Spatio-temporal linear expansions for repolarization analysis

In this work we propose a multichannel signal model based on linear expansions to analyze the cardiac repolarization. Our hypothesis is that a joint spatio-temporal signal description which takes into account both temporal and spatial features provide a more compact signal representation, i.e. the signal energy is packed into a smaller number of coefficients. In this work we also deal with the problem of estimating optimal basis functions in two different situations: when no information of the noise source is available and when the noise statistics is known or estimated from especific signals or intervals, like the TP segment.