An electrocardiography system design for obstructive sleep apnea detection based on improved lomb frequency analysis algorithm

Wai-Chi Fang, I. Wei Chen, Shu Han Fan, Chih Kuo Lee

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

3 Scopus citations

Abstract

In this paper, we present a real-time method for obstructive sleep apnea (OSA) detection of frequency analysis of ECG-derived respiratory (EDR) and heart rate variability (HRV). The method is computationally simple with ECG signals to determine the time interval of OSA. We compare it to a traditional complexly Polysomnography (PSG) which needs several physiological signals measured from patients. For the wearable real-time application, the simplified Lomb Periodogram is proposed to perform the frequency analysis of EDR and HRV. The data from 900 ECG recordings from MIT PhysioNet Sleep Apnea database was utilized in the paper. The approximated method of OSA method obtained the highest Specificity (Sp) 90.1%, Sensitivity (Se) 94.3%, and Accuracy 92.1%.

Original languageEnglish
Title of host publication2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
ISBN (Electronic)9781509058037
DOIs
StatePublished - 23 Mar 2018
Event2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Torino, Italy
Duration: 19 Oct 201721 Oct 2017

Publication series

Name2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings
Volume2018-January

Conference

Conference2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017
CountryItaly
CityTorino
Period19/10/1721/10/17

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