On the off chance: quasi static and dynamic models.

[JeanRintoul]

I'm trying to recreate Nir Grossman's recent Cell paper simulation using pyEIT. I've got a nice static model,
with two current sources using pyEIT, but am hoping to recreate the quasi-electrostatic model. This likely could be applicable to MFEIT also.

I realise this isn't strictly needed by pyEIT as the static model is generally considered 'sufficient', but would you have have any recommendations with regards to packages that could do quasi static modelling(ideally that even integrate with pyEIT!). What are your thoughts on incorporating time effects into EIT reconstruction?

[liubenyuan]

This is really an interesting topic. I also read Grossman's paper and it is inspiring.

In MF-EIT, we are not (or could not) model the time effects into EIT, instead, we use the different conductivity profiles under different frequency, and simulate in pyEIT using the static model.

In Grossman et.al, you have to simulate the diff in frequency at two very close frequencies, for example, 20.01 KHz and 20 KHz, it would be much harder if you directly use the conductivity profile of different frequencies. The measurement inaccuracy would overwhelm this simulation process.

I will share the results if we had any progress.

Best!