Suppr超能文献

使用可穿戴设备的声学信号进行呼吸频率估计的临床验证

Clinical Validation of Respiratory Rate Estimation Using Acoustic Signals from a Wearable Device.

作者信息

Abdulsadig Rawan S, Devani Nikesh, Singh Sukhpreet, Patel Zaibaa, Pramono Renard Xaviero Adhi, Mandal Swapna, Rodriguez-Villegas Esther

机构信息

Wearable Technologies Lab, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2BT, UK.

Thoracic Medicine, Royal Free London NHS Foundation Trust, London NW3 2QG, UK.

出版信息

J Clin Med. 2024 Nov 27;13(23):7199. doi: 10.3390/jcm13237199.

Abstract

: Respiratory rate (RR) is a clinical measure of breathing frequency, a vital metric for clinical assessment. However, the recording and documentation of RR are considered to be extremely poor due to the limitations of the current approaches to measuring RR, including capnography and manual counting. We conducted a validation of the automatic RR measurement capability of AcuPebble RE100 (Acurable, London, UK) against a gold-standard capnography system and a type-III cardiorespiratory polygraphy system in two independent prospective and retrospective studies. : The experiment for the prospective study was conducted at Imperial College London. Data from AcuPebble RE100 (Acurable, London, UK) and the reference capnography system (Capnostream™35, Medtronic, Minneapolis, MN, USA) were collected simultaneously from healthy volunteers. The data from a previously published study were used in the retrospective study, where the patients were recruited consecutively from a standard Obstructive Sleep Apnea (OSA) diagnostic pathway in a UK hospital. Overnight data during sleep were collected using the AcuPebble SA100 (Acurable, London, UK) sensor and a type-III cardiorespiratory polygraphy system (Embletta MPR Sleep System, Natus Medical, Pleasanton, CA, USA) at the patients' homes. Data from 15 healthy volunteers were used in the prospective study. For the retrospective study, 150 consecutive patients had been referred for OSA diagnosis and successfully completed the study. : The RR output of AcuPebble RE100 (Acurable, London, UK) was compared against the reference device in terms of the Root Mean Squared Deviation (RMSD), mean error, and standard deviation (SD) of the difference between the paired measurements. In both the prospective and retrospective studies, the AcuPebble RE100 algorithms provided accurate RR measurements, well within the clinically relevant margin of error, typically used by FDA-approved respiratory rate monitoring devices, with the RMSD under three breaths per minute (BPM) and mean errors of 1.83 BPM and 1.4 BPM, respectively. : The evaluation results provide evidence that AcuPebble RE100 (Acurable, London, UK) algorithms produce reliable results and are hence suitable for overnight monitoring of RR.

摘要

呼吸频率(RR)是呼吸频率的一项临床测量指标,是临床评估的重要参数。然而,由于当前测量RR方法的局限性,包括二氧化碳描记法和人工计数,RR的记录和文档记录被认为极其不完善。我们在两项独立的前瞻性和回顾性研究中,针对金标准二氧化碳描记系统和III型心肺多导记录仪系统,对AcuPebble RE100(英国伦敦的Acurable公司)的自动RR测量能力进行了验证。

前瞻性研究的实验在伦敦帝国理工学院进行。同时从健康志愿者身上收集来自AcuPebble RE100(英国伦敦的Acurable公司)和参考二氧化碳描记系统(Capnostream™35,美国明尼阿波利斯的美敦力公司)的数据。回顾性研究使用了先前发表研究中的数据,这些患者是从英国一家医院的标准阻塞性睡眠呼吸暂停(OSA)诊断途径中连续招募的。在患者家中,使用AcuPebble SA100(英国伦敦的Acurable公司)传感器和III型心肺多导记录仪系统(Embletta MPR睡眠系统,美国加利福尼亚州普莱森顿的Natus Medical公司)收集睡眠期间的夜间数据。前瞻性研究使用了15名健康志愿者的数据。对于回顾性研究,150名连续患者被转诊进行OSA诊断并成功完成研究。

将AcuPebble RE100(英国伦敦的Acurable公司)的RR输出与参考设备在配对测量之间差异的均方根偏差(RMSD)、平均误差和标准差(SD)方面进行了比较。在前瞻性和回顾性研究中,AcuPebble RE100算法都提供了准确的RR测量结果,完全在临床相关误差范围内,这是FDA批准的呼吸频率监测设备通常使用的范围,RMSD每分钟低于三次呼吸(BPM),平均误差分别为1.83 BPM和1.4 BPM。

评估结果提供了证据,表明AcuPebble RE100(英国伦敦的Acurable公司)算法产生可靠的结果,因此适用于RR的夜间监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb50/11642485/dc18f0ead3da/jcm-13-07199-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验