Si-GARCH: Construction and validation of a new method for the detection of breaking points in models |
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| Authors: | Djamel Zitouni Benjamin C. Guinhouya Pierre Ravaux Christian Vilhelm Bruno Sarrazin Mohamed Lemdani |
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| Affiliation: | 1. EA 2694, Santé Publique, Faculté des Sciences Pharmaceutiques et Biologiques de Lille, 3, Lille Cedex, France;2. EA 2694, Santé Publique, UFR Ingénierie et Management de la Santé, France;3. Resuscitation Department, CHU de la Martinique (Martinique University Hospital) Fort-de-France Cedex |
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| 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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| Keywords: | Biomedical GARCH Segmentation Signal Trends |
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