[Eeglablist] Persistent 20 Hz Harmonic Line Noise in EEG Data

[Евгений Машеров]

If you're referring to this spectrum,
https://urldefense.com/v3/__https://ibb.co/5WbNqYCW__;!!Mih3wA!EE1CnKXe_iZ-NjaTa6XgziCX4F1gQ8SRKeq9-pNjv6zxgRhPoSQKQBtzuyfOH9cfimSNL5R9CisUYB2yD_xhBitUe1w$ 
I see a peak at 20 Hz (around 30 dB), 40 Hz (around 40 dB), and 60 Hz (around 30 dB). Possible sources include MRI (pulse frequency) or physiotherapy equipment. It could also be some industrial equipment. In one case, the interference was from a nearby airport's radar.

> The plots here clearly show the noise is at 25 Hz and its harmonics ...
> 
> On Sat, May 9, 2026 at 11:08 AM Евгений Машеров via eeglablist <eeglablist at sccn.ucsd.edu> wrote:
> 
>> This isn't power line interference. It would be 50 or 60 Hz, and possibly harmonics at multiples of 100-150-200... or 120-180-240-... frequencies. Subharmonics wouldn't appear. It's undoubtedly a technical artifact, although I'm unsure of the source. Railways sometimes use other frequencies (16 2/3 Hz, others—20, 25, 45, and others no longer in use)—but not 20 Hz. A television screen will show 50 (PAL/SECAM) or 60 (NTSC) Hz, computer monitors even higher, and it could be some obsolete or specialized video equipment (with a lower frame rate). I'd assume the source in your case is medical equipment (although I can't rule out, for example, a security alarm).
>>
>> The best course of action is to find the source of the interference and turn it off. However, this isn't always possible, especially with medical equipment. A similar situation occurred with an infusion pump in the intensive care unit: the intermittently activated drive solenoid created regular pulsed interference. A possible solution, also used to combat a physiological artifact—an electrocardiographic signal interfering with the EEG—is to evaluate the shape of the interference (the presence of harmonics indicates that the shape is clearly not sinusoidal) and subtract it from the signal. To do this, narrowband filtering isolates the fundamental 20 Hz harmonic, its peaks (or zero crossings) are used as a trigger for averaging, the averaged response is calculated for each channel, and then subtracted from the signals for the individual channels. Naturally, this is a post-processing method and is not suitable for online processing.
>>
>> Your truly
>>
>> Eugen Masherov
>>
>>> Dear EEGLAB List,
>>
>>>
>>
>>> I am currently dealing with persistent line-noise contamination in my EEG
>>
>>> recordings, specifically strong peaks around 20 Hz and its harmonics (40
>>
>>> Hz, 60 Hz, etc.). The contamination remains substantial even after multiple
>>
>>> preprocessing attempts.
>>
>>>
>>
>>> Raw Data PSD for reference: https://urldefense.com/v3/__https://ibb.co/5WbNqYCW__;!!Mih3wA!EfdhaFV_tpprT4Wc8_HcfK7KDVTXA0O0NPLW3Ws732nxP-TmPxHUXI_qXevcPIO8hfndJk8euI6BWbB1_dCuBxHG_A$
>>
>>>
>>
>>> I have already tried:
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>>>
>>
>>> -
>>
>>>
>>
>>> Average re-referencing before notch filtering
>>
>>> -
>>
>>>
>>
>>> Average re-referencing after notch filtering
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>>> -
>>
>>>
>>
>>> Multiple full-rank average reference implementations, including:
>>
>>> -
>>
>>>
>>
>>> Makoto’s fullRankAveRef()
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>>> -
>>
>>>
>>
>>> Manual full-rank average reference using (nchan + 1) denominator
>>
>>>
>>
>>> Despite this, a large amount of the harmonic noise is still present in the
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>>> spectra.
>>
>>>
>>
>>> For reference, the issue looks somewhat similar to this discussion:
>>
>>> https://urldefense.com/v3/__https://mne.discourse.group/t/line-noise-eeg/11817__;!!Mih3wA!EfdhaFV_tpprT4Wc8_HcfK7KDVTXA0O0NPLW3Ws732nxP-TmPxHUXI_qXevcPIO8hfndJk8euI6BWbB1_dB2ZPVDPg$
>>
>>>
>>
>>> I would greatly appreciate advice on how people in the EEGLAB community
>>
>>> typically handle this kind of persistent harmonic contamination.
>>
>>>
>>
>>> Would you recommend CleanLine, Zapline-plus, spectrum interpolation, ASR,
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>>> ICA-based approaches, or something else?
>>
>>>
>>
>>> Thank you very much for your help.
>>
>>>
>>
>>> Best regards,
>>
>>> Maeghal Jain
>>
>>> BISE Lab
>>
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>>
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>>
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>>
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> 
> --
> Scott Makeig, Research Scientist and Director, Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott