Finite Impulse Response Filter for Electroencephalogram Waves Detection

Melinda Melinda; Syahrial; Yunidar; Al Bahri; Muhammad Irhamsyah

doi:10.53623/gisa.v2i1.65

Electroencephalographic data signals consist of electrical signal activity with several characteristics, such as non-periodic patterns and small voltage amplitudes that can mix with noise making it difficult to recognize. This study uses several types of EEG wave signals, namely Delta, Alpha, Beta, and Gamma. The method we use in this study is the application of an impulse response filter to replace the noise obtained before and after the FIR filter is applied. In addition, we also analyzed the quality of several types of electroencephalographic signal waves by looking at the addition of the signal to noise ratio value. In the end, the results we get after applying the filter, the noise that occurs in some types of waves shows better results.

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GISA 2(1), 7-19

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About this article

SUBMITTED: 23 February 2022
ACCEPTED: 02 April 2022
PUBLISHED: 7 April 2022
SUBMITTED to ACCEPTED: 38 days
DOI: https://doi.org/10.53623/gisa.v2i1.65

Cite this article

Melinda, M., Syahrial, Yunidar, Al Bahri, & Irhamsyah, M. (2022). Finite Impulse Response Filter for Electroencephalogram Waves Detection. Green Intelligent Systems and Applications, 2(1), 7–19. https://doi.org/10.53623/gisa.v2i1.65

Keywords

amplitude, EEG signal, filter Finite Impulse Respon

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