利用微波多普勒雷达传感器对心脏运动进行基于模型的估计。

IF 3.3 4区 医学 Q1 PHYSIOLOGY
Takashi Ota, Kosuke Okusa
{"title":"利用微波多普勒雷达传感器对心脏运动进行基于模型的估计。","authors":"Takashi Ota, Kosuke Okusa","doi":"10.1186/s40101-024-00373-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Heart rate is one of the most crucial vital signs and can be measured remotely using microwave Doppler radar. As the distance between the body and the Doppler radar sensor increases, the output signal weakens, making it difficult to extract heartbeat waveforms. In this study, we propose a new template-matching method that addresses this issue by simulating Doppler radar signals. This method extracts the heartbeat waveform with higher accuracy while the participant is naturally sitting in a chair.</p><p><strong>Methods: </strong>An extended triangular wave model was created as a mathematical representation of cardiac physiology, taking into account heart movements. The Doppler radar output signal was then simulated based on this model to automatically obtain a template for one cycle. The validity of the proposed method was confirmed by calculating the PPIs using the template and comparing their accuracy to the R-R intervals (RRIs) of the electrocardiogram for five participants and by analyzing the signals of eight participants in their natural state using the mathematical model of heart movements. All measurements were conducted from a distance of 500 mm.</p><p><strong>Results: </strong>The correlation coefficients between the RRIs of the electrocardiogram and the PPIs using the proposed method were examined for five participants. The correlation coefficients were 0.93 without breathing and 0.70 with breathing. This demonstrates a higher correlation considering the long distance of 500 mm, and the fact that body movements were not specifically restricted, suggesting that the proposed method can successfully estimate RRI. The average correlation coefficients, calculated between the Doppler output signals and the templates for each of the eight participants, exceeded 0.95. Overall, the proposed method showed higher correlation coefficients than those reported in previous studies, indicating that our method performed well in extracting heartbeat waveforms.</p><p><strong>Conclusions: </strong>Our results indicate that the proposed method of remote heart monitoring using microwave Doppler radar demonstrates higher accuracy in estimating the RRI of the electrocardiogram while at rest sitting in a chair, and the ability to extract the heartbeat waveforms from the measured Doppler output signal, eliminating the need to create templates in advance as required by conventional template matching methods. This approach offers more flexibility in the measurement environment than conventional methods.</p>","PeriodicalId":48730,"journal":{"name":"Journal of Physiological Anthropology","volume":"43 1","pages":"27"},"PeriodicalIF":3.3000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11492655/pdf/","citationCount":"0","resultStr":"{\"title\":\"Model-based estimation of heart movements using microwave Doppler radar sensor.\",\"authors\":\"Takashi Ota, Kosuke Okusa\",\"doi\":\"10.1186/s40101-024-00373-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Heart rate is one of the most crucial vital signs and can be measured remotely using microwave Doppler radar. As the distance between the body and the Doppler radar sensor increases, the output signal weakens, making it difficult to extract heartbeat waveforms. In this study, we propose a new template-matching method that addresses this issue by simulating Doppler radar signals. This method extracts the heartbeat waveform with higher accuracy while the participant is naturally sitting in a chair.</p><p><strong>Methods: </strong>An extended triangular wave model was created as a mathematical representation of cardiac physiology, taking into account heart movements. The Doppler radar output signal was then simulated based on this model to automatically obtain a template for one cycle. The validity of the proposed method was confirmed by calculating the PPIs using the template and comparing their accuracy to the R-R intervals (RRIs) of the electrocardiogram for five participants and by analyzing the signals of eight participants in their natural state using the mathematical model of heart movements. All measurements were conducted from a distance of 500 mm.</p><p><strong>Results: </strong>The correlation coefficients between the RRIs of the electrocardiogram and the PPIs using the proposed method were examined for five participants. The correlation coefficients were 0.93 without breathing and 0.70 with breathing. This demonstrates a higher correlation considering the long distance of 500 mm, and the fact that body movements were not specifically restricted, suggesting that the proposed method can successfully estimate RRI. The average correlation coefficients, calculated between the Doppler output signals and the templates for each of the eight participants, exceeded 0.95. Overall, the proposed method showed higher correlation coefficients than those reported in previous studies, indicating that our method performed well in extracting heartbeat waveforms.</p><p><strong>Conclusions: </strong>Our results indicate that the proposed method of remote heart monitoring using microwave Doppler radar demonstrates higher accuracy in estimating the RRI of the electrocardiogram while at rest sitting in a chair, and the ability to extract the heartbeat waveforms from the measured Doppler output signal, eliminating the need to create templates in advance as required by conventional template matching methods. This approach offers more flexibility in the measurement environment than conventional methods.</p>\",\"PeriodicalId\":48730,\"journal\":{\"name\":\"Journal of Physiological Anthropology\",\"volume\":\"43 1\",\"pages\":\"27\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11492655/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Physiological Anthropology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s40101-024-00373-4\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHYSIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Physiological Anthropology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40101-024-00373-4","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHYSIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

背景:心率是最重要的生命体征之一,可使用微波多普勒雷达进行远程测量。随着人体与多普勒雷达传感器之间距离的增加,输出信号会减弱,从而难以提取心跳波形。在本研究中,我们提出了一种新的模板匹配方法,通过模拟多普勒雷达信号来解决这一问题。这种方法能在被试者自然坐在椅子上时以更高的精度提取心跳波形:方法:建立了一个扩展的三角波模型,作为心脏生理的数学表示,同时考虑到心脏运动。然后根据该模型模拟多普勒雷达输出信号,自动获得一个周期的模板。通过使用模板计算 PPI,并将其准确性与五名参与者的心电图 R-R 间期 (RRI) 进行比较,以及使用心脏运动数学模型分析八名参与者自然状态下的信号,证实了所建议方法的有效性。所有测量均在 500 毫米的距离内进行:对五名参与者的心电图 RRI 和使用建议方法的 PPI 之间的相关系数进行了研究。无呼吸时的相关系数为 0.93,有呼吸时为 0.70。考虑到 500 毫米的长距离,以及身体运动未受到特别限制的事实,这显示了较高的相关性,表明所建议的方法可以成功估算 RRI。多普勒输出信号与模板之间的平均相关系数超过了 0.95。总体而言,拟议方法显示出的相关系数高于以往研究报告中的相关系数,表明我们的方法在提取心跳波形方面表现良好:我们的研究结果表明,利用微波多普勒雷达进行远程心脏监测的拟议方法在估算坐在椅子上休息时的心电图 RRI 方面具有更高的准确性,而且能够从测量到的多普勒输出信号中提取心跳波形,无需像传统的模板匹配方法那样事先创建模板。与传统方法相比,这种方法为测量环境提供了更大的灵活性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model-based estimation of heart movements using microwave Doppler radar sensor.

Background: Heart rate is one of the most crucial vital signs and can be measured remotely using microwave Doppler radar. As the distance between the body and the Doppler radar sensor increases, the output signal weakens, making it difficult to extract heartbeat waveforms. In this study, we propose a new template-matching method that addresses this issue by simulating Doppler radar signals. This method extracts the heartbeat waveform with higher accuracy while the participant is naturally sitting in a chair.

Methods: An extended triangular wave model was created as a mathematical representation of cardiac physiology, taking into account heart movements. The Doppler radar output signal was then simulated based on this model to automatically obtain a template for one cycle. The validity of the proposed method was confirmed by calculating the PPIs using the template and comparing their accuracy to the R-R intervals (RRIs) of the electrocardiogram for five participants and by analyzing the signals of eight participants in their natural state using the mathematical model of heart movements. All measurements were conducted from a distance of 500 mm.

Results: The correlation coefficients between the RRIs of the electrocardiogram and the PPIs using the proposed method were examined for five participants. The correlation coefficients were 0.93 without breathing and 0.70 with breathing. This demonstrates a higher correlation considering the long distance of 500 mm, and the fact that body movements were not specifically restricted, suggesting that the proposed method can successfully estimate RRI. The average correlation coefficients, calculated between the Doppler output signals and the templates for each of the eight participants, exceeded 0.95. Overall, the proposed method showed higher correlation coefficients than those reported in previous studies, indicating that our method performed well in extracting heartbeat waveforms.

Conclusions: Our results indicate that the proposed method of remote heart monitoring using microwave Doppler radar demonstrates higher accuracy in estimating the RRI of the electrocardiogram while at rest sitting in a chair, and the ability to extract the heartbeat waveforms from the measured Doppler output signal, eliminating the need to create templates in advance as required by conventional template matching methods. This approach offers more flexibility in the measurement environment than conventional methods.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
6.50%
发文量
39
期刊介绍: Journal of Physiological Anthropology (JPA) is an open access, peer-reviewed journal that publishes research on the physiological functions of modern mankind, with an emphasis on the physical and bio-cultural effects on human adaptability to the current environment. The objective of JPA is to evaluate physiological adaptations to modern living environments, and to publish research from different scientific fields concerned with environmental impact on human life. Topic areas include, but are not limited to: environmental physiology bio-cultural environment living environment epigenetic adaptation development and growth age and sex differences nutrition and morphology physical fitness and health Journal of Physiological Anthropology is the official journal of the Japan Society of Physiological Anthropology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信