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Short Time Fourier Transform based Dominant Frequency Extraction Algorithm for Brain Computer Interface Systems

Abstract : In this paper authors propose a novel method of dominant frequency detection, based on the short time Fourier transforms (STFT), to quantify and visualize the information as feature contains in the specific frequency bands defined in the analysis of electroencephalogram (EEG) signal for brain computer interface (BCI). The raw EEG subjected to band pass filter. The filtered signal subjected to the proposed algorithm for calculating the variance of relative power spectral intensity. The dominant frequency components are easily identified by analyzing the variance of relative power spectral intensity using proposed method. The effectiveness of proposed method of EEG signal processing is validated by self-generated artificial sine wave signal, Steady State Visual Evoked Potential (SSVEP) data set and single subject Movement Imagery (MI) BCI competition data set.

Keyword : Brain-computer interface (BCI), Electroencephalogram (EEG), Short Time Fourier Transforms (STFT), Steady State Visual Evoked Potential (SSVEP) and Movement Imagery (MI).