How do I know if my EEG signal need denoising? I recently started  working on sleep study.

For my research I download sleep EEG data from physionet. The EEG data has 100 Hz sampling rate and was recorded from 2 bipolar EEG site.

When I start the preprocessing stage, I encounter a simple problem:

How would I know if my signal has an artifact or noise?

It should be noted, based on Nyquist theorem and my signal's sampling rate, the maximum frequency of my signal is 50 Hz, so I did not filter unnecessary EEG frequency.

In general I only used a simple notch filter at 50 Hz, and used simple threshold method in order to remove the epochs that were grossly contaminated by muscle and/or eye movement artifacts.

Back to the main question, how should I know if I need to uses more complicated method for removing EMG or EOG artifact from my signal?
It primarily relies on,


what are you looking for in the EEG: define the frequency band that
relates with the phenomena you are interested to investigate and
filter out the rest (e.g. for sleep events bandpass ~= 0.8-30Hz).
power line of your area: notch filter at 50Hz or 60Hz.
Study design: if you are investigating events ensemble averages will remove random noise processes and highlight potential EEG events of interest.


Moreover, you can apply baseline removal to de-noise your signal from saturation trends and other systemical artefacts. Other experimental methods include ICA, which you will not be able to apply robustly since you only have two channels.