In general, the preprocessing methods used in EEG are very dependent on the goal of the applications. Having said that, there are some methods that are used very commonly to improve the quality of Signal to Noise ratio, such as Common Average Referencing (CAR) or filtering. It would be interesting to summarize the effective signal preprocessing methods since they usually can be similar in different applications. What are the methods that you have found effective on your data?

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