Design and Implementation of a Novel Complete Filter for EEG Application on FPGA

Filter is vastly used to detect different human signal in real time. In this paper, a novel complete digital filter is proposed for the fast detection of EEG signals due to avoid the mixtures of different biomedical signals. This paper intends to design a digital complete filter based on Field Programmable Gate Array (FPGA) for the alleviation of unwanted frequency components in biomedical signals specially EEG signals. For this purpose, complete filter which is a combination of integrator filter and differentiator filter which supports both low and high noises and comparatively inexpensive than other signal processing methodologies can be used. For hardware implementation, FPGA board is used which is a combination of different logic gates which offers inexpensive and long lasting services.

[1]  Anantha Chandrakasan,et al.  An energy-efficient biomedical signal processing platform , 2010, 2010 Proceedings of ESSCIRC.

[2]  Vladimir Vujicic.  Generalized low-frequency stochastic true RMS instrument , 2001, IEEE Trans. Instrum. Meas..

[3]  Frank Vahid.  Digital Design with RTL Design, Verilog and VHDL , 2010 .

[4]  Po-Lei Lee,et al.  Development of a Low-Cost FPGA-Based SSVEP BCI Multimedia Control System , 2010, IEEE Transactions on Biomedical Circuits and Systems.

[5]  Shumit Saha,et al.  FPGA implementation of modified type-C PID control system , 2015, 2015 International Conference on Electrical Engineering and Information Communication Technology (ICEEICT).

[6]  Naveen Verma,et al.  A Micro-Power EEG Acquisition SoC With Integrated Feature Extraction Processor for a Chronic Seizure Detection System , 2010, IEEE Journal of Solid-State Circuits.

[7]  V. Pjevalica,et al.  Further Generalization of the Low-Frequency True-RMS instrument , 2005, IMTC 2005.

[8]  Joseph B. Evans,et al.  FPGA IMPLEMENTATION OF DIGITAL FILTERS , 1997 .

[9]  Joseph B. Evans.  Efficient FIR filter architectures suitable for FPGA implementation , 1994 .

[10]  Vladimir V. Vuji.  Low-Frequency Stochastic True RMS Instrument , 1999 .

[11]  Pradeepa,et al.  FPGA based filters for EEG pre-processing , 2016, 2016 Second International Conference on Science Technology Engineering and Management (ICONSTEM).