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Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement
With the rapid increase in the development of miniaturized sensors and embedded devices for vital signs monitoring, personal physiological signal monitoring devices are becoming popular. However, physiological monitoring devices which are worn on the body normally affect the daily activities of peop...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6627890/ https://www.ncbi.nlm.nih.gov/pubmed/31010166 http://dx.doi.org/10.3390/bios9020058 |
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author | Liang, Qiancheng Xu, Lisheng Bao, Nan Qi, Lin Shi, Jingjing Yang, Yicheng Yao, Yudong |
author_facet | Liang, Qiancheng Xu, Lisheng Bao, Nan Qi, Lin Shi, Jingjing Yang, Yicheng Yao, Yudong |
author_sort | Liang, Qiancheng |
collection | PubMed |
description | With the rapid increase in the development of miniaturized sensors and embedded devices for vital signs monitoring, personal physiological signal monitoring devices are becoming popular. However, physiological monitoring devices which are worn on the body normally affect the daily activities of people. This problem can be avoided by using a non-contact measuring device like the Doppler radar system, which is more convenient, is private compared to video monitoring, infrared monitoring and other non-contact methods. Additionally real-time physiological monitoring with the Doppler radar system can also obtain signal changes caused by motion changes. As a result, the Doppler radar system not only obtains the information of respiratory and cardiac signals, but also obtains information about body movement. The relevant RF technology could eliminate some interference from body motion with a small amplitude. However, the motion recognition method can also be used to classify related body motion signals. In this paper, a vital sign and body movement monitoring system worked at 2.4 GHz was proposed. It can measure various physiological signs of the human body in a non-contact manner. The accuracy of the non-contact physiological signal monitoring system was analyzed. First, the working distance of the system was tested. Then, the algorithm of mining collective motion signal was classified, and the accuracy was 88%, which could be further improved in the system. In addition, the mean absolute error values of heart rate and respiratory rate were 0.8 beats/min and 3.5 beats/min, respectively, and the reliability of the system was verified by comparing the respiratory waveforms with the contact equipment at different distances. |
format | Online Article Text |
id | pubmed-6627890 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66278902019-07-23 Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement Liang, Qiancheng Xu, Lisheng Bao, Nan Qi, Lin Shi, Jingjing Yang, Yicheng Yao, Yudong Biosensors (Basel) Article With the rapid increase in the development of miniaturized sensors and embedded devices for vital signs monitoring, personal physiological signal monitoring devices are becoming popular. However, physiological monitoring devices which are worn on the body normally affect the daily activities of people. This problem can be avoided by using a non-contact measuring device like the Doppler radar system, which is more convenient, is private compared to video monitoring, infrared monitoring and other non-contact methods. Additionally real-time physiological monitoring with the Doppler radar system can also obtain signal changes caused by motion changes. As a result, the Doppler radar system not only obtains the information of respiratory and cardiac signals, but also obtains information about body movement. The relevant RF technology could eliminate some interference from body motion with a small amplitude. However, the motion recognition method can also be used to classify related body motion signals. In this paper, a vital sign and body movement monitoring system worked at 2.4 GHz was proposed. It can measure various physiological signs of the human body in a non-contact manner. The accuracy of the non-contact physiological signal monitoring system was analyzed. First, the working distance of the system was tested. Then, the algorithm of mining collective motion signal was classified, and the accuracy was 88%, which could be further improved in the system. In addition, the mean absolute error values of heart rate and respiratory rate were 0.8 beats/min and 3.5 beats/min, respectively, and the reliability of the system was verified by comparing the respiratory waveforms with the contact equipment at different distances. MDPI 2019-04-19 /pmc/articles/PMC6627890/ /pubmed/31010166 http://dx.doi.org/10.3390/bios9020058 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liang, Qiancheng Xu, Lisheng Bao, Nan Qi, Lin Shi, Jingjing Yang, Yicheng Yao, Yudong Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement |
title | Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement |
title_full | Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement |
title_fullStr | Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement |
title_full_unstemmed | Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement |
title_short | Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement |
title_sort | research on non-contact monitoring system for human physiological signal and body movement |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6627890/ https://www.ncbi.nlm.nih.gov/pubmed/31010166 http://dx.doi.org/10.3390/bios9020058 |
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