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基于图形表示的运动中心音特征分析。

Analysis of Heart-Sound Characteristics during Motion Based on a Graphic Representation.

机构信息

College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.

出版信息

Sensors (Basel). 2021 Dec 28;22(1):181. doi: 10.3390/s22010181.

DOI:10.3390/s22010181
PMID:35009728
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8749711/
Abstract

In this paper, the graphic representation method is used to study the multiple characteristics of heart sounds from a resting state to a state of motion based on single- and four-channel heart-sound signals. Based on the concept of integration, we explore the representation method of heart sound and blood pressure during motion. To develop a single- and four-channel heart-sound collector, we propose new concepts such as a sound-direction vector of heart sound, a motion-response curve of heart sound, the difference value, and a state-change-trend diagram. Based on the acoustic principle, the reasons for the differences between multiple-channel heart-sound signals are analyzed. Through a comparative analysis of four-channel motion and resting-heart sounds, from a resting state to a state of motion, the maximum and minimum similarity distances in the corresponding state-change-trend graphs were found to be 0.0038 and 0.0006, respectively. In addition, we provide several characteristic parameters that are both sensitive (such as heart sound amplitude, blood pressure, systolic duration, and diastolic duration) and insensitive (such as sound-direction vector, state-change-trend diagram, and difference value) to motion, thus providing a new technique for the diverse analysis of heart sounds in motion.

摘要

本文基于单通道和四通道心音信号,采用图形表示法研究了从静息状态到运动状态的心音的多种特征。基于积分的概念,探索了运动中心音和血压的表示方法。为了开发单通道和四通道心音采集器,我们提出了心音声矢量、心音运动响应曲线、差值和状态变化趋势图等新概念。根据声学原理,分析了多通道心音信号差异的原因。通过对四通道运动和静息心音的对比分析,从静息状态到运动状态,发现相应状态变化趋势图中的最大和最小相似距离分别为 0.0038 和 0.0006。此外,我们还提供了一些特征参数,这些参数既敏感(如心音幅度、血压、收缩期持续时间和舒张期持续时间)又不敏感(如声矢量、状态变化趋势图和差值),为运动中心音的多样性分析提供了新的技术手段。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/fd7bc2111eab/sensors-22-00181-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/188e607007d0/sensors-22-00181-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/57553d07e012/sensors-22-00181-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/baac8550a858/sensors-22-00181-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/d34b777f9c9f/sensors-22-00181-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/fd7bc2111eab/sensors-22-00181-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/188e607007d0/sensors-22-00181-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/e30755bae60e/sensors-22-00181-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/b59136ebfc00/sensors-22-00181-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/30fcf8c0cb25/sensors-22-00181-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/4f675c506a22/sensors-22-00181-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/57553d07e012/sensors-22-00181-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/baac8550a858/sensors-22-00181-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/d34b777f9c9f/sensors-22-00181-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de18/8749711/fd7bc2111eab/sensors-22-00181-g009.jpg

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