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Abstract This article introduces an innovative approach for creating a circular polarization (CP) antenna-based rotation-insensitive implantable wireless power transfer (WPT) system for medical devices. The system is constructed to work in the industrial, scientific, and medical (ISM) frequency band of 902–928 MHz. Initially, a flexible, wide-band, and bio-compatible open-ended CP slot antenna is designed within a single-layer human skin tissue model to serve as the receiving (Rx) element. To form the implantable WPT link, a circular patch antenna is also constructed in the free-space to use as a transmitting (Tx) source. Further, a new metamaterial-polarization converter (MTM-PC) structure is developed and incorporated into the proposed system to enhance the power transfer efficiency (PTE). Furthermore, the rotational phenomenon of the Rx implant has been studied to show how the rotation affects the system’s performance. Moreover, a numerical analysis of the specific absorption rate (SAR) is conducted to confirm compliance with safety regulations and prioritize human safety from electromagnetic exposure. Finally, to validate the introduced concept, prototypes of the different elements of the proposed WPT system were fabricated and tested using skin-mimicking gel and porcine tissue. The measured results confirm the feasibility of the introduced approach, exhibiting improved efficiency due to use of the MTM-PC. The amplitude of the transmission coefficient ( $$|S_{21}|$$ | S 21 | ) has improved by 6.94 dB in the simulation, whereas the enhancement of 7.04 dB and 6.76 dB is obtained from the experimental study due to the integration of MTM-PC. As a result, the PTE of the proposed MTM-PC integrated implantable WPT system is increased significantly compared to the system without MTM-PC.

Brain hemorrhages have become increasingly common and can be fatal if left untreated. Current methods for monitoring the progression of the disorder that rely on MRI and PET scans are inconvenient and costly for patients. This has spurred research toward portable and cost-effective techniques for predicting the current stage and malignancy of the hemorrhages. In this study, simulated S-parameter data obtained from a two-antenna system placed over the head is used in conjunction with machine learning to detect the dielectric changes in the brain caused by hemorrhage non-invasively. Several machine learning classifiers are used to analyze the data, and their performance metrics are compared to determine the optimal classifier for this case. The study revealed that Decision Tree, KNN, and Random Forest classifiers are better than SVM and MLP classifiers in terms of accuracy, precision, and recall in predicting Brain hemorrhage at the most probable locations. Contrary to conventional microwave imaging systems requiring several antennas for brain hemorrhage detection, this study demonstrates that integrating machine learning with microwave sensors enables accurate solutions with a reduced antenna count. The results present a transformative strategy for monitoring systems in clinics, where a simple, safe, and low-cost microwave antenna-based system can be intelligently integrated with machine learning to diagnose the presence of Brain hemorrhage.

In this work, a customized portable semi-shielded chamber for torso phantoms to evaluate fat-intrabody communication (Fat-IBC) is presented. Fat-IBC is a technology where human fat tissue is used for microwave communication with intrabody medical devices. The potential clinical applications are vast including central nervous system (brain and spine) communication, cardiovascular disease monitoring and metabolic disorder control. However, validating this technology needs assurance that the signal leakage through undesired paths, particularly surface waves and reflections, does not occur. To solve this issue, an effective technique involving a modified design of a semi-shielded chamber is presented. The cross-section of the torso phantoms is about 25 cm $\times35$ cm and the height about 20 cm. As specified by ISO 3745:2012, the maximum object volume that can be measured in a chamber is 5% of the chamber’s internal net volume. Therefore, the dimensions of the semi-shielded chamber was set to 100 cm $\times60$ cm $\times60$ cm. The semi-shielded chamber was constructed out of a wooden crate, covered on the inside with microwave absorbers and with thin aluminum sheets on the outside. The experimental evaluation of the semi-shielded chamber was validated according to standards such as EN 50147-1:1996, IEC 61000-4-3:2020, and IEC CISPR 16-1-4:2019. The torso phantom was positioned at the center of the chamber, with a separation wall to ensure signal transmission solely through the phantoms interior and not its surface or chamber walls. The separation wall can be modified either to be conformal to the phantom sample or serve as a solid partition dividing the chamber into two separate volumes for performance measurement. The separation wall was found to have a shielding attenuation of 30 dB to 60 dB for frequencies between 0.7 GHz and 18 GHz, respectively, while the corresponding values for the external walls were found to be 45 dB to 70 dB. The semi-shielded chamber realized in this work is useful for Fat-IBC technology, brain-computer interface, brain-machine interface, body area networks (BANs), and related applications.

The dielectric properties of skin tissues in relation to different degrees of burn are a necessary prerequisite for designing non-invasive microwave sensing modalities. Due to the difficulties in obtaining human tissue samples, such databases are largely unavailable. To bridge the knowledge gap in this field, we attempt to create a dielectric database of various burn-degree skin samples and their statistical analysis in this work. This research is part of the European “Senseburn” project, which aims to create a non-invasive diagnostic tool that can measure the severity and depth of burns on humans in a clinical setting. In this work, several ex-vivo burnt samples were collected from the Uppsala University Hospital (Akademiska sjukhuset, Sweden). Out of that, eight samples with different degrees of burns in various human body locations were selected for the analysis. The dielectric characterization of the categorized samples was done using an Keysight N1501A dielectric open-end co-axial probe Kit. The dielectric characterization was made from 500 MHz to 10 GHz with 1001 points. The measurement was made systematically, and the clinician feedback forms were gathered and analyzed throughout the process. The measurement data followed the FASTCLUS procedure, which was initially analyzed using density plot, convergence, and cubic clustering criteria. For the statistical analysis, 11 frequency points were considered for eight samples. The results of the fundamental statistical analysis using the FASTCLUS procedure resulted in 88 data sets. Later, data sets were analyzed in sample-wise clusters. Every sample was made with two clusters, i.e., cluster 1, which consisted of healthy sectors, and cluster 2, which consisted of burnt sectors. We made the linear approximations for the sample-wise clusters and found the constant real permittivity difference. Furthermore, we found a pattern in the constant real permittivity differences of every sample that is proportional to the burn degrees. This information is needed in order to identify optimization parameters, i.e., the sensitivity with respect to dielectric difference for various burn degrees. For this purpose, extensive measurement campaigns across the microwave frequency band from 500 MHz – 10 GHz were conducted. Based on the analysis of dielectric data, each skin region of interest (ROI) has its own dielectric properties. Additionally, we developed a proof of concept non-invasive flexible microwave sensor based on the dielectric database collected from burnt ex-vivo human tissue samples. In this way, we could distinguish between phantoms with different dielectric properties in the burned human tissue sample range.

In this paper, a conformal absorber metasurface has been designed and used for reducing the specific absorption rate (SAR) of an implantable antenna. SAR reduction of implantable antennas is one of the significant design aspects to be considered for their use in modern-day healthcare applications. The introduction of the absorber metasurface restricts the back radiation of the antenna to control the SAR value. This technique decreases the maximum SAR value by 24% and also reduces the average SAR distribution significantly without affecting the desired antenna gain. A reduction in SAR value indicates the decrease in radiation absorption by human tissue, and thus, decreases the possibility of health hazards due to EM radiation. Later, this antenna-absorber system is designed as a capsule module for increased mobility and less-invasiveness. The redundancy of invasive surgery increases acceptance of the capsule module designs of implantable antennas and devices for various biomedical usages. In vitro testing of the fabricated prototype has been carried out inside a multi-layer porcine slab to verify the effectiveness of this unique SAR reduction technique.

The European “Senseburn” project aims to develop a smart, portable, non-invasive microwave early effective diagnostic tool to assess the depth(d) and degree of burn. The objective of the work is to design and develop a convenient non-invasive microwave sensor for the analysis of the burn degree on burnt human skin. The flexible and biocompatible microwave sensor is developed using a magnetically coupled loop probe with a spiral resonator (SR). The sensor is realized with precise knowledge of the lumped element characteristics (resistor (R), an inductor (L), and a capacitor (C) RLC parameters). The estimated electrical equivalent circuit technique relies on a rigorous method enabling a comprehensive characterization of the sensor (loop probe and SR). The microwave resonator sensor with high quality factor (Q) is simulated using a CST studio suite, AWR microwave office, and fabricated on the RO 3003 substrate with a standard thickness of 0.13 mm. The sensor is prepared based on the change in dielectric property variation in the burnt skin. The sensor can detect a range of permittivity variations (εr 3–38). The sensor is showing a good response in changing resonance frequency between 1.5 and 1.71 GHz for (εr 3 to 38). The sensor is encapsulated with PDMS for the biocompatible property. The dimension of the sensor element is length (L) = 39 mm, width (W) = 34 mm, and thickness (T) = 1.4 mm. The software algorithm is prepared to automate the process of burn analysis. The proposed electromagnetic (EM) resonator based sensor provides a non-invasive technique to assess burn degree by monitoring the changes in resonance frequency. Most of the results are based on numerical simulation. We propose the unique circuit set up and the sensor device based on the information generated from the simulation in this article. The clinical validation of the sensor will be in our future work, where we will understand closely the practical functioning of the sensor based on burn degrees. The senseburn system is designed to support doctors to gather vital info of the injuries wirelessly and hence provide efficient treatment for burn victims, thus saving lives.

Of all the skin cancer that is prevalent, melanoma has the highest mortality rates. Melanoma becomes life threatening when it penetrates deep into the dermis layer unless detected at an early stage, it becomes fatal since it has a tendency to migrate to other parts of our body. This study presents an automated non‐invasive methodology to assist the clinicians and dermatologists for detection of melanoma. Unlike conventional computational methods which require (expensive) domain expertise for segmentation and hand crafted feature computation and/or selection, a deep convolutional neural network‐based regularised discriminant learning framework which extracts low‐dimensional discriminative features for melanoma detection is proposed. Their approach minimises the whole of within‐class variance information and maximises the total class variance information. The importance of various subspaces arising in the within‐class scatter matrix followed by dimensionality reduction using total class variance information is analysed for melanoma detection. Experimental results on ISBI 2016, MED‐NODE, PH2 and the recent ISBI 2017 databases show the efficacy of their proposed approach as compared to other state‐of‐the‐art methodologies.

Microwave-based sensing for tissue analysis is recently gaining interest due to advantages such as non-ionizing radiation and non-invasiveness. We have developed a set of transmission sensors for microwave-based real-time sensing to quantify muscle mass and quality. In connection, we verified the sensors by 3D simulations, tested them in a laboratory on a homogeneous three-layer tissue model, and collected pilot clinical data in 20 patients and 25 healthy volunteers. This report focuses on initial sensor designs for the Muscle Analyzer System (MAS), their simulation, laboratory trials and clinical trials followed by developing three new sensors and their performance comparison. In the clinical studies, correlation studies were done to compare MAS performance with other clinical standards, specifically the skeletal muscle index, for muscle mass quantification. The results showed limited signal penetration depth for the Split Ring Resonator (SRR) sensor. New sensors were designed incorporating Substrate Integrated Waveguides (SIW) and a bandstop filter to overcome this problem. The sensors were validated through 3D simulations in which they showed increased penetration depth through tissue when compared to the SRR. The second-generation sensors offer higher penetration depth which will improve clinical data collection and validation. The bandstop filter is fabricated and studied in a group of volunteers, showing more reliable data that warrants further continuation of this development.

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.