Digitalización de imágenes de ECG para la detección del síndrome de Bayés

Abstract

Bayes Syndrome is a recently recognized by medical community sickness. This desease has been studied in the last decades by its discoverer, MD. Antonio Bayés de Luna. Since several works shows that this desease is related to multiple symptoms, an early detection is considered relevant. Given that digital support of the EKG signal is mandatory for its analysis by a computer algorithm and considering that even with the technological advances, a big number of health institutions rely on paper or image digitalized support por EKGs. Hence, an image digitalization method that preserves the signal features that are relevant to diagnose the Bayes Syndrome is needed. In this paper, some alternatives of digitalization are analyzed for a representative dataset. Results are promising and shows that developed digitalization algorithm could be used for the further project stages that involves signal processing and classification.