Abstract
The differentiation of signals in presence of noise results complicated, due to the amplification effect of the traditional methods. In this work we do a preliminary evaluation of the use of the wavelet transform to obtain the first derivative in electrooculographic records generated by means of simulation and strongly contaminated by white and biological noise and interference of 60 Hz of the AC line. The Haar and Gauss1 wavelets produce excellent results when compared with other existing methods, revealing a very promissory field of application of this tool.
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Garcia-Bermudez, R., Rojas, F., Demera, G., Torres, C., Zambrano, D., Joya, G., & Becerra, R. (2017). Evaluation of the differentiation of noisy electrooculographic records using continuous wavelet transform. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10208 LNCS, pp. 557–566). Springer Verlag. https://doi.org/10.1007/978-3-319-56148-6_50
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