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A Novel Method for Screening Children with Isolated Bicuspid Aortic Valve

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Abstract

This paper presents a novel processing method for heart sound signal: the statistical time growing neural network (STGNN). The STGNN performs a robust classification by merging supervised and unsupervised statistical methods to overcome non-stationary behavior of the signal. By combining available preprocessing and segmentation techniques and the STGNN classifier, we build an automatic tool for screening children with isolated BAV, the congenital heart malformation which can lead to serious cardiovascular lesions. Children with BAV (22 individuals) and healthy condition (28 individuals) are subjected to the study. The performance of the STGNN is compared to that of a time growing neural network (CTGNN) and a conventional support vector (CSVM) machine, using balanced repeated random sub sampling. The average of the accuracy/sensitivity is estimated to be 87.4/86.5 for the STGNN, 81.8/83.4 for the CTGNN, and 72.9/66.8 for the CSVM. Results show that the STGNN offers better performance and provides more immunity to the background noise as compared to the CTGNN and CSVM. The method is implementable in a computer system to be employed in primary healthcare centers to improve the screening accuracy.

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Acknowledgments

This study was supported by the KKS financed research profile Embedded sensor systems for health at Mälardalen University, Sweden, the CAPIS Biomedical Research and Department Center, Mons, Belgium, and the TCTS lab in Mons University, Belgium.

Conflict of Interest

The authors state that they have no conflict of interest associated with this study.

Statement of Human Studies

All the procedures followed in this study were in accordance with the ethical standards of the responsible committee on human experimentation and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all the patients or their legal guardians for participating in the study.

Statement of Animal Studies

No animal studies were carried out by the authors for this article.

Author information

Authors and Affiliations

  1. Division of Intelligent Future Technology, Department of Innovation, Design and Technology, Mälardalen University, Västerås, Sweden

    Arash Gharehbaghi & Maria Lindén

  2. TCTS Lab, Faculty of Polytechnic, Mons University, Mons, Belgium

    Thierry Dutoit

  3. CAPIS Biomedical Research and Department Center, Mons, Belgium

    Amir A. Sepehri

  4. Department of Pediatrics, Tehran University of Medical Sciences, Tehran, Iran

    Armen Kocharian

  5. Department of Clinical Cardiology, Children’s Medical Center, Pediatrics Center of Excellence, Tehran, Iran

    Armen Kocharian

Authors
  1. Arash Gharehbaghi
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  2. Thierry Dutoit
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  3. Amir A. Sepehri
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  4. Armen Kocharian
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  5. Maria Lindén
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Corresponding author

Correspondence to Arash Gharehbaghi.

Additional information

Associate Editor Ajit P. Yoganathan oversaw the review of this article.

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Gharehbaghi, A., Dutoit, T., Sepehri, A.A. et al. A Novel Method for Screening Children with Isolated Bicuspid Aortic Valve. Cardiovasc Eng Tech 6, 546–556 (2015). https://doi.org/10.1007/s13239-015-0238-6

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  • DOI: https://doi.org/10.1007/s13239-015-0238-6

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