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Eindhoven University of Technology, Netherlands, The
Techniques to detect the presence or location of a human come in many forms. Approaches based on measuring radio signals may involve geometric principles and taking phase, delay and/or attenuation into account. This paper extends studies into the detection a human in a reverberant environment, without using dedicated localization hardware aside from measurement equipment. It uses scattering parameters to measure the absorption cross-section in a loaded and unloaded reverberation chamber. By referencing the loaded data to the unloaded data and comparing that to Mie theory models of spheres of water with specified radii, we show that a human body cannot be directly modelled as a sphere of water with a fixed radius.We optimize our model for multiple variables to match the measurements, resulting in a representative sphere with a fixed radius and complex, frequency-dependent relative permittivity that fits the human measurement. Hence, our model accounts for the relative refractive index, which stems from relative permittivity, and for the sphere radius. Using measurements and a multivariable optimisation, permittivity and radius for a given measurement are extracted and compared to confirm accuracy. It is shown that a stochastic approach for human occupancy estimation is required due to the uniqueness of people RF characteristics. The results are discussed with a focus on the occupancy estimation and the accuracy of the estimation given a set of measurements.
Full-Body vs. Head-Only Modeling: Full Wave Computational SAR and Adaptation of Corresponding ANN Models
Hamideh Esmaeili, Cheng Yang, Christian Schuster
Hamburg University of Technology, Germany
Electromagnetic compatibility (EMC) analysis is often computationally expensive, with partial modeling and domain-specific approximations commonly employed to improve efficiency, although these simplifications can introduce accuracy trade-offs. To address these challenges, this work focuses on bioelectromagnetic compatibility (Bio-EMC) problems, particularly the Specific Absorption Rate (SAR) calculations, by evaluating SAR in human head tissues using Full-Body and Head-Only models with finite element method (FEM) solvers under plane wave (PW) and near field (NF) exposures at 13.56 MHz. More than 2,000 full wave simulations are conducted, incorporating uncertainties in material properties and exposure angles, with machine learning techniques applied for enhanced analysis.
Results show that while model truncation can impact SAR, certain scenarios allow Head-Only data to effectively replace Full-Body data. In these cases, parameter prioritization in artificial neural networks (ANNs) achieves over 90% accuracy while reducing input parameters by up to 70%. For cases where truncation effects are more significant, the ANN trained on Head-Only data is refined using Full-Body data, improving predictive accuracy up to 85% while maintaining computational efficiency.
The proposed ANN-based approach enhances both computational efficiency and prediction reliability in Bio-EMC analysis, making it applicable to other emission susceptibility scenarios by reducing system complexity and improving the physical interpretation of results.
EM Environment Through Different Lenses: ICU Room Measurements with Different Strategies
Sebastian Mauricio Salas Laurens1, Bärbel van den Berg-de Bakker2, Anne Roc'h1
1Eindhoven University of Technology, Netherlands, The; 2Medisch Spectrum Twente, Netherlands, The
In modern hospitals, particularly in ICUs, medical equipment can introduce various levels of electromagnetic fields, potentially impacting device performance through EMI. A comprehensive risk assessment of electromagnetic environments is essential to ensure reliable device function within the ICU's specific operational environment. This research explores the electromagnetic landscape within an ICU by applying multiple measurement strategies to capture the spatial and spectral distribution of electromagnetic fields. The findings demonstrate that each strategy provides distinct insights into the behaviour of the EMF, some revealing concentrated areas of high field intensity and fluctuations. This leads to a discussion of whether a strategy is better and their pros and cons.
Estimation of CM Input Impedance of a Structure Containing Medical Wearable Devices on Saline
Mohammad Khorramizadeh, Sander Bronckers, Anne Roc'h
Eindhoven University of Technology, Netherlands, The
Several studies focused on the EMC of medical devices. However, the CM input impedance of a structure featuring wearable devices, which can facilitate the assessment of EMI, has not yet been investigated. Here, we present an estimation approach for assessing the CM input impedance of a structure including wearable devices. This estimation is made by the CM input impedance of a structure containing thin wires. Bottles filled with saline emulate the human body, providing an approximation of real-world scenarios involving the human body. Since the CM input impedance of the structure containing wearable devices can differ with the bending shape and positioning of the wearable devices on the human body, statistical analysis is performed to obtain more reliable results.
