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All about EEG artifacts and filtering tools

bitbrain.com · 4,314 words · saved by 1 readers

One of the main concerns when dealing with electroencephalographic signals (EEG) is assuring that we record clean data with a high signal to noise ratio. The EEG signal amplitude is in the microvolts range and it is easily contaminated with noise, known as “artifacts”, which need to be filtered from the neural processes to keep the valuable information we need for our applications. We review in this post different EEG artifacts and the main tools and techniques to remove them.

Go back to blog Neurotechnology All about EEG artifacts and filtering tools 14 Min. Technical By the Bitbrain team November 25, 2025 One of the main challenges in working with electroencephalographic (EEG) data is ensuring that the recorded signals are clean and exhibit a high signal-to-noise ratio (SNR). Because EEG amplitudes are typically in the microvolt range, they are highly susceptible to various sources of contamination, commonly referred to as artifacts. These unwanted signals can obscure the underlying neural activity and compromise the quality of the data, making artifact detection

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