Eye State Identification Based on Discrete Wavelet Transforms

Featured Application Authors are encouraged to provide a concise description of the specific application or a potential application of the work. This section is not mandatory. 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.