The microwave sensing technique is a possible and attractive alternative modality to standard X-rays, magnetic resonance imaging, and computed tomography methods for medical diagnostic applications. This technique is beneficial since it uses non-ionizing radiation and that can be potentially used for the microwave healthcare system. The main purpose of this paper is to present a microwave sensing technique to analyze the variations in biological tissue thickness, considering the effects of physiological and biological properties on microwave signals. In order to fulfill this goal, we have developed a two-port noninvasive sensor system composed of two split ring resonators (SRRs) operating at an Industrial, Scientific, and Medical (ISM) frequency band of 2.45 GHz. The system is verified using the amplitude and phase of the transmitted signal in ex-vivo models, representing different tissue thicknesses. Clinical applications such as the diagnosis of muscular atrophy can be benefitted from this study.

The human subcutaneous fat layer, skin and muscle together act as a waveguide for microwave transmissions and provide a low-loss communication medium for implantable and wearable body area networks (BAN). In this work, fat-intrabody communication (Fat-IBC) as a human body-centric wireless communication link is explored. To reach a target 64 Mb/s inbody communication, wireless LAN in the 2.4 GHz band was tested using low-cost Raspberry Pi single-board computers. The link was characterized using scattering parameters, bit error rate (BER) for different modulation schemes, and IEEE 802.11n wireless communication using inbody (implanted) and onbody (on the skin) antenna combinations. The human body was emulated by phantoms of different lengths. All measurements were done in a shielded chamber to isolate the phantoms from external interference and to suppress unwanted transmission paths. The BER measurements show that, except when using dual on-body antennas with longer phantoms, the Fat-IBC link is very linear and can handle modulations as complex as 512-QAM without any significant degradation of the BER. For all antenna combinations and phantoms lengths, link speeds of 92 Mb/s were achieved using 40 MHz bandwidth provided by the IEEE 802.11n standard in the 2.4 GHz band. This speed is most likely limited by the used radio circuits, not the Fat-IBC link. The results show that Fat-IBC, using low-cost off-the-shelf hardware and established IEEE 802.11 wireless communication, can achieve high-speed data communication within the body. The obtained data rate is among the fastest measured with intrabody communication.

This paper presents numerical modeling and experimental validation of the signal path loss at the 5.8 GHz Industrial, Scientific, and Medical (ISM) band, performed in the context of fat-intrabody communication (fat-IBC), a novel intrabody communication platform using the body-omnipresent fat tissue as the key wave-guiding medium. Such work extends our previous works at 2.0 and 2.4 GHz in the characterization of its performance in other useful frequency range. In addition, this paper also includes studies of both static and dynamic human body movements. In order to provide with a more comprehensive characterization of the communication performance at this frequency, this work focuses on investigating the path loss at different configurations of fat tissue thickness, antenna polarizations, and locations in the fat channel. We bring more realism to the experimental validation by using excised tissues from porcine cadaver as both their fat and muscle tissues have electromagnetic characteristics similar to those of human with respect to current state-of-art artificial phantom models. Moreover, for favorable signal excitation and reception in the fat-IBC model, we used topology optimized waveguide probes. These probes provide an almost flat response in the frequency range from 3.2 to 7.1 GHz which is higher than previous probes and improve the evaluation of the performance of the fat-IBC model. We also discuss various aspects of real-world scenarios by examining different models, particularly homogeneous multilayered skin, fat, and muscle tissue. To study the effect of dynamic body movements, we examine the impact of misalignment, both in space and in wave polarization, between implanted nodes. We show in particular that the use of fat-IBC techniques can be extended up in frequency to a broadband channel at 5.8 GHz.

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.

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.

The potential offered by intra-body communication (IBC) over the past few years has resulted in a spike of interest for the topic, specifically for medical applications. Fat-IBC is subsequently a novel alternative technique that utilizes fat tissue as a communication channel. This work aimed to identify such transmission medium and its performance in varying blood-vessel systems at 2.45 GHz, particularly in the context of IBC and medical applications. It incorporated three-dimensional (3D) electromagnetic simulations and laboratory investigations that implemented models of blood vessels of varying orientations, sizes, and positions. Such investigations were undertaken by using ex-vivo porcine tissues and three blood-vessel system configurations. These configurations represent extreme cases of real-life scenarios that sufficiently elucidated their principal influence on the transmission. The blood-vessel models consisted of ex-vivo muscle tissues and copper rods. The results showed that blood vessels crossing the channel vertically contributed to 5.1 dB and 17.1 dB signal losses for muscle and copper rods, respectively, which is the worst-case scenario in the context of fat-channel with perturbants. In contrast, blood vessels aligned-longitudinally in the channel have less effect and yielded 4.5 dB and 4.2 dB signal losses for muscle and copper rods, respectively. Meanwhile, blood vessels crossing the channel horizontally displayed 3.4 dB and 1.9 dB signal losses for muscle and copper rods, respectively, which were the smallest losses among the configurations. The laboratory investigations were in agreement with the simulations. Thus, this work substantiated fat-IBC signal transmission variability in the context of varying blood vessel configurations.