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Evaluating reliability of ultrashort heart rate variability parameters in metabolic syndrome subjects

  • Darwin Astudilllo
  • , Kenneth Palacio-Baus
  • , Lizandro Solano-Quinde
  • , Erika Severeyn
  • , Sara Wong
  • Universidad de Cuenca
  • Simon Bolivar University Caracas

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

Abstract

Heart rate variability (HRV) analysis is barely employed in healthcare environments mainly because of the lack of standard values determining the sympathovagal balance and the difficulty to register RR stationary series. Recent studies have proposed the use of shorter HRV series. For this work, we use a public metabolic syndrome subjects database retrieved during oral glucose tolerance test. In order to explore ultra-short HRV measures reliability we employ an autoregressive model using Burg method, such that short RR sequences can be evaluated while maintaining a good frequency resolution. RR, SD, rMSSD, LF, HF, LFn and LF/HF were computed for different RR sequences (10 min, 5 min, 1 min, 30 s, 10 s). To evaluate the reliability we used the intraclass correlation coefficient (ICC). Additionally, we compared the sympathovagal balance parameters (LFn, LF/HF) among the stages (basal and 30 min). Considering 10 min long registers as references, parameters obtained from 5 min long series present ICC values above 0.78 for all cases. One min long registers present ICC values above 0.70 only for temporal parameters in both RR series and rMSSD. By comparing LFn and LF/HF parameters among the basal state and 30 min, we observed a significant increase of the sympathetic tone (p < 0.05). However, these differences are important only for 10 and 5 min series. In general, we observe that temporal parameters exhibit higher reliability than those the spectral ones. Nonetheless, registers duration below one min do not present adequate results for the spectral parameters in this work.

Original languageEnglish
Title of host publication2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
EditorsMiguel Altuve
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509037971
DOIs
StatePublished - 14 Nov 2016
Event21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016 - Bucaramanga, Colombia
Duration: 30 Aug 20162 Sep 2016

Publication series

Name2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016

Conference

Conference21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
Country/TerritoryColombia
CityBucaramanga
Period30/08/162/09/16

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