Abstract

Gastric contractions are governed by a bioelectrical event known as slow waves. High-resolution electrical mapping has recently been applied to study complex gastric slow wave spatiotemporal propagations in detail. As these methods are translated to clinical and experimental applications, it is evident that efficient and automated methods are a necessity for analysis. Despite automated methods to detect slow wave events, manual review and correction remains necessary due to the presence of experimental noise in the recordings. Manual deletion of invalid slow wave events is time consuming and inefficient. We have therefore developed an algorithm to eliminate invalid markers of slow waves, via the use of frequency and morphological analysis. The techniques were validated with experimental data using serosal gastric slow wave recordings from animals and humans with a sensitivity of 90% and specificity of 85%. It is anticipated these methods will facilitate analyzing high-resolution slow wave mapping data and accelerate clinical translation of electrical mapping to clinical and diagnostic gastroentrology.

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