Open access
Computational Method for Continuous Monitoring of Ocular Artifacts in Electroencephalography Data
Yuri Silveira Pereira
Daniel Dargelio Ferrão Luft
Matheus Gularte Tavares
Tadeu Vargas
Samuel dos Santos Cardoso
Abstract
This work presents a computational method for detecting ocular artifacts in EEG/EOG signals, focusing on Brain-Computer Interfaces and Assistive Technologies. The system uses an Arduino Nano and AD8232 module for real-time acquisition and processing, implementing an algorithm based on voltage thresholds and signal derivative analysis. In a 10-minute trial, 248 blinks were detected, of which 210 were real and 38 false, with only 6 missed. The method achieved an accuracy of 84.7% and a sensitivity of 97.2%, demonstrating effectiveness in identifying real blinks and potential for EEG pre-processing and Assistive Control applications.