The Use of Counting Peaks Method for the Purpose of Smoothing Filtering Efficiency Assessment in Analysis of Electroencephalography Data

In this paper an innovative counting peaks method applied for the purpose of efficiency assessment of smoothing filtering applied on electroencephalography data was presented. The proposed method gave promising results and can be treated as an introductory method for intelligent machine-based reasoning. The analysed data were obtained from the open source data-base and recorded with the OpenBCI EEG headset. The comparison focused on Moving Average and Savitzky-Golay (SG) filter. The best results were obtained with the use of the Moving Average filtering.