Electrooculography Signals Classification for FPGA-based Human-Computer Interaction-Reference-Cited by-同舟云学术

Electrooculography Signals Classification for FPGA-based Human-Computer Interaction

Published:2022-11-16 Issue: Volume: Page:
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Container-title:2022 IEEE ANDESCON
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Author:

Asanza Victor¹,Miranda Jesus¹,Miranda Jocelyn²,Rivas Leiber²,Hernan Peluffo-Ordonez Diego³,Pelaez Enrique¹,Loayza Francis⁴,Alejandro Otilia¹

Affiliation:

1. Escuela Superior Politécnica del Litoral - ESPOL,Electrical and Computer Science Engineering Depart.,Guayaquil,Ecuador

2. Escuela Superior Politécnica del Litoral - ESPOL,Mechanical and Production Science Engineering Depart.,Guayaquil,Ecuador

3. Mohammed VI Polytechnic University,MSDA Research Program,Ben Guerir,Morocco,47963

4. Escuela Superior Politécnica del Litoral - ESPOL,Mechanical an Production Science Eng. Depart.,Guayaquil,Ecuador

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9989530/9989521/09989664.pdf?arnumber=9989664

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2. Behavioral signal processing with machine learning based on fpga;asanza;Int Conf Information Sciences and Systems,2020

3. Laboratory biosafety guidance related to coronavirus disease 2019 (covid-19): interim guidance;Technical Report World Health Organization,2020

4. CaracterizaciÓn de seÑales lectromiogrÁficas para la discriminaciÓn de seis movimientos de la mano;pinzon morales;Revista Scientia et Technica,2009

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