DEVICE AND METHOD FOR DENOISING OF ELECTROENCEPHALOGRAPHY SIGNAL USING SEGMENT-BASED PRINCIPAL COMPONENT ANALYSIS

摘要

Provided is a method for denoising of electroencephalography. The method for denoising of electroencephalography (EEG) includes: generating a two-dimensional data matrix (X) from a one-dimensional EEG signal (x), based on segmentation; generating an eigenvector matrix (E) from the two-dimensional data matrix (X), using principal component analysis (PCA); and removing noise in the one-dimensional EEG signal (x), based on a center-frequency and kurtosis for each of a plurality of eigenvectors. The device for denoising of electroencephalography is also provided.