Inferring depolarization of cells from 3D-electrode measurements using a bank of linear state space models

Zalmai, Nour; Wildhaber, Reto; Clausen, Desiree; Loeliger, Hans-Andrea (March 2016). Inferring depolarization of cells from 3D-electrode measurements using a bank of linear state space models In: The 41st IEEE International Conference on Acoustics, Speech and Signal Processing. Shanghai. 20.03.2016 - 25.03.2016. 10.1109/ICASSP.2016.7472294

Full text not available from this repository. (Request a copy)

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

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

School of Engineering and Computer Science > Institute for Human Centered Engineering (HUCE)
School of Engineering and Computer Science
BFH Centres > BFH centre for Health technologies

Name:

Zalmai, Nour;
Wildhaber, Reto;
Clausen, Desiree and
Loeliger, Hans-Andrea

Language:

English

Submitter:

Admin import user

Date Deposited:

20 Nov 2019 09:35

Last Modified:

24 Nov 2019 01:31

Publisher DOI:

10.1109/ICASSP.2016.7472294

URI:

https://arbor.bfh.ch/id/eprint/7627

Actions (login required)

View Item View Item
Provide Feedback