Inferring depolarization of cells from 3D-electrode measurements using a bank of linear state space models
Nour Zalmai, Reto A. Wildhaber, Desiree Clausen, Hans-Andrea Loeliger
Abstract
Cell depolarization runs essentially in a uniform motion along the muscular tissue, which creates transient electrical potential differences measurable by nearby electrodes. Inferring the depolarization speed and direction from measurements is of great interest for physicians. In cardiology, this is part of the inverse ECG problem which often requires a large number of electrodes and intense computational power even if the simple common model of the single equivalent moving dipole (SEMD) is applied. In this paper, we model a depolarization process as a straight-line movement of a SEMD. We provide an efficient algorithm based on linear state space models that infers the SEMD movement using only 3 measurement channels from a tetrahedral electrode and with the presence of interferences. Our algorithm is tested both on simulated and experimental data.
BibTeX
@inproceedings{icassp2016_inferringdepolar,
title = {Inferring depolarization of cells from 3D-electrode measurements using a bank of linear state space models},
author = {Nour Zalmai and Reto A. Wildhaber and Desiree Clausen and Hans-Andrea Loeliger},
booktitle = {ICASSP 2016},
year = {2016}
}