標題: Real-Time Obstructive Sleep Apnea Detection from Frequency Analysis of EDR and HRV using Lomb Periodogram
作者: Fan, Shu-Han
Chou, Chia-Ching
Chen, Wei-Chen
Fang, Wai-Chi
電機工程學系
Department of Electrical and Computer Engineering
公開日期: 2015
摘要: In this study, an effective real-time obstructive sleep apnea (OSA) detection method from frequency analysis of ECG-derived respiratory (EDR) and heart rate variability (HRV) is proposed. Compared to traditional Polysomnography (PSG) which needs several physiological signals measured from patients, the proposed OSA detection method just only use ECG signals to determine the time interval of OSA. In order to be feasible to be implemented in hardware to achieve the real-time detection and portable application, the simplified Lomb Periodogram is utilized to perform the frequency analysis of EDR and HRV in this study. The experimental results of this work indicate that the overall accuracy can be effectively increased with values of Specificity (Sp) of 91%, Sensitivity (Se) of 95.7%, and Accuracy of 93.2% by integrating the EDR and HRV indexes.
URI: http://hdl.handle.net/11536/134291
ISBN: 978-1-4244-9270-1
ISSN: 1557-170X
期刊: 2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
起始頁: 5989
結束頁: 5992
Appears in Collections:Conferences Paper