EEGsig machine learning-based toolbox for End-to-End EEG signal processing

In the quest to realize comprehensive EEG signal processing toolbox, in this paper, we demonstrate the first toolbox contain three states of EEG signal processing (preprocessing, feature extraction, classification) together. Our goal is to provide a comprehensive toolbox for EEG signal processing. Using MATLAB software, we have developed an open-source toolbox for end-to-end processing of the EEG signal. As we know, in many research work in the field of neuroscience and EEG signal processing, we first clear the signal and remove noise, artifact, etc. Which we know as preprocessing, and then extract the feature from the relevant signal, and finally Machine learning classifiers used to classification of signal. We have tried to provide all the above steps in the form of EEGsig as a graphical user interface(GUI) so that there is no need for programming for all the above steps and reduce the time to complete these projects to a desirable level.