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p-leader Multifractal Analysis and Sparse SVM for Intrapartum Fetal Acidosis Detection

Abstract : Interpretation and analysis of intrapartum fetal heart rate, enabling early detection of fetal acidosis, remains a challenging signal processing task. Among the many strategies that were used to tackle this problem, scale-invariance and multifractal analysis stand out. Recently, a new and promising variant of multifractal analysis, based on p-leaders, has been proposed. In this contribution, we use sparse support vector machines applied to p-leader multifractal features with a double aim: Assessment of the features actually contributing to classification; Assessment of the contribution of non linear features (as opposed to linear ones) to classification performance. We observe and interpret that the classification rate improves when small values of the tunable parameter p are used.
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Submitted on : Friday, April 21, 2017 - 5:05:37 PM
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  • HAL Id : hal-01511878, version 1
  • OATAO : 17043


Roberto Leonarduzzi, Jiri Spilka, Jordan Frecon, Herwig Wendt, Nelly Pustelnik, et al.. p-leader Multifractal Analysis and Sparse SVM for Intrapartum Fetal Acidosis Detection. 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2015), Aug 2015, Milano, Italy. pp. 1-4. ⟨hal-01511878⟩



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