My current lab relies on a KIT system with 157 axial gradiometers. This machine does not allow continuous HPI monitoring. The best I could do would be to assess markers’ position at the end of each block (i.e. every ~8 min for a paradigm that lasts 1h15). In case I did that, how could I use this information to compensate for movements?
[The only hint I have is to use maxwell_filter but I read that it does not work well with axial and not-to-numerous gradiometers and I am not understanding how to use this function for movement compensation only…]
You could process each run separately with maxwell_filter. If you use the same fixed destination=... in each, they should all be transformed to the same destination location. For example you could use destination=(0., 0., 0.04) or so and it might work.
If you do this, I recommend you look at your data before and after to verify that the SNR hasn’t been adversely affected, and that the resulting head-sensor alignment is reasonable (using plot_alignment).