An Apnea Detection Method Based on Correlation Analysis of Blood Oxygen Desaturation and Pulse Rate Variability

被引：0

作者：

Huang, Longping ^{[1
]}

Li, Min ^{[1
]}

Zhao, Yihan

He, Dong

Yang, Haonan

机构：

[1] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200072, Peoples R China

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (RCAR) | 2017年

基金：

中国国家自然科学基金;

关键词：

OSA; SpO2; Pulse rate variability; Apnea detection; SLEEP-APNEA;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Obstructive Sleep Apnea (OSA) is a widespread breathing disorder during sleep. Traditional approaches to the diagnosis of OSA based on polysomnography are inconvenient and uncomfortable, which may lead to unconvincing detection results. This paper proposes an apnea detection method based on correlation analysis of blood oxygen desaturation and pulse rate variability. The blood oxygen desaturation events are figured out by analyzing the characteristics of sampled SpO2 data in both time and frequency domain. Then the associated apnea events are detected by investigating the variability of pulse rate in detail. By comparing with the referenced results obtained from the respiration wave, the results verified that the proposed algorithm is reliable.

引用

页码：403 / 408

页数：6

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