The work carried out in this paper consists of the classification of the physiological signal generated by eye movement called Electrooculography (EOG). The human eye performs simultaneous movements, when focusing on an object, generating a potential change in origin between the retinal epithelium and the cornea and modeling the eyeball as a dipole with a positive and negative hemisphere. Supervised learning algorithms were implemented to classify five eye movements; left, right, down, up and blink.
View Article and Find Full Text PDFIndustry 4.0 involves various areas of engineering such as advanced robotics, Internet of Things, simulation, and augmented reality, which are focused on the development of smart factories. The present work presents the design and application of the methodology for the development of augmented reality applications (MeDARA) using a concrete, pictorial, and abstract approach with the intention of promoting the knowledge, skills, and attitudes of the students within the conceptual framework of educational mechatronics (EMCF).
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