Application study of apnea-hypopnea duration for assessing adult obstructive sleep apnea.

IF 1.4 4区医学 Q4 ENGINEERING, BIOMEDICAL Technology and Health Care Pub Date : 2024-01-01 DOI:10.3233/THC-231900

Weigen Cheng, Cheng Xu, Fen Wang, Yongmin Ding, Jianglong Tu, Linglin Xia

{"title":"Application study of apnea-hypopnea duration for assessing adult obstructive sleep apnea.","authors":"Weigen Cheng, Cheng Xu, Fen Wang, Yongmin Ding, Jianglong Tu, Linglin Xia","doi":"10.3233/THC-231900","DOIUrl":null,"url":null,"abstract":"Background: Obstructive sleep apnea (OSA) is a common sleep disordered breathing disorder, which can cause serious damage to multiple human systems. Although polysomnography (PSG) is the current gold standard for diagnosis, it is complex and expensive. Therefore, it is of great significance to find a simple, economical and rapid primary screening and diagnosis method to replace PSG for the diagnosis of OSA.Objective: The purpose of this study is to propose a new method for the diagnosis and classification of OSA, which is used to automatically detect the duration of sleep apnea hypopnea events (AHE), so as to estimate the ratio(S) of the total duration of all-night AHE to the total sleep time only based on the sound signal of sleep respiration, and to identify OSA.Methods: We performed PSG tests on participants and extracted relevant sleep breathing sound signal data. This study is carried out in two stages. In the first stage, the relevant PSG report data of eligible subjects were recorded, the total duration of AHE in each subject's data was extracted, and the S value was calculated to evaluate the severity of OSA. In the second stage, only the sleep breath sound signal data of the same batch of subjects were used for automatic detection, and the S value in the sleep breath sound signal was extracted, and the S value was compared with the PSG diagnosis results to calculate the accuracy of the experimental method.Results: Among 225 subjects. Using PSG as the reference standard, the S value extracted from the PSG diagnostic data report can accurately diagnose OSA(accuracy rate 99.56%) and distinguish its severity (accuracy rate 95.11%). The accuracy of the S value detected in the sleep breathing sound signal in the diagnosis of severe OSA reached 100%.Conclusion: The results show that the experimental parameter S value is feasible in OSA diagnosis and classification. OSA can be identified and evaluated only by sleep breathing sounds. This method helps to simplify the diagnostic grading of traditional OSA and lays a foundation for the subsequent development of simple diagnostic grading equipment.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"3201-3215"},"PeriodicalIF":1.4000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technology and Health Care","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3233/THC-231900","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}

引用次数: 0

Abstract

Background: Obstructive sleep apnea (OSA) is a common sleep disordered breathing disorder, which can cause serious damage to multiple human systems. Although polysomnography (PSG) is the current gold standard for diagnosis, it is complex and expensive. Therefore, it is of great significance to find a simple, economical and rapid primary screening and diagnosis method to replace PSG for the diagnosis of OSA.

Objective: The purpose of this study is to propose a new method for the diagnosis and classification of OSA, which is used to automatically detect the duration of sleep apnea hypopnea events (AHE), so as to estimate the ratio(S) of the total duration of all-night AHE to the total sleep time only based on the sound signal of sleep respiration, and to identify OSA.

Methods: We performed PSG tests on participants and extracted relevant sleep breathing sound signal data. This study is carried out in two stages. In the first stage, the relevant PSG report data of eligible subjects were recorded, the total duration of AHE in each subject's data was extracted, and the S value was calculated to evaluate the severity of OSA. In the second stage, only the sleep breath sound signal data of the same batch of subjects were used for automatic detection, and the S value in the sleep breath sound signal was extracted, and the S value was compared with the PSG diagnosis results to calculate the accuracy of the experimental method.

Results: Among 225 subjects. Using PSG as the reference standard, the S value extracted from the PSG diagnostic data report can accurately diagnose OSA(accuracy rate 99.56%) and distinguish its severity (accuracy rate 95.11%). The accuracy of the S value detected in the sleep breathing sound signal in the diagnosis of severe OSA reached 100%.

Conclusion: The results show that the experimental parameter S value is feasible in OSA diagnosis and classification. OSA can be identified and evaluated only by sleep breathing sounds. This method helps to simplify the diagnostic grading of traditional OSA and lays a foundation for the subsequent development of simple diagnostic grading equipment.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

用于评估成人阻塞性睡眠呼吸暂停的呼吸暂停-低通气持续时间应用研究。

背景：阻塞性睡眠呼吸暂停（OSA）是一种常见的睡眠呼吸障碍，可对人体多个系统造成严重损害。虽然多导睡眠图（PSG）是目前诊断的黄金标准，但其复杂且昂贵。因此，寻找一种简单、经济、快速的初筛和诊断方法来替代 PSG 诊断 OSA 具有重要意义：本研究旨在提出一种用于诊断和分类 OSA 的新方法，该方法用于自动检测睡眠呼吸暂停低通气事件（AHE）的持续时间，从而根据睡眠呼吸的声音信号估算出整夜 AHE 的总持续时间与总睡眠时间的比值（S），进而识别 OSA：方法：我们对参与者进行 PSG 测试，并提取相关的睡眠呼吸声音信号数据。本研究分两个阶段进行。第一阶段，记录符合条件的受试者的相关 PSG 报告数据，提取每个受试者数据中的 AHE 总持续时间，并计算 S 值，以评估 OSA 的严重程度。第二阶段，只对同一批受试者的睡眠呼吸音信号数据进行自动检测，提取睡眠呼吸音信号中的 S 值，并将 S 值与 PSG 诊断结果进行对比，计算实验方法的准确性：在 225 名受试者中。以 PSG 为参考标准，从 PSG 诊断数据报告中提取的 S 值可以准确诊断 OSA（准确率为 99.56%）并区分其严重程度（准确率为 95.11%）。从睡眠呼吸音信号中检测出的 S 值诊断重度 OSA 的准确率达到 100%：结果表明，实验参数 S 值在 OSA 诊断和分类中是可行的。结论：结果表明，实验参数 S 值在 OSA 诊断和分级中是可行的。该方法有助于简化传统 OSA 的诊断分级，为后续开发简易诊断分级设备奠定了基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Technology and Health Care HEALTH CARE SCIENCES & SERVICES-ENGINEERING, BIOMEDICAL

CiteScore

2.10

自引率

6.20%

发文量

282

审稿时长

>12 weeks

期刊介绍： Technology and Health Care is intended to serve as a forum for the presentation of original articles and technical notes, observing rigorous scientific standards. Furthermore, upon invitation, reviews, tutorials, discussion papers and minisymposia are featured. The main focus of THC is related to the overlapping areas of engineering and medicine. The following types of contributions are considered: 1.Original articles: New concepts, procedures and devices associated with the use of technology in medical research and clinical practice are presented to a readership with a widespread background in engineering and/or medicine. In particular, the clinical benefit deriving from the application of engineering methods and devices in clinical medicine should be demonstrated. Typically, full length original contributions have a length of 4000 words, thereby taking duly into account figures and tables. 2.Technical Notes and Short Communications: Technical Notes relate to novel technical developments with relevance for clinical medicine. In Short Communications, clinical applications are shortly described. 3.Both Technical Notes and Short Communications typically have a length of 1500 words. Reviews and Tutorials (upon invitation only): Tutorial and educational articles for persons with a primarily medical background on principles of engineering with particular significance for biomedical applications and vice versa are presented. The Editorial Board is responsible for the selection of topics. 4.Minisymposia (upon invitation only): Under the leadership of a Special Editor, controversial or important issues relating to health care are highlighted and discussed by various authors. 5.Letters to the Editors: Discussions or short statements (not indexed).