney.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:2865-8. doi: 10.1109/EMBC.2012.6346561.
Frequency analysis based on the Hilbert-Huang transform (HHT) is examined as an alternative to Fourier spectral analysis in the study of EEG signals. This method overcomes the need for the EEG signal to be linear and stationary, assumptions necessary for the application of Fourier spectral analysis. The HHT method comprises two components: empirical mode decomposition (EMD) of the signal into intrinsic mode functions (IMF's); and the Hilbert transform of the IMF's. This technique is applied here in the study of consecutive eyes open (EO), eyes closed (EC) EEG signals of able bodied and spinal cord injured participants. The study found that in this EO, EC pair the instantaneous frequencies in the EO state were higher compared to the EC state. The Hilbert weighted frequency, a measure of the mean of the instantaneous frequencies present in an IMF, is used here to detect these changes from EO to the EC state in an EEG signal. Although there was a good detection of this change with information obtained from just one IMF (94% in able-bodied persons and 84% in SCI persons), almost 100% success in detecting between group differences was achieved using all the IMF's. This result has implications for assistive technology that rely on EEG changes in EO and EC states.
在脑电图（EEG）信号研究中，基于希尔伯特-黄变换（HHT）的频率分析被视为傅里叶频谱分析的一种替代方法进行研究。该方法克服了傅里叶频谱分析应用中对EEG信号线性和平稳性的要求，而这两个假设对于傅里叶频谱分析的应用是必要的。HHT方法包括两个部分：将信号进行经验模态分解（EMD）为固有模态函数（IMF）；以及对IMF进行希尔伯特变换。这项技术在此处应用于对健全人和脊髓损伤参与者连续睁眼（EO）、闭眼（EC）EEG信号的研究。研究发现，在这种EO-EC对中，EO状态下的瞬时频率高于EC状态。希尔伯特加权频率是一种衡量IMF中存在的瞬时频率平均值的指标，在此用于检测EEG信号中从EO状态到EC状态的这些变化。尽管仅从一个IMF获得的信息就能很好地检测到这种变化（健全人中有94%，脊髓损伤者中有84%），但使用所有IMF在检测组间差异方面几乎取得了100%的成功。这一结果对依赖EO和EC状态下EEG变化的辅助技术具有启示意义。
