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算法改进后的微波雷达监测呼吸比传感器带更准确。

Algoritmically improved microwave radar monitors breathing more acurrate than sensorized belt.

机构信息

Department of Multimedia Systems, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, 80‑233, Gdańsk, Poland.

Audio Acoustics Department, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, 80‑233, Gdańsk, Poland.

出版信息

Sci Rep. 2022 Aug 24;12(1):14412. doi: 10.1038/s41598-022-18808-2.


DOI:10.1038/s41598-022-18808-2
PMID:36002632
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9400007/
Abstract

This paper describes a novel way to measure, process, analyze, and compare respiratory signals acquired by two types of devices: a wearable sensorized belt and a microwave radar-based sensor. Both devices provide breathing rate readouts. First, the background research is presented. Then, the underlying principles and working parameters of the microwave radar-based sensor, a contactless device for monitoring breathing, are described. The breathing rate measurement protocol is then presented, and the proposed algorithm for octave error elimination is introduced. Details are provided about the data processing phase; specifically, the management of signals acquired from two devices with different working principles and how they are resampled with a common processing sample rate. This is followed by an analysis of respiratory signals experimentally acquired by the belt and microwave radar-based sensors. The analysis outcomes were checked using Levene's test, the Kruskal-Wallis test, and Dunn's post hoc test. The findings show that the proposed assessment method is statistically stable. The source of variability lies in the person-triggered breathing patterns rather than the working principles of the devices used. Finally, conclusions are derived, and future work is outlined.

摘要

本文描述了一种新颖的方法,用于测量、处理、分析和比较两种设备获取的呼吸信号:一种是带有传感器的可穿戴腰带,另一种是基于微波雷达的传感器。这两种设备都提供呼吸频率读数。首先介绍背景研究。然后,描述了基于微波雷达的传感器的基本原理和工作参数,该传感器是一种用于监测呼吸的非接触式设备。接着介绍了呼吸率测量协议,并引入了用于消除倍频程误差的建议算法。详细说明了数据处理阶段的细节;具体来说,管理具有不同工作原理的两种设备采集的信号,以及如何以通用处理采样率对它们进行重采样。然后分析了通过腰带和微波雷达传感器实验获得的呼吸信号。使用莱文检验、克鲁斯卡尔-沃利斯检验和邓恩事后检验检查分析结果。结果表明,所提出的评估方法在统计学上是稳定的。可变性的来源在于人为触发的呼吸模式,而不是所使用设备的工作原理。最后得出结论并概述了未来的工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/b0a1a0e515f4/41598_2022_18808_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/ca9b00a43438/41598_2022_18808_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/c02a3f1341dc/41598_2022_18808_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/d0f098f0fce5/41598_2022_18808_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/431163dc20df/41598_2022_18808_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/9f120c15bbd2/41598_2022_18808_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/f0aaf9407de4/41598_2022_18808_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/75d331647795/41598_2022_18808_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/d23d3896b6b3/41598_2022_18808_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/073c313918f4/41598_2022_18808_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/57de8710ef9e/41598_2022_18808_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/ef6fecaccb8b/41598_2022_18808_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/fd8e093c1a4f/41598_2022_18808_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/82f93d37fda9/41598_2022_18808_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/b0a1a0e515f4/41598_2022_18808_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/ca9b00a43438/41598_2022_18808_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/c02a3f1341dc/41598_2022_18808_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/d0f098f0fce5/41598_2022_18808_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/431163dc20df/41598_2022_18808_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/9f120c15bbd2/41598_2022_18808_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/f0aaf9407de4/41598_2022_18808_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/75d331647795/41598_2022_18808_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/d23d3896b6b3/41598_2022_18808_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/073c313918f4/41598_2022_18808_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/57de8710ef9e/41598_2022_18808_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/ef6fecaccb8b/41598_2022_18808_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/fd8e093c1a4f/41598_2022_18808_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/82f93d37fda9/41598_2022_18808_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f51/9402717/b0a1a0e515f4/41598_2022_18808_Fig14_HTML.jpg

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[2]
Mining Knowledge of Respiratory Rate Quantification and Abnormal Pattern Prediction.

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[3]
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[4]
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[5]
NeuroKit2: A Python toolbox for neurophysiological signal processing.

Behav Res Methods. 2021-8

[6]
Wearable Belt With Built-In Textile Electrodes for Cardio-Respiratory Monitoring.

Sensors (Basel). 2020-8-12

[7]
The Reflectance of Human Skin in the Millimeter-Wave Band.

Sensors (Basel). 2020-3-8

[8]
Estimation of respiratory rate using infrared video in an inpatient population: an observational study.

J Clin Monit Comput. 2020-12

[9]
Contact-Based Methods for Measuring Respiratory Rate.

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[10]
A new physiological signal acquisition patch designed with advanced respiration monitoring algorithm based on 3-axis accelerator and gyroscope.

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