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Dimensional analysis of heart rate variability parameters for metabolic dysfunctions diagnosis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Obesity, metabolic syndrome (MS) and insulin resistance (IR) are diseases related to lifestyle, they have become a social and public health problem. There are numerous diagnostic criteria of MS, the most used is the diagnostic criterion according to NCEP-ATP III and the NCEP-ATP III revised version. Otherwise, obesity and IR are diagnosed through HOMA-IR and body mass index (BMI), respectively. These methods have diagnostic limitations; in HOMA-IR case there can be false negatives in incipient stages of the disease. BMI may show false positives in subjects with a high percentage of muscle mass. In addition to the anthropometric and biochemical variables, other types of parameters have been studied for the diagnosis of obesity, MS and IR; studies reveal that heart rate variability (HRV) parameters can discriminate between diabetic, MS and control subjects. The aim of this research is to propose dimensionless indexes that can be used to diagnose subjects with MS, IR and obesity using HRV parameters (RR, RMSSD, SD, HF and LF). For this purpose, seven dimensionless indexes, designed from the π Vaschy-Buckingham theorem, were assessed using ROC curves and a database of 40 subjects. The index π1, built with the variables: HF and RMSSD; obtained a better performance as classifier of MS, IR and obesity, presenting an area under the ROC curve greater than 0.70, a sensitivity and specificity greater than 0.70 in each pathology. The π1 dimensionless index designed in this study is a simple method that allows diagnosing three pathologies from a non-invasive test such as electrocardiogram.

Original languageEnglish
Title of host publication2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538638941
DOIs
StatePublished - 4 Jan 2018
Event2nd IEEE Ecuador Technical Chapters Meeting, ETCM 2017 - Salinas, Ecuador
Duration: 16 Oct 201720 Oct 2017

Publication series

Name2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017
Volume2017-January

Conference

Conference2nd IEEE Ecuador Technical Chapters Meeting, ETCM 2017
Country/TerritoryEcuador
CitySalinas
Period16/10/1720/10/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Dimensional analysis
  • medical database
  • metabolic syndrome
  • ROC curves
  • theorem π of Vaschy-Buckingham

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