Publication detail

Sleep Apnea Detection Using Single Lead ECG Respiration Estimates

KRÁLÍK, M. KOZUMPLÍK, J.

Original Title

Sleep Apnea Detection Using Single Lead ECG Respiration Estimates

English Title

Sleep Apnea Detection Using Single Lead ECG Respiration Estimates

Type

conference paper

Language

en

Original Abstract

This article is dealing with problematics of sleep apnea syndrome and its diagnostics. It briefly summarizes two main types of sleep apnea and their distinctive features visible on polysomnographic signal. Using Physionet database as a source of data, one of the alternative approaches of sleep apnea detection is utilized, using respiration sinus arrhythmia (RSA) method of respiration estimate and single lead electrocardiography (ECG) signal. Multiple classification methods are utilized for comparison with overall accuracy over 80 % achieved.

English abstract

This article is dealing with problematics of sleep apnea syndrome and its diagnostics. It briefly summarizes two main types of sleep apnea and their distinctive features visible on polysomnographic signal. Using Physionet database as a source of data, one of the alternative approaches of sleep apnea detection is utilized, using respiration sinus arrhythmia (RSA) method of respiration estimate and single lead electrocardiography (ECG) signal. Multiple classification methods are utilized for comparison with overall accuracy over 80 % achieved.

Keywords

ECG estimated respiration (EDR), respiration sinus arrhythmia (RSA), sleep apnea classification

Released

05.10.2018

Publisher

Technická univerzita v Košiciach

Location

Košice

ISBN

978-80-8086-271-8

Book

YBERC 2018 International Conference Proceedings

Pages from

1

Pages to

5

Pages count

5

URL

http://www.yberc.sk/2018/

Documents

BibTex 


@inproceedings{BUT150353,
  author="Martin {Králík} and Jiří {Kozumplík}",
  title="Sleep Apnea Detection Using Single Lead ECG Respiration Estimates",
  annote="This article is dealing with problematics of sleep apnea syndrome and its diagnostics. It briefly summarizes two main types of sleep apnea and their distinctive features visible on polysomnographic signal. Using Physionet database as a source of data, one of the alternative approaches of sleep apnea detection is utilized, using respiration sinus arrhythmia (RSA) method of respiration estimate and single lead electrocardiography (ECG) signal. Multiple classification methods are utilized for comparison with overall accuracy over 80 % achieved.",
  address="Technická univerzita v Košiciach",
  booktitle="YBERC 2018 International Conference Proceedings",
  chapter="150353",
  howpublished="electronic, physical medium",
  institution="Technická univerzita v Košiciach",
  year="2018",
  month="october",
  pages="1--5",
  publisher="Technická univerzita v Košiciach",
  type="conference paper"
}