ABSTRACT
In this article, we define a new method (Si-GARCH) for signal segmentation based on a class of models coming from econometrics. We make use of these models not to perform prediction but to characterize portions of signals. This enables us to compare these portions in order to determine if there is a change in the signal’s dynamics and to define breaking points with an aim of segmenting it according to its dynamics. We, then, expand these models by defining a new coefficient to improve their accuracy. The Si-GARCH method was tested on several thousands of hours of biomedical signals coming from intensive care units.
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