Comparison of Adaptive Cancellation and Laplacian Operation in Removing Eye Blinking Artifacts in EEG

The long-term goal of our project is to develop a brain computer interface for locked-in patients. In this study, we designed a controlled experiment and compared the efficacy of real-time adaptive cancellation and Laplacian operation in removing eye blinking artifacts in EEG. Scalp EEG was recorded while the subject performed thumb movements in three different states of eye blinking, i.e., persisted eye opening, persisted eye closure and natural blinking. The collected data were preprocessed with one of three preprocessing algorithms, namely, adaptive cancellation, Laplacian operation and null and, then, passed through windowed Fourier transform to calculate the change of wave power. Templates of wave power were derived by averaging the whole set. Correlation coefficients of templates and single-pass experimental results were calculated and a threshold value of coefficient was chosen to define the detection of thumb movements. The validity of detection was tested by EMG of thumb extensor. The efficacy of preprocessing algorithms was evaluated by ANOVA and chi-square tests. The results showed that, compared with the control group, both adaptive cancellation and Laplacian operation enhanced the wave suppression percentage. There is no difference between the group results of two preprocessing methods, while the individual difference is prominent. The implication of the effect of preprocessing on enhancing event detection rate is discussed.