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The higher-order spectra (HOSA) as a tool for the rehabilitation progress estimation referred to the patients diagnosed with various cardiac diseases

  • Silesian University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This article explores the possibility of using the higher-order spectra to identify different types of diseases. In order to assess the effectiveness of such tool the HRV (Heart Rate Variability) recordings obtained from patients suffering from three different cardiac problems are listed and compared to the results recorded for healthy subjects. Each set of HRV signals is processed with bispectral and bicoherent analysis. In both cases three statistical parameters are observed. For each type of the investigated analysis the parameters under examination differ enough to allow clear distinction of the specific cardiac disease. The obtained results show usefulness of higher-order spectra as a tool for differentiation between specific diseases. Authors believe that further work would greatly improve potential of the described tool, allowing to identify number of different diseases or even stage of the illness or progress in the rehabilitation process.

Original languageEnglish
Title of host publicationInformation Technology in Biomedicine - Proceedings 6th International Conference, ITIB’2018
EditorsEwa Pietka, Pawel Badura, Jacek Kawa, Wojciech Wieclawek
PublisherSpringer Verlag
Pages303-314
Number of pages12
ISBN (Print)9783319912103
DOIs
Publication statusPublished - 2019
Event6th International Conference on Information Technology in Biomedicine, ITIB 2018 - Kamien Slaski, Poland
Duration: 18 Jun 2018 → 20 Jun 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume762
ISSN (Print)2194-5357

Conference

Conference6th International Conference on Information Technology in Biomedicine, ITIB 2018
Country/TerritoryPoland
CityKamien Slaski
Period18/06/18 → 20/06/18

Keywords

  • Heart rate variability
  • Higher-order statistics
  • Signal processing

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science

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