Lauren Fovargue

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Modelling cardiac electrophysiology (EP) can help understand pathologies and predict the response to therapies. Moreover, estimating patient-specific parameters of the EP model is crucial to obtain personalised information. The novelty of this paper is to use non-invasive data (body surface potential mapping, BSPM) in order to personalise the main(More)
Modelling the cardiac electrophysiology (EP) can help understand pathologies and predict the response to therapies such as cardiac resynchronization. To this end, estimating patient-specific model parameters is crucial. In the case of patients with bundle branch blocks (BBB), part of the Purkinje system is often affected. The aim of this work is to estimate(More)
In the scope of modelling cardiac electrophysiology (EP) for understanding pathologies and predicting the response to therapies, patient-specific model parameters need to be estimated. Although personalisation from non-invasive data (body surface potential mapping, BSPM) has been investigated on simple cases mostly with a single pacing site, there is a need(More)
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