[Eeglablist] How to Clean EEG Data with Large Amplitudes After High-Pass Filtering

[Евгений Машеров]

Frequency filtering can be helpful if the artifact is concentrated in a fairly narrow frequency band outside the region of primary interest. However, if the artifact's shape is anything other than sinusoidal, it cannot be completely eliminated, since in addition to the fundamental frequency, there are also harmonics, which typically fall within the band of primary research interest. Frequency filtering is helpful, for example, in removing artifacts associated with electrode polarization or galvanic skin response, at the cost of losing some of the delta range. It is also possible to attempt to eliminate muscle artifacts by losing some of the beta range. This type of filtering aids visual analysis, but is rather detrimental to mathematical processing.
Independent component analysis has already been proposed here, and it can be a lifesaver if the component caused by motion is correctly identified.
However, if there is no signal at all, nothing will help. And in the figure shown, at least one channel (FP1) appears extremely unreliable. The presence of power line interference in one channel often indicates a complete lack of contact with the scalp. Power line interference occurs due to capacitive coupling between the electrical network and the electrode, and since the area of ​​the "capacitor plates" (EEG electrode and power cable) is small and the distance between them is quite large, the capacitance is on the order of tenths of a picofarad or less, while the resistance at 50 or 60 Hz is tens or hundreds of gigaohms. If the electrode and scalp contact are sufficiently good (resistance 10 kiloohms or less), the resulting voltage divider attenuates the power line interference by several million times, and it is not detected. If contact with the scalp is broken, the attenuation is equal to the ratio of the amplifier's input impedance to the resistance of the capacitive coupling to the electrical cables. If interference appears on one of the electrodes, it should be adjusted.
Motion artifacts may be due to a cap that is too loose. Only after correcting all the causes of artifacts appearing during recording does it make sense to use mathematical methods for their elimination, primarily ICA.

Your truly

Eugen Masherov

> Hello,
> I'm working with EEG data collected using a Cyton + Daisy setup. The
> experiment allows participants to move freely throughout the recording, so
> I expected a significant amount of motion-related noise.
> 
> I applied a 1 Hz high-pass filter, but the data still shows a very large
> proportion of high-amplitude values. Overall, about *55% of samples have
> absolute values greater than 100 µV*, which seems too high for usable EEG.
> 
> My question is: *how to clean this dataset*, since standard filtering does
> not seem sufficient?
> 
> 1. Percent of samples with |amplitude| > 100 µV per channel:
> Channel PercentAbs > 100uV
> FP1 92.946
> FP2 31.312
> C3 37.702
> C4 34.826
> P7 77.775
> P8 50.242
> O1 85.518
> O2 52.286
> F7 27.337
> F8 42.444
> F3 43.282
> F4 34.779
> T7 25.874
> T8 27.634
> P3 87.468
> P4 69.978
> 
> 2. Additional channel statistics:
> Channel Min Max Mean Std P5 P95
> FP1 -1.55E+05 3.98E+05 -0.33667 18173 -18654 14161
> FP2 -3312.7 3268.7 -0.056876 243.58 -324.27 353.39
> C3 -2650.7 4902.2 -0.064448 330.28 -465.32 490.06
> C4 -3082.8 3528.5 -0.052471 269.78 -389.84 426.57
> P7 -5018 17516 -0.018368 880.09 -1263.1 1431.4
> P8 -2085.9 9144.2 0.11526 404.97 -523.25 638.35
> O1 -11920 70997 0.43565 1346 -1509 1743.5
> O2 -2705.5 9071.8 -0.014948 293.52 -395.37 447.87
> F7 -2894.7 2943.4 0.024095 193.53 -234.4 255.67
> F8 -2973.9 2639.3 0.054757 225.84 -314.76 324.82
> F3 -4752.6 5627.2 0.08169 517.18 -635.01 672.64
> F4 -6333.3 3600.2 0.07269 515.99 -392.74 630.2
> T7 -2638.4 2738 0.015915 177.67 -229.59 253.66
> T8 -3213.5 3242.7 0.0090257 223.3 -298.77 327.22
> P3 -27780 43690 0.80651 2552.2 -3342.1 3681.6
> P4 -14668 46330 0.17228 1622.3 -1771.8 1753.2
> 3. Channel Data Screenshot:
> https://urldefense.com/v3/__https://drive.google.com/file/d/1FwlMrvYE1e7zn0mQOYnwG7WtYk1Q3SAh/view?usp=sharing__;!!Mih3wA!CrjzKaf8yxIzQ7S7-hNrGlTX3i4E6i-3GXMBj9uYu71UDEIrHRdtyhGKF0ShjK6kP-r-OnCRDllzIN6CQI-UPeoMk6Wj$
> 
> Thank you so much for your guidance!
> 
> Best Regards,
> Jiongjiong
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