I am required to filter out noise from EEG data using preferably Python or MATLAB. My dataset contains values for 64-electrode EEG along with their time-corresponding HEOG (horizontal eye movement), VEOG (vertical eye movement) and ECG (for heart-complex artefacts) values. I wish to implement cascading adaptive filtering technique and have gone through the paper 'Noise Removal from EEG Signals in Polisomnographic Records Applying Adaptive Filters in Cascade' by M. Agustina Garces Correa and Eric Laciar Leber (Chapter Noise Removal from EEG Signals in Polisomnographic Records A...
) but I am not proficient enough with programming to allow me to program the logic.Could anybody tell me what libraries and functions would be appropriate for this?
Matlab is best. Have a look at :https://www.mathworks.com/help/hdlcoder/examples/lms-filter-noise-cancellation.html
https://www.mathworks.com/help/dsp/adaptive-filters.html
https://www.mathworks.com/help/dsp/ug/overview-of-adaptive-filters-and-applications.html
Hello Saprativ Ray
For implementation of Adaptive filter in python follow this:
https://pypi.org/project/adaptfilt/
Regards
The Neurophysiological biomarker toolbox can be opened in MATLAB as a package. It has it's own GUI and can do the filtering as well as other analysis.
https://www.nbtwiki.net/
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