Application and Contrast in Brain-Computer Interface between Hilbert-Huang Transform and Wavelet Transform

Brain-computer interface (BCI) can make people control machines through electroencephalogram (EEG) which produced by brain activities. It provides a new communication method between human and environment and extents human´s ability to control machines. One of the key points of BCI system is how to abstract and distinguish different EEG features. Therefore, EEG signal processing method is the focus of BCI. This article analyzed Wavelet Transform method and Hilbert-Huang Transform (HHT) method. The results indicate that both these two methods can abstract the main characters of the EEG. But HHT can more accurately express EEG distribution in time and frequency domain. That´s because it can produce a self-adaptive basis according to the signal data and obtain local and instantaneous frequency of EEG.