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Biomedical Microwave Sensors for Point-of-Care Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (20 October 2022) | Viewed by 19005

Special Issue Editors


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Guest Editor
Department of Electrical Engineering, Division of Solid State Electronics, Head of The Microwaves in Medical Engineering Group, Angstrom Laboratory, Uppsala University, Elektroteknik, Box 65, 751 03 Uppsala, Sweden
Interests: automation; robotics; IoT; bio-mechatronics; cyber–physical systems; intra-body communication; sensing; prosthetics; electronics; industry; materials
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Guest Editor
The Microwave Imaging and Spectroscopy (MIS) group, Thayer School of Engineering at Dartmouth, 14 Engineering Drive Hanover, NH 03755, USA
Interests: dielectric properties of tissue, microwave electronics; microwave imaging spectroscopy; non-linear image reconstruction techniques; therapy monitoring

Special Issue Information

Dear Colleagues,

Point of care sensors have huge potential in present and future clinical and home care scenarios. Microwave sensors are a very important technology that can be used for early screening and diagnosis of various diseases, which will help avoid delays in the administration of treatment. Due to their safe non-ionizing characteristics and tissue discernability, microwave sensors are a very good alternative to conventional X-Ray and electrical impedance-based sensing. This Special Issue will also focus on various clinical needs that microwave sensors could address and, thus, attract more research in the point of care area.

Dr. Robin Augustine
Prof. Dr. Paul M. Meaney
Guest Editors

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Keywords

  • Reflection-based sensing
  • Transmission-based sensing
  • Physiological monitoring
  • Bone mineral density
  • Time-domain analysis
  • Nearfield sensing
  • Dielectric properties
  • In-Vivo measurements
  • Dielectric Characterization
  • Rehabilitation
  • Trauma care
  • Ultra-wideband sensing
  • Narrowband sensing

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Published Papers (6 papers)

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Research

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16 pages, 3621 KiB  
Article
Feasibility Evaluation of Metamaterial Microwave Sensors for Non-Invasive Blood Glucose Monitoring
by Lukas Malena, Ondrej Fiser, Paul R. Stauffer, Tomas Drizdal, Jan Vrba and David Vrba
Sensors 2021, 21(20), 6871; https://doi.org/10.3390/s21206871 - 16 Oct 2021
Cited by 15 | Viewed by 3746
Abstract
The use of microwave technology is currently under investigation for non-invasive estimation of glycemia in patients with diabetes. Due to their construction, metamaterial (MTM)-based sensors have the potential to provide higher sensitivity of the phase shift of the S21 parameter ( [...] Read more.
The use of microwave technology is currently under investigation for non-invasive estimation of glycemia in patients with diabetes. Due to their construction, metamaterial (MTM)-based sensors have the potential to provide higher sensitivity of the phase shift of the S21 parameter (S21) to changes in glucose concentration compared to standard microstrip transmission line (MSTL)-based sensors. In this study, a MSTL sensor and three MTM sensors with 5, 7, and 9 MTM unit cells are exposed to liquid phantoms with different dielectric properties mimicking a change in blood glucose concentration from 0 to 14 mmol/L. Numerical models were created for the individual experiments, and the calculated S-parameters show good agreement with experimental results, expressed by the maximum relative error of 8.89% and 0.96% at a frequency of 1.99 GHz for MSTL and MTM sensor with nine unit cells, respectively. MTM sensors with an increasing number of cells show higher sensitivity of 0.62° per mmol/L and unit cell to blood glucose concentration as measured by changes in S21. In accordance with the numerical simulations, the MTM sensor with nine unit cells showed the highest sensitivity of the sensors proposed by us, with an average of 3.66° per mmol/L at a frequency of 1.99 GHz, compared to only 0.48° per mmol/L for the MSTL sensor. The multi-cell MTM sensor has the potential to proceed with evaluation of human blood samples. Full article
(This article belongs to the Special Issue Biomedical Microwave Sensors for Point-of-Care Applications)
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24 pages, 9610 KiB  
Article
Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors
by Somayyeh Chamaani, Alireza Akbarpour, Marko Helbig and Jürgen Sachs
Sensors 2021, 21(17), 5735; https://doi.org/10.3390/s21175735 - 26 Aug 2021
Cited by 6 | Viewed by 2739
Abstract
Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an [...] Read more.
Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an efficient method with good frequency resolution, is applied to back-reflected microwave signals to extract vital signs. It is shown that decomposing of the signal to its damping exponentials fulfilled by MPM gives the opportunity to separate signals, e.g., breathing and heartbeat, with high precision. A publicly online dataset (GUARDIAN), obtained by a continuous wave microwave sensor, is applied to evaluate the performance of MPM. Two methods of bandpass filtering (BPF) and variational mode decomposition (VMD) are also implemented. In addition to the GUARDIAN dataset, these methods are also applied to signals acquired by an ultra-wideband (UWB) sensor. It is concluded that when the vital sign is sufficiently strong and pure, all methods, e.g., MPM, VMD, and BPF, are appropriate for vital sign monitoring. However, in noisy cases, MPM has better performance. Therefore, for non-contact microwave vital sign monitoring, which is usually subject to noisy situations, MPM is a powerful method. Full article
(This article belongs to the Special Issue Biomedical Microwave Sensors for Point-of-Care Applications)
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18 pages, 5916 KiB  
Article
High-Precision Temperature Inversion Algorithm for Correlative Microwave Radiometer
by Jie Liu, Kai Zhang, Jingyan Ma, Qiang Wu, Zhenlin Sun, Hao Wang and Youquan Zhang
Sensors 2021, 21(16), 5336; https://doi.org/10.3390/s21165336 - 7 Aug 2021
Cited by 3 | Viewed by 2152
Abstract
In order to achieve high precision from non-contact temperature measurement, the hardware structure of a broadband correlative microwave radiometer, calibration algorithm, and temperature inversion algorithm are innovatively designed in this paper. The correlative radiometer is much more sensitive than a full power radiometer, [...] Read more.
In order to achieve high precision from non-contact temperature measurement, the hardware structure of a broadband correlative microwave radiometer, calibration algorithm, and temperature inversion algorithm are innovatively designed in this paper. The correlative radiometer is much more sensitive than a full power radiometer, but its accuracy is challenging to improve due to relatively large phase error. In this study, an error correction algorithm is designed, which reduces the phase error from 69.08° to 4.02°. Based on integral calibration on the microwave temperature measuring system with a known radiation source, the linear relationship between the output voltage and the brightness temperature of the object is obtained. Since the metal aluminum plate, antenna, and transmission line will have a non-linear influence on the receiver system, their temperature characteristics and the brightness temperature of the object are used as the inputs of the neural network to obtain a higher accuracy of inversion temperature. The temperature prediction mean square error of a back propagation (BP) neural network is 0.629 °C, and its maximum error is 3.351 °C. This paper innovatively proposed the high-precision PSO-LM-BP temperature inversion algorithm. According to the global search ability of the particle swarm optimization (PSO) algorithm, the initial weight of the network can be determined effectively, and the Levenberg–Marquardt (LM) algorithm makes use of the second derivative information, which has higher convergence accuracy and iteration efficiency. The mean square error of the PSO-LM-BP temperature inversion algorithm is 0.002 °C, and its maximum error is 0.209 °C. Full article
(This article belongs to the Special Issue Biomedical Microwave Sensors for Point-of-Care Applications)
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20 pages, 7881 KiB  
Article
Design of Metamaterial Based Efficient Wireless Power Transfer System Utilizing Antenna Topology for Wearable Devices
by Tarakeswar Shaw, Gopinath Samanta, Debasis Mitra, Bappaditya Mandal and Robin Augustine
Sensors 2021, 21(10), 3448; https://doi.org/10.3390/s21103448 - 15 May 2021
Cited by 20 | Viewed by 4479
Abstract
In this article, the design of an efficient wireless power transfer (WPT) system using antenna-based topology for the applications in wearable devices is presented. To implement the wearable WPT system, a simple circular patch antenna is initially designed on a flexible felt substrate [...] Read more.
In this article, the design of an efficient wireless power transfer (WPT) system using antenna-based topology for the applications in wearable devices is presented. To implement the wearable WPT system, a simple circular patch antenna is initially designed on a flexible felt substrate by placing over a three-layer human tissue model to utilize as a receiving element. Meanwhile, a high gain circular patch antenna is also designed in the air environment to use as a transmitter for designing the wearable WPT link. The proposed WPT system is built to operate at the industrial, scientific and medical (ISM) band of 2.40–2.48 GHz. In addition, to improve the power transfer efficiency (PTE) of the system, a metamaterial (MTM) slab built with an array combination of 3 × 3 unit cells has been employed. Further, the performance analysis of the MTM integrated system is performed on the different portions of the human body like hand, head and torso model to present the versatile applicability of the system. Moreover, analysis of the specific absorption rate (SAR) has been performed in different wearable scenarios to show the effect on the human body under the standard recommended limits. Regarding the practical application issues, the performance stability analysis of the proposed system due to the misalignment and flexibility of the Rx antenna is executed. Finally, the prototypes are fabricated and experimental validation is performed on several realistic wearable platforms like three-layer pork tissue slab, human hand, head and body. The simulated and measured result confirms that by using the MTM slab, a significant amount of the PTE improvement is obtained from the proposed system. Full article
(This article belongs to the Special Issue Biomedical Microwave Sensors for Point-of-Care Applications)
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10 pages, 3617 KiB  
Communication
Use of the Composite Properties of a Microwave Resonator to Enhance the Sensitivity of a Honey Moisture Sensor
by José R. Reyes-Ayona, Eloisa Gallegos-Arellano and Juan M. Sierra-Hernández
Sensors 2021, 21(7), 2549; https://doi.org/10.3390/s21072549 - 6 Apr 2021
Cited by 1 | Viewed by 2174
Abstract
A moisture sensor based on a composite resonator is used to measure different honey samples, which include imitation honey. The sensor changes its frequency response in accordance with the dielectric permittivity that it detects in the measured samples. Although reflectometry sensors have been [...] Read more.
A moisture sensor based on a composite resonator is used to measure different honey samples, which include imitation honey. The sensor changes its frequency response in accordance with the dielectric permittivity that it detects in the measured samples. Although reflectometry sensors have been used to measure the percentage of moisture in honey for almost a century, counterfeiters have achieved that their apocryphal product is capable of deceiving these kinds of sensors. Metamaterial features of the composite resonators are expected to improve their response when detecting lossy samples such as organic samples. It is also sought that these sensors manage to detect small differences not only in the real parts of the dielectric permitivities of samples but also in their imaginary parts, and, thus, the sensors are able to discern between real honey and slightly altered honey. Effectively, not only was it possible to improve the response of the sensors by using lossy samples but it was also possible to identify counterfeit honey. Full article
(This article belongs to the Special Issue Biomedical Microwave Sensors for Point-of-Care Applications)
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Other

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16 pages, 10315 KiB  
Letter
Expansion of the Nodal-Adjoint Method for Simple and Efficient Computation of the 2D Tomographic Imaging Jacobian Matrix
by Samar Hosseinzadegan, Andreas Fhager, Mikael Persson, Shireen Geimer and Paul Meaney
Sensors 2021, 21(3), 729; https://doi.org/10.3390/s21030729 - 22 Jan 2021
Cited by 5 | Viewed by 2328
Abstract
This paper focuses on the construction of the Jacobian matrix required in tomographic reconstruction algorithms. In microwave tomography, computing the forward solutions during the iterative reconstruction process impacts the accuracy and computational efficiency. Towards this end, we have applied the discrete dipole approximation [...] Read more.
This paper focuses on the construction of the Jacobian matrix required in tomographic reconstruction algorithms. In microwave tomography, computing the forward solutions during the iterative reconstruction process impacts the accuracy and computational efficiency. Towards this end, we have applied the discrete dipole approximation for the forward solutions with significant time savings. However, while we have discovered that the imaging problem configuration can dramatically impact the computation time required for the forward solver, it can be equally beneficial in constructing the Jacobian matrix calculated in iterative image reconstruction algorithms. Key to this implementation, we propose to use the same simulation grid for both the forward and imaging domain discretizations for the discrete dipole approximation solutions and report in detail the theoretical aspects for this localization. In this way, the computational cost of the nodal adjoint method decreases by several orders of magnitude. Our investigations show that this expansion is a significant enhancement compared to previous implementations and results in a rapid calculation of the Jacobian matrix with a high level of accuracy. The discrete dipole approximation and the newly efficient Jacobian matrices are effectively implemented to produce quantitative images of the simplified breast phantom from the microwave imaging system. Full article
(This article belongs to the Special Issue Biomedical Microwave Sensors for Point-of-Care Applications)
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