Finding the correct scale

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1

If you have a question or issue with MNE-Python, please include the following info:

  • MNE-Python version: 0.23
  • operating system: Windows 10

Greetings everyone,

My dataset contains 20 EEG channels which I rescaled from µV to V (1e-6). It also contains data of another 3 channels (ECG, R, GSR) which was collected using the NeXus-10 system.

The ECG sensor had a resolution/bit of .012215 µV and a range of -100mV to +100mV.
The R sensor had a resolution/bit of .2384186 µV and a range of -2.0V to +2.0V.
The GSR sensor had a resolution/bit of .2384186 µV and a range of -2.0V to +2.0V.

could you advise me on how to rescale them properly?

Another question:

How could I create a raw object that contains EEG data collected at a sample rate of 256 Hz and ECG, R, and GSR data collected at a sample rate of 128 Hz (i.e., What the sfreq will be in the raw object)

Below is what the plot of my raw object looks like:

raw data
raw data1868Ă—1137 206 KB

2

My understanding is that there can only be a single sampling frequency for a Raw object. You can first create separate Raws and then resample to have the same sampling frequency. Then, you can create a new Raw object that contains the resampled data of all individual Raws.

3

Thank you @richard,

I only converted the EEG and ECG data from µV to V by multiplying the data with (1e-6) and left R and GSR unconverted because I believe the unit is AU. Is this the correct way or do I have to rescale them when you look at the figure?

4

Hello, the respiratory signal seems to be within a reasonable range. I’m not sure about the GSR signal though – the default scaling that MNE assumes doesn’t seem to match your data very well, according to the above figure?

btw if it’s just a matter of visualization, you can also pass a scalings parameter to Raw.plot() to supply custom scalings!

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