Pub Date : 2023-08-14DOI: 10.1109/JERM.2023.3298730
Marco Mercuri;Emilio Arnieri;Raffaele De Marco;Pierangelo Veltri;Felice Crupi;Luigi Boccia
The application of radar technology in indoor people monitoring has opened up new avenues, such as localization and tracking, vital signs monitoring, and fall detection. Nevertheless, one of the significant challenges facing radar systems is the issue of indoor multipath propagation, which results in radar ghosts that can diminish the detection accuracy or even compromise the monitoring process entirely. This study delves into the utilization of reconfigurable intelligent surfaces (RISs) in radar-based indoor people localization. Thanks to the use of RIS, targets can be tracked from multiple orientations, achieving a more precise estimation of the propagation channel and in turn mitigating the effects of indoor multipath propagation. As a result, the detection performance of the radar system can be improved without increasing the radar's complexity. Empirical evidence gathered from experiments conducted in a laboratory environment has demonstrated the feasibility of the proposed approach in accurately locating multiple subjects in a two-dimensional (2-D) space while being able to reject radar ghosts. Practical implications of this novel approach include the development of smart building systems, Internet of Things (IoT), telemedicine, Hospital 4.0, automated nurse call solutions, ambient assisted living, firefighter tracking, and security applications.
{"title":"Reconfigurable Intelligent Surface-Aided Indoor Radar Monitoring: A Feasibility Study","authors":"Marco Mercuri;Emilio Arnieri;Raffaele De Marco;Pierangelo Veltri;Felice Crupi;Luigi Boccia","doi":"10.1109/JERM.2023.3298730","DOIUrl":"10.1109/JERM.2023.3298730","url":null,"abstract":"The application of radar technology in indoor people monitoring has opened up new avenues, such as localization and tracking, vital signs monitoring, and fall detection. Nevertheless, one of the significant challenges facing radar systems is the issue of indoor multipath propagation, which results in radar ghosts that can diminish the detection accuracy or even compromise the monitoring process entirely. This study delves into the utilization of reconfigurable intelligent surfaces (RISs) in radar-based indoor people localization. Thanks to the use of RIS, targets can be tracked from multiple orientations, achieving a more precise estimation of the propagation channel and in turn mitigating the effects of indoor multipath propagation. As a result, the detection performance of the radar system can be improved without increasing the radar's complexity. Empirical evidence gathered from experiments conducted in a laboratory environment has demonstrated the feasibility of the proposed approach in accurately locating multiple subjects in a two-dimensional (2-D) space while being able to reject radar ghosts. Practical implications of this novel approach include the development of smart building systems, Internet of Things (IoT), telemedicine, Hospital 4.0, automated nurse call solutions, ambient assisted living, firefighter tracking, and security applications.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"7 4","pages":"354-364"},"PeriodicalIF":3.2,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136116504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-08DOI: 10.1109/JERM.2023.3299525
Francesco Lestini;Nicoletta Panunzio;Gaetano Marrocco;Cecilia Occhiuzzi
Hyperthermia is an anti-cancer treatment that exploits the interaction between high-power electromagnetic fields and restricted regions of human tissues releasing a great amount of power to locally increase tissues temperature. Due to the high power, dangerous hot-spots may occur on the skin so that continuous monitoring of superficial temperature distribution is required. Thermal Monitoring Sheets (TMSs), which are grids of several wired temperature sensors, are currently used in clinical practice; however, they have some limitations in terms of poor spatial resolution, thermal conduction errors, and complex application procedures. Epidermal electronics associated with passive Ultra High Frequency (UHF) Radio Frequency IDentification (RFID) sensing technology could represent an attractive alternative thanks to its wireless nature and limited invasiveness. In this framework, this article proposes an innovative TMS based on battery-less RFID sensors (R-TMS). It comprises a planar grid of circular loop antennas with temperature-sensing-oriented ICs that can sample skin temperature without interfering with hyperthermia treatment. The system proved capable of monitoring skin temperature via wireless data transmission with a higher spatial resolution that state-of-the-art devices. The physical rationale, the design, and the experimentation of the R-TMS are here presented to validate the proposed approach and evaluate its feasibility from the electromagnetic perspective.
{"title":"Epidermal RFID-Based Thermal Monitoring Sheet (R-TMS) for Microwave Hyperthermia","authors":"Francesco Lestini;Nicoletta Panunzio;Gaetano Marrocco;Cecilia Occhiuzzi","doi":"10.1109/JERM.2023.3299525","DOIUrl":"10.1109/JERM.2023.3299525","url":null,"abstract":"Hyperthermia is an anti-cancer treatment that exploits the interaction between high-power electromagnetic fields and restricted regions of human tissues releasing a great amount of power to locally increase tissues temperature. Due to the high power, dangerous hot-spots may occur on the skin so that continuous monitoring of superficial temperature distribution is required. Thermal Monitoring Sheets (TMSs), which are grids of several wired temperature sensors, are currently used in clinical practice; however, they have some limitations in terms of poor spatial resolution, thermal conduction errors, and complex application procedures. Epidermal electronics associated with passive Ultra High Frequency (UHF) Radio Frequency IDentification (RFID) sensing technology could represent an attractive alternative thanks to its wireless nature and limited invasiveness. In this framework, this article proposes an innovative TMS based on battery-less RFID sensors (R-TMS). It comprises a planar grid of circular loop antennas with temperature-sensing-oriented ICs that can sample skin temperature without interfering with hyperthermia treatment. The system proved capable of monitoring skin temperature via wireless data transmission with a higher spatial resolution that state-of-the-art devices. The physical rationale, the design, and the experimentation of the R-TMS are here presented to validate the proposed approach and evaluate its feasibility from the electromagnetic perspective.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"7 4","pages":"365-374"},"PeriodicalIF":3.2,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88397618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-28DOI: 10.1109/JERM.2023.3294707
Muhammad Solihin Zulkefli;Kai Zhang;Mariella Sarestoniemi;Sami Myllymäki;William G. Whittow;Sen Yan;Ping Jack Soh
An experimental wireless link and specific absorption rate (SAR) assessment is presented in this work. A compact planar inverted-F antenna (PIFA) is designed and evaluated for biotelemetry application as an antenna at 2.45 GHz band. The proposed antenna provided a satisfactory bandwidth per unit volume using a two-layered stacked structure consisting of a high-frequency laminate and a low loss ceramic layer. The antenna was first co-designed inside several different types of phantom boxes to optimize its performance, considering computational resources. Next, a semisolid intestinal phantom model used in simulations were chosen to be fabricated for experimental evaluations. Evaluation results indicated a satisfactory antenna's operation from 2.13 to 2.81 GHz (bandwidth of 27.8%), with realized gains of −26.49 dBi when implanted at 45 mm inside the phantom. Next, measurements were performed on the antenna's communication link with a wearable antenna to study the effects its depth (from 10 to 45mm), indicating transmission coefficients of between −40 and −60 dB at 2.45 GHz. Finally, its SAR levels are evaluated experimentally using a commercial measurement system when implanted within the human tissue. Results indicated satisfactory level of 0.685 W/kg (averaged over 10 g of tissues) and is suitable for biotelemetry application.
{"title":"Experimental Wireless Link and SAR Assessments of an Implantable PIFA for Biotelemetry in the 2.45 GHz Band","authors":"Muhammad Solihin Zulkefli;Kai Zhang;Mariella Sarestoniemi;Sami Myllymäki;William G. Whittow;Sen Yan;Ping Jack Soh","doi":"10.1109/JERM.2023.3294707","DOIUrl":"https://doi.org/10.1109/JERM.2023.3294707","url":null,"abstract":"An experimental wireless link and specific absorption rate (SAR) assessment is presented in this work. A compact planar inverted-F antenna (PIFA) is designed and evaluated for biotelemetry application as an antenna at 2.45 GHz band. The proposed antenna provided a satisfactory bandwidth per unit volume using a two-layered stacked structure consisting of a high-frequency laminate and a low loss ceramic layer. The antenna was first co-designed inside several different types of phantom boxes to optimize its performance, considering computational resources. Next, a semisolid intestinal phantom model used in simulations were chosen to be fabricated for experimental evaluations. Evaluation results indicated a satisfactory antenna's operation from 2.13 to 2.81 GHz (bandwidth of 27.8%), with realized gains of −26.49 dBi when implanted at 45 mm inside the phantom. Next, measurements were performed on the antenna's communication link with a wearable antenna to study the effects its depth (from 10 to 45mm), indicating transmission coefficients of between −40 and −60 dB at 2.45 GHz. Finally, its SAR levels are evaluated experimentally using a commercial measurement system when implanted within the human tissue. Results indicated satisfactory level of 0.685 W/kg (averaged over 10 g of tissues) and is suitable for biotelemetry application.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"7 3","pages":"281-289"},"PeriodicalIF":3.2,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50291935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article, an explainable deep learning scheme is proposed to tackle microwave imaging for the task of multiple object localisation. Deep learning has been involved in solving microwave imaging tasks due to its strong pattern recognition capabilities. However, the lack of explainability of the model's predictions makes it infeasible to deploy deep learning models in practical applications such as stroke detection and localisation as the model is a black box, the confidence of the output is unknown as they cannot be verified. This article aims to alleviate this concern by applying the gradient-weighted class activation map (Grad-CAM), an explainable artificial intelligence technique, together with the Delay-Multiply-And-Sum (DMAS) algorithm to spatially explain the deep learning model. The Grad-CAM method highlights the important parts of the input signal for decision making and the important parts are mapped to the image domain to provide a more intuitive understanding of the model. This article concludes that the deep learning model learns from reliable information and provides outputs which have a physical basis.
{"title":"An Explainable Deep Learning Method for Microwave Head Stroke Localization","authors":"Wei-chung Lai;Lei Guo;Konstanty Bialkowski;Alina Bialkowski","doi":"10.1109/JERM.2023.3287681","DOIUrl":"10.1109/JERM.2023.3287681","url":null,"abstract":"In this article, an explainable deep learning scheme is proposed to tackle microwave imaging for the task of multiple object localisation. Deep learning has been involved in solving microwave imaging tasks due to its strong pattern recognition capabilities. However, the lack of explainability of the model's predictions makes it infeasible to deploy deep learning models in practical applications such as stroke detection and localisation as the model is a black box, the confidence of the output is unknown as they cannot be verified. This article aims to alleviate this concern by applying the gradient-weighted class activation map (Grad-CAM), an explainable artificial intelligence technique, together with the Delay-Multiply-And-Sum (DMAS) algorithm to spatially explain the deep learning model. The Grad-CAM method highlights the important parts of the input signal for decision making and the important parts are mapped to the image domain to provide a more intuitive understanding of the model. This article concludes that the deep learning model learns from reliable information and provides outputs which have a physical basis.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"7 4","pages":"336-343"},"PeriodicalIF":3.2,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75084701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-06DOI: 10.1109/JERM.2023.3289767
Douglas J. Kurrant;Muhammad Omer;Elise C. Fear
The emergence and subsequent expansion of the field of medical microwave imaging has resulted in numerous approaches to image reconstruction. This includes microwave tomography, radar imaging, and more recently, multi-modality approaches. However, there is an absence of a standardized and widely accepted process that is proficient at extracting information from these images and employing this knowledge to conduct a thorough quantitative evaluation of images and regions within images. This shortcoming may interfere with a researcher's ability to make reliable and consistent inferences from experiments and to interpret results. Consequently, comparing the results of different research groups is difficult. This is becoming increasingly relevant due to the development of standardized test phantoms and the increase in clinical studies. To remedy this deficiency, an automated workflow has been developed with the objective to standardize the processing and analysis of images acquired from a range of modalities. Images are first segmented into regions dominated by a tissue type. Quantitative information extracted from these regions is used for analysis and by visualization tools for the qualitative interpretation of images. The effectiveness of the workflow is demonstrated with multiple examples that focus on quantifying changes to images due to enhancements of the reconstruction algorithm or perturbations of a parameter used by the reconstruction operator.
{"title":"Automated Workflow for Evaluating Microwave and Multi-Modality Breast Images","authors":"Douglas J. Kurrant;Muhammad Omer;Elise C. Fear","doi":"10.1109/JERM.2023.3289767","DOIUrl":"https://doi.org/10.1109/JERM.2023.3289767","url":null,"abstract":"The emergence and subsequent expansion of the field of medical microwave imaging has resulted in numerous approaches to image reconstruction. This includes microwave tomography, radar imaging, and more recently, multi-modality approaches. However, there is an absence of a standardized and widely accepted process that is proficient at extracting information from these images and employing this knowledge to conduct a thorough quantitative evaluation of images and regions within images. This shortcoming may interfere with a researcher's ability to make reliable and consistent inferences from experiments and to interpret results. Consequently, comparing the results of different research groups is difficult. This is becoming increasingly relevant due to the development of standardized test phantoms and the increase in clinical studies. To remedy this deficiency, an automated workflow has been developed with the objective to standardize the processing and analysis of images acquired from a range of modalities. Images are first segmented into regions dominated by a tissue type. Quantitative information extracted from these regions is used for analysis and by visualization tools for the qualitative interpretation of images. The effectiveness of the workflow is demonstrated with multiple examples that focus on quantifying changes to images due to enhancements of the reconstruction algorithm or perturbations of a parameter used by the reconstruction operator.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"7 3","pages":"290-300"},"PeriodicalIF":3.2,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50291936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/JERM.2023.3288741
Matteo Bruno Lodi;Nicola Curreli;Chiara Dachena;Alessandro Fedeli;Rosa Scapaticci;Andrea Randazzo;Matteo Pastorino;Alessandro Fanti
Magnetic biomaterials are multifunctional tools currently under investigation as theranostic platforms for biomedical applications. They can be implanted in bone tissue after bone cancer resection to perform local interstitial hyperthermia treatment. Given the requirements of high quality treatment, the hyperthermia therapy should be performed monitoring the system temperature, to avoid hot spots and control the treatment outcome. It is known that the magnetic properties of such implants vary with temperature. It is hypotesized that the treatment dynamic could be monitored using a microwave monitoring system. The variation of the electromagnetic properties of the biological tissues and the magnetic implant during the therapy would result in a different propagation of the microwave signal. This work investigates the feasibility of using microwaves to non-invasively monitor hyperthermia treatments with a simplified monodimensional propagation model. The forward problem is solved to identify the working frequencies, the matching medium properties and study several candidate materials. By using the numerical solutions from nonlinear and multiphysics simulations of the bone tumor hyperthermia treatment using magnetic scaffolds, the microwave signal propagation dynamic is studied. From our feasibility analysis, we found that it is possible to correlate the average tumor temperature with significant ( $sim$