XDFT EEG Signal Classification Methods

版本 1.0.0 (57.5 MB) 作者: Putu Fadya

The program is used to describe or classify the electrode response signal from the measurement results using XDFT Methods

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更新时间 2022/3/20

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The program is used to describe or classify the electrode response signal from the measurement results using EEG. The output signal is translated by Fourier Transform to be converted into a signal with a time domain. I use reference calculations to describe each type of wave with a specific frequency in the brain. This is because the human brain produces 5 main types of waves classified according to their frequency: alpha (8–13 Hertz), theta (4–8 Hertz), beta (14–26 Hertz), delta (0.5–4.0 Hertz), gamma (above) waves. 30 Hertz) and mu (8–13 Hertz) (Zulfikri, 2019). The output results are filtered first with DWT or Discrete Wavelet Transform to read the wavelet function of each signal described. Then the DWT function is analyzed by XDFT or Excitonic Density-Functional Theory then from the number of frequencies produced by each output signal it can be read how many frequency bands of each of the 5 types of waves are. The output of the program is in the form of the frequency band of the signal.

引用格式

Putu Fadya (2024). XDFT EEG Signal Classification Methods (https://www.mathworks.com/matlabcentral/fileexchange/108319-xdft-eeg-signal-classification-methods), MATLAB Central File Exchange. 检索来源 2024/8/25.