Modelling Multilayer Communication Channel in Terahertz Band for Medical Applications

In this work we present a multi-layer channel model for terahertz communication that incorporates both layers of human body tissues and textile layers. Many research works tackled communication channel modelling in human body alone while some other research focused on textile characterization/modelling alone. There is a real gap in connecting these different models. To investigate this, a multi-layer channel model for terahertz communication is developed, this model assumes external textile layer stacked over layers of human body tissues. The electromagnetic properties of the different layers are extracted from previous works that used time domain spectroscopy (TDS) in the terahertz band to characterize each of the considered layers. The model is implemented as a flexible MATLAB/Octave program that enables the simulation of layers with either fixed or random depths. This paper aims to pave the way to connecting patients’ in-body nano-nodes with off-body (on-cloth) nano-nodes by building such a combined channel model. This helps in many applications especially in the medical field. For example, having connected nano-nodes can help in diagnosing diseases, monitoring health by sending information to the external environment, treatment (e.g., increasing or decreasing a certain dose depending on the monitoring), etc. The obtained results show how the THz signal can be affected when it propagates through heterogeneous mediums (i.e., human body tissues and textile). Various types of path-loss has been calculated for this purpose and verified by comparison with results from previous research on separate models of human body and textile

System design and performance analysis of wireless body area networks

One key solution to provide affordable and proactive healthcare facilities to overcome the fast world population growth and a shortage of medical professionals is through health monitoring systems capable of early disease detection and real-time data transmission leading to considerable improvements in the quality of human life. Wireless body area networks (WBANs) are proposed as promising approaches to providing better mobility and flexibility experience than traditional wired medical systems by using low-power, miniaturised sensors inside, around, or off the human body and are employed to monitor physiological signals. However, the design of reliable and energy efficient in-body communication systems is still a major research challenge since implant devices are characterised by strict requirements on size, energy consumption and safety. Moreover, there is still no agreement regarding QoS support in WBANs. The first part of this work concentrates on the design and performance evaluation of WBAN communication systems involving the ‘in-body to in-body’ and ‘in-body to on-body’ scenarios. The essential step is to derive the statistical WBAN path loss (PL) models, which characterise the signal propagation energy loss transmitting via intra-body region. Moreover, from the point of view of human body safety evaluation, the obtained specific absorption rate (SAR) values are compared with the latest Institute of Electrical and Electronics Engineers (IEEE) 802.15.6 Task Group technical standard and the International Commission on Non-Ionizing Radiation Protection (ICNIRP) safety guidelines. Link budget analysis is then presented using a range of energy-efficient modulation schemes, and the results are given including the transmission distance, data rate and transmitting power in individual sections. On the other hand, major quality of service (QoS) support challenges in WBANs are discussed and investigated. To achieve higher lifetime and lower network energy consumption, different data routing protocol methods, including incremental relaying and the two-relay based routing technique are taken into account. A set of key QoS metrics for linear mathematical models is given along with the related subjective functions. The incremental relaying routing protocol promises significant enhancements in in-body WBAN network lifetime by minimising the overall communication distance while the two-relay based routing method achieves better performance in terms of emergency data transmission and high traffic condition, QoS-aware WBANs design. Moreover, to handle real-time high data transmission applications such as capsule endoscope image transmission, a flexible QoS-aware wireless body area sensor networks (WBASNs) model is proposed and evaluated that can bring novel solutions for a realistic multi-user hospital environment regarding information packet collision probability, manageable numbers of sensor nodes and a wide range of data rates

Experimental Phantom-Based Security Analysis for Next-Generation Leadless Cardiac Pacemakers

[EN] With technological advancement, implanted medical devices can treat a wide range of chronic diseases such as cardiac arrhythmia, deafness, diabetes, etc. Cardiac pacemakers are used to maintain normal heart rhythms. The next generation of these pacemakers is expected to be completely wireless, providing new security threats. Thus, it is critical to secure pacemaker transmissions between legitimate nodes from a third party or an eavesdropper. This work estimates the eavesdropping risk and explores the potential of securing transmissions between leadless capsules inside the heart and the subcutaneous implant under the skin against external eavesdroppers by using physical-layer security methods. In this work, we perform phantom experiments to replicate the dielectric properties of the human heart, blood, and fat for channel modeling between in-body-to-in-body devices and from in-body-to-off-body scenario. These scenarios reflect the channel between legitimate nodes and that between a legitimate node and an eavesdropper. In our case, a legitimate node is a leadless cardiac pacemaker implanted in the right ventricle of a human heart transmitting to a legitimate receiver, which is a subcutaneous implant beneath the collar bone under the skin. In addition, a third party outside the body is trying to eavesdrop the communication. The measurements are performed for ultrawide band (UWB) and industrial, scientific, and medical (ISM) frequency bands. By using these channel models, we analyzed the risk of using the concept of outage probability and determine the eavesdropping range in the case of using UWB and ISM frequency bands. Furthermore, the probability of positive secrecy capacity is also determined, along with outage probability of a secrecy rate, which are the fundamental parameters in depicting the physical-layer security methods. Here, we show that path loss follows a log-normal distribution. In addition, for the ISM frequency band, the probability of successful eavesdropping for a data rate of 600 kbps (Electromyogram (EMG)) is about 97.68% at an eavesdropper distance of 1.3 m and approaches 28.13% at an eavesdropper distance of 4.2 m, whereas for UWB frequency band the eavesdropping risk approaches 0.2847% at an eavesdropper distance of 0.22 m. Furthermore, the probability of positive secrecy capacity is about 44.88% at eavesdropper distance of 0.12 m and approaches approximately 97% at an eavesdropper distance of 0.4 m for ISM frequency band, whereas for UWB, the same statistics are 96.84% at 0.12 m and 100% at 0.4 m. Moreover, the outage probability of secrecy capacity is also determined by using a fixed secrecy rate.This work was supported by the Marie Curie Research Grants Scheme, with project grant no 675353, EU Horizon 2020-WIBEC ITN 00 (Wireless In-Body Environment). Details can be found at a source https://cordis.europa.eu/project/rcn/198286_en.html.Awan, MF.; Perez-Simbor, S.; Garcia-Pardo, C.; Kansanen, K.; Cardona Marcet, N. (2018). Experimental Phantom-Based Security Analysis for Next-Generation Leadless Cardiac Pacemakers. Sensors. 18(12):1-24. https://doi.org/10.3390/s18124327S124181

Target-specific multiphysics modeling for thermal medicine applications

Dissertation to obtain the degree of Doctor of Philosophy in Biomedical EngineeringThis thesis addresses thermal medicine applications on murine bladder hyperthermia and brain temperature monitoring. The two main objectives are interconnected by the key physics in thermal medicine: heat transfer. The first goal is to develop an analytical solution to characterize the heat transfer in a multi-layer perfused tissue. This analytical solution accounts for important thermoregulation mechanisms and is essential to understand the fundamentals underlying the physical and biological processes associated with heat transfer in living tissues. The second objective is the development of target-specific models that are too complex to be solved by analytical methods. Thus, the software for image segmentation and model simulation is based on numerical methods and is used to optimize non-invasive microwave antennas for specific targets. Two examples are explored using antennas in the passive mode (probe) and active mode (applicator). The passive antenna consists of a microwave radiometric sensor developed for rapid non-invasive feedback of critically important brain temperature. Its design parameters are optimized using a power-based algorithm. To demonstrate performance of the device, we build a realistic model of the human head with separate temperaturecontrolled brain and scalp regions. The sensor is able to track brain temperature with 0.4 °C accuracy in a 4.5 hour long experiment where brain temperature is varied in a 37 °C, 27 °C and 37 °C cycle. In the second study, a microwave applicator with an integrated cooling system is used to develop a new electro-thermo-fluid (multiphysics) model for murine bladder hyperthermia studies. The therapy procedure uses a temperature-based optimization algorithm to maintain the bladder at a desired therapeutic level while sparing remaining tissues from dangerous temperatures. This model shows that temperature dependent biological properties and the effects of anesthesia must be accounted to capture the absolute and transient temperature fields within murine tissues. The good agreement between simulation and experimental results demonstrates that this multiphysics model can be used to predict internal temperatures during murine hyperthermia studies

The simulated effect of the lightning first short stroke current on a multi-layered cylindrical model of the human leg

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in ful lment of the requirements for the degree of Master of Science in Engineering. Johannesburg, 2015This research investigates the e ects of the frequency components of the lightning First Short Stroke (FSS) on the current pathway through human tissues using frequency domain analysis. A Double Exponential Function (DEF) is developed to model the FSS with frequency components in the range 10 Hz 100 kHz. Human tissues are simulated using Finite Element Analysis (FEA) in COMSOL and comprises of two types of models: Single Layer Cylindrical Model (SLCM) and Multi-layered Cylindrical Model (MLCM). The SLCM models 54 human tissues independently and the MLCM models the human leg with ve tissue layers: bone marrow, cortical bone, muscle, blood and fat. Three aspects are analysed: current density, complex impedance and power dissipation. From the SLCM results, aqueous tissues have the lowest impedances and tissue heat dissipation is proportional to tissue impedance. Results from the MLCM show that 85% of the FSS current ows through muscle, 11% ows through blood, 3:5% through fat and the rest through cortical bone and bone marrow. From the results, frequency dependent equivalent circuit models consisting of resistors and capacitors connected in series are proposed. The simulation results are correlated with three main clinical symptoms of lightning injuries: neurological, cardiovascular and external burns. The results of this work are applicable to the analysis of High Voltage (HV) injuries at power frequencies.MT201

Electromagnetic Absorption by the Human Body from 1 - 15 GHz

Microwave radiation is emitted by a wide variety of computing, communications and other technologies. In many transport, industrial and medical contexts, humans are placed in close proximity to several of these sources of emission in reflective, enclosed cavities. Pseudo-reverberant conditions are created, in which absorption by human bodies can form a significant, even the dominant loss mechanism. The amount of energy stored, and hence the field intensities in these environments depend on the nature of electromagnetic absorption by the human body, so quantifying human absorption at these frequencies is necessary for accurate modelling of both electromagnetic interference and communications path loss in such situations. The research presented here aims to quantify absorption by the body, for the purpose of simulating its effect on the environments listed above. For this purpose, nine volunteer participants are enlisted in a preliminary study in which their height and mass are taken and their electromagnetic absorption cross section is measured in a reverberation chamber. The preliminary study is unable to gather enough data to provide precise measurements during the time that a participant is willing to sit motionless in the chamber. Issues also exist due to power loss in some parts of the equipment. A number improvements are made to both the experimental equipment and methodology, and the study is repeated with a sample of 60 adult volunteer participants. The results are compared to the preliminary data and found to match, once unwanted absorption in the latter has been subtracted. The results are also validated using data from absorption by a spherical phantom of known absorptive properties. The absorption cross section of the body is plotted and its behaviour is compared to several biometric parameters, of which the body’s surface area is found to have a dominant effect on absorption. This is then normalised out to give an absorption efficiency of the skin, which is again compared to several biometric parameters; the strongest correlation is found to be with an estimate for average thickness of the subcutaneous fat layer. These data are used to model the effect of 400 passengers on the Q-factor of an airliner’s cabin. Absorption by the passengers is shown to be the dominant loss mechanism in the cabin, showing the importance of accounting for human absorption when modelling electromagnetic propagation and interference in situations that include human occupants. The relationship between subcutaneous fat and absorption efficiency is suggested for further research, as it promises development of new tools to study body composition, with possible medical applications

Microwave Imaging of Brain Stroke:Contributions to Modeling and Inverse Problem Resolution

Brain stroke is an age-related illness which has become a major issue in our ageing societies. Early diagnosis and treatment are of high importance for the full recovery of the patient, as reminded in Anglo-Saxon countries by the abbreviation FAST (Face, Arm, Speech, Time) referring to both the four major visible signs and the necessity to act fast. In this respect, Computed Tomography (CT) and Nuclear Magnetic Resonance (NMR) imaging are key diagnostic tools in clinical practice. Unfortunately, not only these modalities can neither be transported nor rapidly usable, which would allow early treatment (especially in rural environments), but also cannot be brought to the bedside of the patient to monitor the evolution of the disease. Microwave Imaging (MWI) is a potential candidate to provide fast and accurate diagnostic insights for brain stroke pathological states. The head of the patient is illuminated with low-power microwave waveforms (non-ionizing radiations), whose backscattered signals are used to generate either images of its internal structures, distributions, patterns and shapes (qualitative imaging) or directly its physical parameters such as the dielectric contrast and the permittivity values (quantitative imaging). The technology relies on the high sensitivity of microwaves on the water content of tissues to allow for the discrimination between pathological and healthy regions. This thesis focuses on both the forward modeling of the electromagnetic phenomena arising in biological tissues and the inverse scattering problem for imaging in the differential MWI (dMWI) scenario for brain stroke monitoring. It is intrinsically interdisciplinary as it requires knowledge in Biology, Medicine, Physics, Chemistry, and Engineering. In order to investigate the challenges arising in brain MWI, it is crucial to have accurate and efficient solvers to model electromagnetic (EM) fields at UHF/SHF-bands. The head is a distributed, heterogeneous, and lossy scatterer for which existing solvers are known to struggle at higher frequencies. Volume Integral Equation (VIE) formulations and MultiGrid (MG) approaches are investigated to find the actual solution of the field distributions for large scale problems. The EM modeling also permits to analyze the feasibility of brain MWI, which depends on the power transmission from the antennas towards the human brain. In order to estimate this transmission, simplified but still representative models, including intermediate layers -skin, fat, bone, and CerebroSpinal Fluid (CSF) - of the head, are proposed in the framework of simulations (analytical tools) and experimental validations (3D printed head phantom). For the imaging task, the physics of the EM scattering, leads to complex non-linear inverse scattering problems (consisting in retrieving from a set of field measurements the physical parameters which produced them) for which reliable assumptions and approximations must be found. For brain MWI, estimating and quantifying the degree of non-linearity allows for determining the scope of application of existing algorithms, for which different regularizers are applied. Modeling and inverse problem resolution for brain MWI investigated in the present work are ultimately meant to contribute to the development of a technology dedicated to brain stroke detection, differentiation, and monitoring