|Title:|| Statistical Assessment and Calibration of Numerical ECG Models|
|Date:|| Friday 30th September 2016|
|Author(s) :|| Tarabelloni, N.; Schenone, E.; Collin, A.; Ieva, F.; Paganoni, A.m.; Gerbeau, J.-f.|
|Abstract:|| Objective: Because of the inter-subject variability of ECGs in a healthy
population, it is not straightforward to assess the quality of synthetic ECGs
produced by deterministic mathematical models. We propose a statistical method
to address this question.
Methods: We use a dataset of 1588 healthy, real ECGs and we introduce a way to
calibrate the deterministic model so that its output fits the dataset. Our
approach is based on the concepts of spatial quantiles and spatial depths. These
notions are convenient to manipulate functional data since they provide a
non-parametric way to measure the discrepancy of the model output with a
distribution of data.
Results: The method is successfully applied to two very different models: a
phenomenological model based on ordinary differential equations, and a complex
biophysical model based on partial differential equations set on a
three-dimensional geometry of the heart and the torso. We show in particular
that the proposed calibration strategy allows us to improve the quality of the
ECG obtained with the biophysical model.
Significance: The proposed methodology is to our knowledge the first attempt to
assess the quality of synthetic ECGs with quantitative statistical arguments.
More generally it can be applied to other situations where a deterministic model
produces a functional output that has to be compared with a population of
measurements containing inter-subject variability.|