(2011-12-23) Monte, Gustavo; Scarone, Norberto; Liscovsky, Pablo
This paper presents an application of a novel algorithm for real time detection of
ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling
process of an oversampled signal. After this treatment, analyzing sequence of segments, global
signal behaviours are obtained in the same way like a human being does. The entire process
can be seen as a morphological filtering after a smart data sampling. The algorithm does not
require any ECG digital signal pre-processing, and the computational cost is low, so it can be
embedded into the sensors for wearable and permanent applications. The proposed algorithms
could be the input signal description to expert systems or to artificial intelligence software in
order to detect other pathologies
