Abstract

This study focused on extracting to finding differences between apnea events and non-apnea events using time-frequency approach. This approach is of particular relevance to obtain the efficiency and accuracy of the support system for the classification model. Heart rate variability(HRV) was calculated using the statistic and frequency approach based on the time-frequency domain. The analysis of HRV, about the occurrence of the short recording, was performed selecting two segments: a class of apnea events and a class of non-apnea events. The experiment findings of the statistical analysis of our feature extraction showed time-domain feature estimation with Heart rate means (BPM) slightly higher for non-apnea events about mean ± standard deviation (72(±4)). The frequency-domain features, at VLF, LF and HF power of apnea events, are monitored over time with non-apnea events. The overall experiment indicates a significantly different feature value in the heart rate during examining apnea events and non-apnea events.

Original languageEnglish
Title of host publication2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728129655
DOIs
Publication statusPublished - Nov 2019
Event2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Surabaya, Indonesia
Duration: 19 Nov 201920 Nov 2019

Publication series

Name2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding
Volume2019-November

Conference

Conference2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019
Country/TerritoryIndonesia
CitySurabaya
Period19/11/1920/11/19

Keywords

  • apnea
  • hrv
  • non-apnea
  • qrs complex
  • spectrogram

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