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• W3169041359 abstract "We present a prototype to identify eye states from electroencephalography signals captured from one or two channels. The hardware is based on the integration of low-cost components, while the signal processing algorithms combine discrete wavelet transform and linear discriminant analysis. We consider different parameters: nine different wavelets and two features extraction strategies. A set of experiments performed in real scenarios allows to compare the performance in order to determine a configuration with high accuracy and short response delay." @default.
• W3169041359 created "2021-06-22" @default.
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• W3169041359 date "2021-05-29" @default.
• W3169041359 modified "2023-10-15" @default.
• W3169041359 title "Eye State Identification Based on Discrete Wavelet Transforms" @default.
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• W3169041359 doi "https://doi.org/10.3390/app11115051" @default.
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