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Journal of Healthcare Engineering
Volume 2018 (2018), Article ID 1902176, 10 pages
https://doi.org/10.1155/2018/1902176
Research Article

A Novel Sleep Respiratory Rate Detection Method for Obstructive Sleep Apnea Based on Characteristic Moment Waveform

1Graduate School of Science and Engineering, Yamaguchi University, Yamaguchi, Japan
2School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, China

Correspondence should be addressed to Haibin Wang

Received 9 June 2017; Revised 24 September 2017; Accepted 9 October 2017; Published 10 January 2018

Academic Editor: Chengyu Liu

Copyright © 2018 Yu Fang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Obstructive sleep apnea (OSA) affecting human’s health is a kind of major breathing-related sleep disorders and sometimes leads to nocturnal death. Respiratory rate (RR) of a sleep breathing sound signal is an important human vital sign for OSA monitoring during whole-night sleeping. A novel sleep respiratory rate detection with high computational speed based on characteristic moment waveform (CMW) method is proposed in this paper. A portable and wearable sound device is used to acquire the breathing sound signal. And the amplitude contrast decreasing has been done first. Then, the CMW is extracted with suitable time scale parameters, and the sleep RR value is calculated by the extreme points of CMW. Experiments of one OSA case and five healthy cases are tested to validate the efficiency of the proposed sleep RR detection method. According to manual counting, sleep RR can be detected accurately by the proposed method. In addition, the apnea sections can be detected by the sleep RR values with a given threshold, and the time duration of the segmentation of the breath can be calculated for detailed evaluation of the state of OSA. The proposed method is meaningful for continued research on the sleep breathing sound signal.