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1.
Med Sci Monit ; 29: e939949, 2023 May 15.
Article En | MEDLINE | ID: mdl-37183387

BACKGROUND Self-injection locking (SIL) radar uses continuous-wave radar and an injection-locked oscillator-based frequency discriminator that receives and demodulates radar signals remotely to monitor vital signs. This study aimed to compare SIL radar with traditional electrocardiogram (ECG) measurements to monitor respiratory rate (RR) and heartbeat rate (HR) during the COVID-19 pandemic at a single hospital in Taiwan. MATERIAL AND METHODS We recruited 31 hospital staff members (16 males and 15 females) for respiratory rates (RR) and heartbeat rates (HR) detection. Data acquisition with the SIL radar and traditional ECG was performed simultaneously, and the accuracy of the measurements was evaluated using Bland-Altman analysis. RESULTS To analyze the results, participates were divided into 2 groups (individual subject and multiple subjects) by gender (male and female), or 4 groups (underweight, normal weight, overweight, and obesity) by body mass index (BMI). The results were analyzed using mean bias errors (MBE) and limits of agreement (LOA) with a 95% confidence interval. Bland-Altman plots were utilized to illustrate the difference between the SIL radar and ECG monitor. In all BMI groups, results of RR were more accurate than HR, with a smaller MBE. Furthermore, RR and HR measurements of the male groups were more accurate than those of the female groups. CONCLUSIONS We demonstrated that non-contact SIL radar could be used to accurately measure HR and RR for hospital healthcare during the COVID-19 pandemic.


COVID-19 , Signal Processing, Computer-Assisted , Male , Humans , Female , Radar , Taiwan/epidemiology , Pandemics , Vital Signs , Heart Rate , Respiratory Rate , Hospitals , Algorithms , Monitoring, Physiologic/methods
2.
IEEE Trans Biomed Circuits Syst ; 16(1): 153-167, 2022 02.
Article En | MEDLINE | ID: mdl-35104225

During the global epidemic, non-contact methods for monitoring the vital signs of several people have become particularly important. Advanced signal processing techniques have recently been demonstrated to separate and track the vital signs of multiple people. In this paper, we further develop the multi-person vital signs identification (VSign-ID) system to make non-contact detection available in public places. VSign-ID not only extracts multi-person vital signs but also states from whom these vital signs are collected. We utilize multiple doppler radars to expand the effective range of the measurement area and propose a space and time matching mechanism for vital signs identification. We use a thermal camera to detect the number of people and their movements. VSign-ID efficiently coordinates these two types of sensors (i.e., the doppler radars and the thermal camera) to track and identify the respiration rates and heartbeat rates of multiple people. A series of experiments and simulations are conducted to measure the efficiency of VSign-ID. In the case of five people sitting closely, the estimation errors for respiration and heartbeat rates are -4.85 dB and -2.36 dB lower than the standard resolution of the system, respectively, despite using only two independent radars.


Radar , Vital Signs , Algorithms , Heart Rate , Humans , Monitoring, Physiologic/methods , Respiratory Rate , Signal Processing, Computer-Assisted
3.
Sensors (Basel) ; 21(7)2021 Apr 01.
Article En | MEDLINE | ID: mdl-33915906

To achieve a sensitive and accurate method in body temperature measurement of cattle, this study explores the uses of infrared thermography (IRT), an anemometer, and a humiture meter as a multiple sensors architecture. The influence of environmental factors on IRT, such as wind speed, ambient temperature, and humidity, was considered. The proposed signal processes removed the IRT frames affected by air flow, and also eliminated the IRT frames affected by random body movement of cattle using the frame difference method. In addition, the proposed calibration method reduced the impact of ambient temperature and humidity on IRT results, thereby increasing the accuracy of IRT temperature. The difference of mean value and standard deviation value between recorded rectal reference temperature and IRT temperature were 0.04 °C and 0.10 °C, respectively, and the proposed system substantially improved the measurement consistency of the IRT temperature and reference on cattle body temperature. Moreover, with a relatively small IRT image sensor, the combination of multiple sensors architecture and proper data processing still achieved good temperature accuracy. The result of the root-mean-square error (RMSE) was 0.74 °C, which is quite close to the accurate result of the IRT measurement.


Body Temperature , Thermography , Animals , Cattle , Humidity , Infrared Rays , Temperature , Wind
4.
IEEE Trans Biomed Circuits Syst ; 14(6): 1346-1361, 2020 12.
Article En | MEDLINE | ID: mdl-33031035

Noninvasive monitoring is an important Internet-of-Things application, which is made possible with the advances in radio-frequency based detection technologies. Existing techniques however rely on the use of antenna array and/or frequency modulated continuous wave radar to detect vital signs of multiple adjacent objects. Antenna size and limited bandwidth greatly limit the applicability. In this paper, we propose our system termed 'DeepMining' which is a single-antenna, narrowband Doppler radar system that can simultaneously track the respiration and heartbeat rates of multiple persons with high accuracy. DeepMining uses a number of signal observations over a period of time as input and returns the trajectory of the respiration and heartbeat rates of each person. The extraction is based on frequency separation algorithms using successive signal cancellation. The proposed system is implemented using the self-injection locking radar architecture and tested in a series of experiments, showing accuracies of 90% and 85% for two and three objects, respectively, even for closely located persons.


Algorithms , Monitoring, Physiologic/instrumentation , Ultrasonography, Doppler/instrumentation , Wireless Technology/instrumentation , Data Mining , Equipment Design , Humans , Vital Signs
5.
Biosensors (Basel) ; 6(4)2016 Oct 26.
Article En | MEDLINE | ID: mdl-27792176

To achieve sensitivity, comfort, and durability in vital sign monitoring, this study explores the use of radar technologies in wearable devices. The study first detected the respiratory rates and heart rates of a subject at a one-meter distance using a self-injection-locked (SIL) radar and a conventional continuous-wave (CW) radar to compare the sensitivity versus power consumption between the two radars. Then, a pulse rate monitor was constructed based on a bistatic SIL radar architecture. This monitor uses an active antenna that is composed of a SIL oscillator (SILO) and a patch antenna. When attached to a band worn on the subject's wrist, the active antenna can monitor the pulse on the subject's wrist by modulating the SILO with the associated Doppler signal. Subsequently, the SILO's output signal is received and demodulated by a remote frequency discriminator to obtain the pulse rate information.


Monitoring, Physiologic/methods , Pulse , Radar , Wrist , Heart Rate , Humans , Vital Signs
6.
IEEE Trans Biomed Eng ; 62(12): 2931-40, 2015 Dec.
Article En | MEDLINE | ID: mdl-26168431

This paper presents wearable health monitors that are based on continuous-wave Doppler radar technology. To achieve low complexity, low power consumption, and simultaneous wireless transmission of Doppler information, the radar architecture is bistatic with a self-injection-locked oscillator (SILO) tag and an injection-locked oscillator (ILO)-based frequency demodulator. In experiments with a prototype that was operated in the medical body area network and the industrial scientific and medical bands from 2.36 to 2.484 GHz, the SILO tag is attached to the chest of a subject to transform the movement of the chest due to cardiopulmonary activity and body exercise into a transmitted frequency-modulated wave. The tag consumes a very low power of 4.4 mW. The ILO-based frequency demodulator, located 30 cm from the subject, receives and processes this wave to yield the waveform that is associated with the movement of the chest. Following further digital signal processing, the cardiopulmonary activity and body exercise are displayed as time-frequency spectrograms. Promisingly, the experimental results that are presented in this paper reveal that the proposed health monitor has high potential to integrate a cardiopulmonary sensor, a pedometer, and a wireless transmission device on a single radar platform.


Monitoring, Ambulatory/instrumentation , Radar/instrumentation , Signal Processing, Computer-Assisted/instrumentation , Heart Rate/physiology , Humans , Monitoring, Ambulatory/methods , Respiration , Walking/physiology
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