A lever-like EEG feature-extraction method based on the Hurst exponent and regression-fitting errors is proposed for identifying beta rhythms. The proposed method is superior to most methods using the time- and frequency-domain feature extraction parameters for identifying beta rhythms.
.In our study of EEG during Zen-Buddhism meditation, EEG signals recorded sometimes exhibit complex baseline drift caused by eye movement, deep breathing, etc. The baseline drift affects the grading of stages of meditation according to EEG rhythms. This paper describes a new method for EEG baseline drift correction. The method, utilizing the adaptive scheme, is able to extract the complex...