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Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement

1
School of Sino-Dutch Biomedical and Information Engineering, Northeastern University, Shenyang 110819, China
2
Neusoft Research of Intelligent Healthcare Technology, Co. Ltd., Shenyang 110167, China
*
Author to whom correspondence should be addressed.
Biosensors 2019, 9(2), 58; https://doi.org/10.3390/bios9020058
Received: 28 February 2019 / Revised: 12 April 2019 / Accepted: 16 April 2019 / Published: 19 April 2019
(This article belongs to the Special Issue In Vivo Physiological Monitoring)
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Abstract

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. View Full-Text
Keywords: doppler bio-radar; non-contact monitoring system; body movement classify; physiological signals doppler bio-radar; non-contact monitoring system; body movement classify; physiological signals
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MDPI and ACS Style

Liang, Q.; Xu, L.; Bao, N.; Qi, L.; Shi, J.; Yang, Y.; Yao, Y. Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement. Biosensors 2019, 9, 58.

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