Clasificación de señales de Electroencefalografía (EEG) con redes neuronales en FPGA

#EEG #signal #processing #Artificial #Neural #Networks #Clustering #FPGA.
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This webinar presents some theoretical and technical solutions to the problem of EEG signal processing, by using artificial neural networks and FPGA. Some topics will be discussed, such as the clustering of the EEG occipital signals using K-means, EEG Signal Clustering for Motor and Imaginary Motor Tasks on Hands and Feet, and Implementation of a Classification System of EEG Signals Based on FPGA. Additionally, other projects using FPGA will be presented.


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  • Date: 18 Jun 2020
  • Time: 11:00 AM to 01:00 PM
  • All times are (GMT-05:00) America/Guayaquil
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  • ONLINE
  • Cuenca, Azuay
  • Ecuador
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  Speakers

Victor Asanza

Topic:

Clasificación de señales de Electroencefalografía (EEG) con redes neuronales en FPGA

This webinar presents some theoretical and technical solutions to the problem of EEG signal processing, by using artificial neural networks and FPGA. Some topics will be discussed, such as the clustering of the EEG occipital signals using K-means, EEG Signal Clustering for Motor and Imaginary Motor Tasks on Hands and Feet, and Implementation of a Classification System of EEG Signals Based on FPGA. Additionally, other projects using FPGA will be presented.

Biography:

Victor Asanza (EL Oro - Ecuador, 1986). He was graduated as Electronic and Telecommunications Engineering on 2009 (ESPOL, Ecuador). He has worked as Professor of  Electronic's Department since 2012 at Escuela Superior Politécnica del Litoral. He has been researching in fields like, FPGA-based Digital Systems Design, Embedded Systems, Hardware Design and Biomedical Signal Processing with a major research interest in Artificial Intelligence and Brain-Computer Interface. He was graduated as master in Automation and Industrial Control on 2012 (ESPOL, Ecuador). Currently, He is Ph.D. Candidate at Escuela Superior Politécnica del Litoral in Applied Computer Science.