Wavelet Design for Automatic Real-Time Eye Blink Detection and Recognition in EEG Signals

Michael Gabriel Miranda, Renato Alberto Salinas, Ulrich Raff, Oscar Magna

Abstract


The blinking of an eye can be detected in electroencephalographic (EEG) recordings and can be understood as a useful control signal in some information processing tasks. The detection of a specific pattern associated with the blinking of an eye in real time using EEG signals of a single channel has been analyzed. This study considers both theoretical and practical principles enabling the design and implementation of a system capable of precise real-time detection of eye blinks within the EEG signal. This signal or pattern is subject to considerable scale changes and multiple incidences. In our proposed approach, a new wavelet was designed to improve the detection and localization of the eye blinking signal. The detection of multiple occurrences of the blinking perturbation in the recordings performed in real-time operation is achieved with a window giving a time-limited projection of an ongoing analysis of the sampled EEG signal.

Keywords


Biological signals, electroencephalogram, brain computer interface, eye blink detection, pattern recognition, wavelet design

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References


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DOI: https://doi.org/10.15837/ijccc.2019.3.3516



Copyright (c) 2019 Michael Gabriel Miranda, Renato Alberto Salinas, Ulrich Raff, Oscar Magna

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