Hardware efficient denoising system for real EOG signal processing

The traditional signal processing algorithms suffer from large execution delay for real time issues, therefore implementation of high speed algorithms is needed. The present work aims to implement multiplier less Savitzky Golay smoothing filter (SGSF) based on distributed arithmetic (DA) for pre-processing of Electro-oculographic (EOG) signals such that speed is increased along with reduction in chip area. The filter used should be efficient enough to remove the artifacts along with least deformation from the actual signal. Savitzky-Golay (SG) filter is widely employed in biomedical signal analysis but its fast and efficient implementation is not proposed yet for EOG analysis. SGSF is selected so that disease diagnosis using saccade detection of EOG signal can be done accurately. The efficiency of proposed filter is tested in terms of signal-to-signal-plus-noise ratio (SSNR) and real time computations. It is observed from the analysis that DA based architecture increases the processing speed, reduces the chip area and original features of filtered signal are preserved.