nrv.eit

Description

Electrical Impedance Tomography - eit: models for neural impedance imaging

eit provides high level models for imaging techniques based on electrical impedance sensing for neural activity reconstruction. Tissue properties are computed taking into account the temporal and frequencial evolution of neural membranes conductivity. Models are based on both Finite Differences (NEURON) computations and FEM models.

Warning

The eit sb-package is currently under construction and scientific validation. The code can change fast, results not guaranteed, and developpers do not ensure backwards compatibility.

Classes

eit_forward()	Class allowing to simulate Electircal Impedance Tomography in a nerve
eit_inverse()	Class allowing image reconstruction from eit_forward results.
protocol([p])	Caution not fully implemented.
pyeit_protocol([n_elec, inj_offset, start_elec])

Functions

crop_fascicle(fasc, x0, new_l)	_summary_
crop_nerve(nerv, x0, new_l)	_summary_