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Variable Embedding Based on L–statistic for Electrocardiographic Signal Analysis

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Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications (IWINAC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13258))

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Abstract

In this paper, a variable embedding approach for reconstructing attractors of dynamical systems is proposed, using the L–statistic based on noise amplification. Particularly, the variable manifold is obtained from a time-series using delay coordinates and an embedding vector, the last one, is constructed based on a L–statistic matrix which contains the local reconstruction quality of whole attractor. The embedding vector contains the optimal embedding dimension for each point in the manifold. This approach were performed on electrocardiography databases, we obtain the first four statistical moments for the embedding dimension vectors and apply statistical tests to distinguish between normal and pathological signals. Results shown significant differences that lead to new classification strategies, infer about functional states, and establish a new path for processing signals with high embedding dimensions, i.e., high computer complexity.

This work is presented in partial fulfillment of the requirements for the “Call for the strengthening of vocations and training in ST&I for economic reactivation in the framework of the 2020 post-pandemic” No. 891 of MinCiencias- Colombia.

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Author information

Authors and Affiliations

  1. AMYSOD Lab –Parque i, CM&P Research Group, Instituto Tecnológico Metropolitano ITM, 050034, Medellín, Colombia

    Lucas Escobar-Correa & Edilson Delgado-Trejos

  2. Department of Exact and Applied Sciences, GI2B Research Group, Instituto Tecnológico Metropolitano ITM, 050034, Medellín, Colombia

    Juan Murillo-Escobar

  3. Technological Institute of Informatics, Universitat Politecnica de Valencia, Alcoi Campus, 03801, Alcoi, Spain

    David Cuesta-Frau

Authors
  1. Lucas Escobar-Correa
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  2. Juan Murillo-Escobar
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  3. Edilson Delgado-Trejos
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  4. David Cuesta-Frau
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Corresponding author

Correspondence to Lucas Escobar-Correa .

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Editors and Affiliations

  1. Universidad Politécnica de Cartagena, Cartagena, Spain

    José Manuel Ferrández Vicente

  2. Universidad Nacional de Educación a Distancia, Madrid, Spain

    José Ramón Álvarez-Sánchez

  3. Universidad Nacional de Educación a Distancia, Madrid, Spain

    Félix de la Paz López

  4. Ohio State University, Columbus, OH, USA

    Hojjat Adeli

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Escobar-Correa, L., Murillo-Escobar, J., Delgado-Trejos, E., Cuesta-Frau, D. (2022). Variable Embedding Based on L–statistic for Electrocardiographic Signal Analysis. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications. IWINAC 2022. Lecture Notes in Computer Science, vol 13258. Springer, Cham. https://doi.org/10.1007/978-3-031-06242-1_59

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  • DOI: https://doi.org/10.1007/978-3-031-06242-1_59

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  • Online ISBN: 978-3-031-06242-1

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