Denoising small signals using averaging methods in Arduino

Abstract

Electroencephalograms (EEG) acquired from the scalp is a small amplitude and low-frequency signal, with noise accumulation which originates from spontaneous activity of the human brain. Averaging methods are frequently used in reducing noise in EEG signals during the post-processing stage and never in real time. The methods are frequently engaged in waveform measurements in order to reduce the additive noise and at the same time, retaining significant parts of the noisy instances. This paper describes averaging methods used in real-time. The processes are emulated using MATLAB and then implemented in Arduino. The correlation and the SNR between the input signal and output of the averaging methods were calculated and compared.