Citas bibligráficas
Rodriguez, J., (2020). Diseño y simulación de un filtro digital para Señales EEG con el paradigma de Imaginación Motora en FPGA [Universidad Tecnológica del Perú]. https://hdl.handle.net/20.500.12867/3795
Rodriguez, J., Diseño y simulación de un filtro digital para Señales EEG con el paradigma de Imaginación Motora en FPGA []. PE: Universidad Tecnológica del Perú; 2020. https://hdl.handle.net/20.500.12867/3795
@misc{renati/804424,
title = "Diseño y simulación de un filtro digital para Señales EEG con el paradigma de Imaginación Motora en FPGA",
author = "Rodriguez Yarahuaman, José Carlos",
publisher = "Universidad Tecnológica del Perú",
year = "2020"
}
Nowadays, the digital filters have different applications in different branches of engineering such as Biomedical, Electronics, Telecommunications. In various research centers related to Electroencephalographic (EGG) signals, they present certain limitations in the preprocessing stage of the electroencephalographic signals due to the high cost of equipment that allows the pre-processing, acquisition and visualization of the filtered EEG signal to be carried out. . The objective of this work is to design and simulate a hardware digital filter for EEG signals of the motor imagination paradigm in an embedded FPGA system (Field Programmable Gate Array), whose purpose is to develop the pre-processing stage of the EEG signal of the motor imagination paradigm. Using the hardware and software resources of the FPGA allows a wide flexibility in being able to design a digital filter. The Matlab simulation tools, Modelsim, allow a practical solution for the visualization of the filtered EEG signal. The use of the FIR filter based on the Hamming and Blackman window method is chosen. Additionally, we worked with a 60-channel EEG database which uses channels C3 and C4 in order to work with the EEG waves of motor imagination Beta and Mu. The design of the digital filter in software uses the language of VHDL programming, also in the results obtained a comparison of the digital FIR filter is made using the Hamming and Blackman window method, which through tests carried out in software shows that the Blackman window method presents a better response of the Electroencephalographic signal for the pre-processing stage, providing a software tool that will allow users to carry out different complementary studies to the pre-processing area of EEG signals.
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