Analyzing source sampling to reduce error in ECG forward simulations

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Abstract

A continuing challenge in validating ECG Imaging is the persistent error in the associated forward problem observed in experimental studies. One possible cause of error is insufficient representation of the cardiac sources, which is often measured from only the ventricular epicardium, ignoring the endocardium and the atria. We hypothesize that measurements that completely cover the heart are required for accurate forward solutions. In this study, we used simulated and measured cardiac potentials to test the effect of different levels of sampling on the forward simulation. We found that omitting source samples on the atria increases the peak RMS error by a mean of 464 μV when compared the the fully sampled cardiac surface. Increasing the sampling on the atria in stages reduced the average error of the forward simulation proportionally to the number of additional samples and revealed some strategies may reduce error with fewer samples, such as adding samples to the AV plane and the atrial roof. Based on these results, we can design a sampling strategy to use in future validation studies.

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APA

Tate, J., Gillette, K., Burton, B., Good, W., Coll-Font, J., Brooks, D., & MacLeod, R. (2017). Analyzing source sampling to reduce error in ECG forward simulations. In Computing in Cardiology (Vol. 44, pp. 1–4). IEEE Computer Society. https://doi.org/10.22489/CinC.2017.371-097

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