Inferring depolarization of cells from 3D-electrode measurements using a bank of linear state space models
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Author (Corporation)
Publication date
2016
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04B - Conference paper
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2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Volume
Issue / Number
Pages / Duration
3331-3335
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IEEE
Place of publication / Event location
Shanghai
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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.
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Event
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Exhibition start date
Exhibition end date
Conference start date
20.03.2016
Conference end date
25.03.2016
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ISBN
978-1-4799-9988-0
978-1-4799-9987-3
978-1-4799-9987-3
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Language
English
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No
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Publication status
Published
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Peer review of the complete publication
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Closed
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Citation
Zalmai, N., Wildhaber, R., Clausen, D., & Loeliger, H.-A. (2016). Inferring depolarization of cells from 3D-electrode measurements using a bank of linear state space models. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 3331–3335. https://doi.org/10.1109/icassp.2016.7472294