Design and Implementation of Pre-processing Chip for Brain Computer Interface Machine

Many researchers have work on the preprocessing of biomedical signal. Main objectives of these algorithms are to minimize noise and artifacts existing with these signals, so that it will be easy to analyze and diagnosis human diseases. This paper is presented a proposed digital filter design using sampling rate conversion (SRC) system for biomedical signal processing with Field Programmable Gate Array (FPGA). This proposed digital filter has advantages on simple structure, stationary response and adaptively with embedded microprocessors. Another important advantage to FPGA to digital filter implementation include higher sampling rate as compared to traditional DSP chips. The proposed system is tested on computer programmable on Xilinx ISE Suite 14.7 or Quartus II software with interface ALTRA Cyclone DE II board of FPGA device. FPGA technique is flexible and provide better performance as compared to traditional techniques. To testify this chip, we use Brian computer Interface (BCI) machine data like Electroencephalography (EEG).