Design and Implementation of a Novel Interferometric Microwave Radiometer for Human Body Temperature Measurement

In this paper, the key technology of interferometric microwave thermometer is studied, the research can be applied to the temperature measurement of human body and subcutaneous tissue. This paper proposes a hardware architecture of interferometric microwave thermometer with 2 GHz bandwidth, in which the phase shifter is used to correct phase error and the quadrature demodulator is used to realize autocorrelation detection function. The results show that when input power is 7 dBm, the detection sensitivity can reach 176.54 mV/dBm and the temperature resolution of the microwave radiometer can reach 0.4 K. Correction algorithm is designed to improve the accuracy of temperature measurement. After correction, the phase error is reduced from 40° to 1.4° and when temperature changes 0.1 °C, the voltage value changes obviously. Step-by-step calibration and overall calibration are used to calibrate the device. Inversion algorithm can determine the relationship between physical temperature and output voltage. The mean square error of water temperature inversion by multiple linear regression algorithm is 0.607 and that of BP neural network algorithm is 0.334. The inversion accuracy can be improved by reducing the temperature range. Our work provides a promising realization of accurate, rapid and non-contact detection device of human body temperature.

[2]  T. Weller,et al.  A tunable Cavity Backed Slot Antenna (CBSA) for close proximity biomedical sensing applications , 2009, 2009 IEEE International Conference on Microwaves, Communications, Antennas and Electronics Systems.

[3]  Chao Wang,et al.  A 3.5-8 GHz Analog Complex Cross-Correlator for Interferometric Passive Millimeter-Wave Security Imaging Systems , 2018, 2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama).

[4]  Jinho Jeong,et al.  Total Power Radiometer for Medical Sensor Applications Using Matched and Mismatched Noise Sources , 2017, Sensors.

[5]  T. M. Weller,et al.  Towards Core Body Temperature Measurement via Close Proximity Radiometric Sensing , 2012, IEEE Sensors Journal.

[6]  Panagiotis I. Charamis,et al.  Development of the RF Front-end of a Multi-Channel Microwave Radiometer for Internal Body Temperature Measurements , 2015 .

[7]  T. Weller,et al.  A total power radiometer (TPR) and measurement test bed for non-contact biomedical sensing applications , 2009, 2009 IEEE 10th Annual Wireless and Microwave Technology Conference.

[8]  Zoya Popovic,et al.  Toward wearable wireless thermometers for internal body temperature measurements , 2014, IEEE Communications Magazine.

[9]  Liang Weihong,et al.  Vegetable Price Prediction Based on PSO-BP Neural Network , 2015, 2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA).

[10]  Quenton Bonds.  A microwave radiometer for close proximity core body temperature monitoring: Design, development, and experimentation , 2010 .

[11]  Robert Scheeler.  A Microwave Radiometer for Internal Body Temperature Measurement , 2013 .

[12]  Xin Xin,et al.  Quadrature Errors and DC Offsets Calibration of Analog Complex Cross-Correlator for Interferometric Passive Millimeter-Wave Imaging Applications , 2018, Sensors.

[13]  A. N. Reznik,et al.  Thermal Near Field and the Possibilities of Its Use for In-Depth Temperature Diagnostics of Media , 2002 .

[14]  Chao Wang,et al.  A Compact Analog Complex Cross-Correlator for Passive Millimeter-Wave Imager , 2017, IEEE Transactions on Instrumentation and Measurement.

[15]  Jungang Miao,et al.  Design and implementation of an analog complex correlator for passive millimeter wave imaging system , 2016, 2016 13th International Bhurban Conference on Applied Sciences and Technology (IBCAST).

[16]  Jinho Jeong,et al.  Design of Cavity-Backed Bow-Tie Antenna with Matching Layer for Human Body Application , 2019, Sensors.

[17]  Anubhav,et al.  GA and PSO hybrid algorithm for ANN training with application in Medical Diagnosis , 2019, 2019 Third International Conference on Intelligent Computing in Data Sciences (ICDS).

[18]  C. He,et al.  Prediction of the tensile force applied on surface-hardened steel rods based on a CDIF and PSO-optimized neural network , 2018, Measurement Science and Technology.