The paper deals with a simplified procedure for the assessment of steady-state temperature increase in one-dimensional 3-layer tissue model (composed of skin, fat and muscle) using analytical approach. The solution of a simplified variant of Pennes' bioheat transfer Equation (PBHE) reduces the number of parameters in the parametric analysis, resulting in modified equation that can be solved analytically using the classical theory of ordinary differential equations in each tissue layer. The steady-state temperature distribution in 3-layer tissue model, exposed to an incident time harmonic electromagnetic (EM) field, is governed by the stationary form of the PBHE supplemented by the Robin boundary condition (BC). The presented results are given for the case of a constant and exponentially decreasing power density vs tissue depth. The results show that the obtained solution gives an overestimation of steady-state temperature due to EM radiation compared to other analytical methods.

The paper deals with a simplified procedure for the assessment of steady-state temperature in a single-layer parallelepiped human body model exposed to electromagnetic (EM) radiation using analytical approach. The related bioheat transfer equation variant is solved analytically using the classical theory of ordinary differential equations. The results are given for the case of constant power density and for power density exponentially decreasing with the tissue depth. The proposed approach leads to the overestimation of steady-state temperature in the body exposed to EM radiation, compared to other analytical methods.

This paper deals with a simple procedure for the assessment of Specific Absorption Rate (SAR) and Transmitted Power Density (TPD) in the parallelepiped human body model exposed to a vertical dipole antenna above a lossy half space. The results are obtained by numerical/analytical evaluation of the field integrals with analytical model with far field approximation. Results obtained via different approximations agree satisfactorily under certain conditions.

This paper compares a numerical model of a vertical dipole placed in the air, along the z-axis, above a lossy half space with a model with assumed current distribution (triangular and sinusoidal). The electric field is computed for various heights above ground and various ratios of the physical length and wavelength of the antenna. The obtained results show that both approaches give similar results under certain conditions.

The paper deals with a simplified assessment of distribution of Specific Absorption Rate averaged over a whole body (SARWB) for the human exposure to near RFiD reader antennas. SARWB is computed for various distances between the antenna and the user featuring parallelepiped model of the human body. The frequencies of interest are $f = 100$ kHz, $f = 13.56$ MHz, $f = 915$ MHz and $f = 2.4$ GHz, and the reader is assumed to radiate EIRP of 4 We.i.r.p.. The obtained results show that for distances between 1 cm and 2 m from the reader antenna SARWB values are below the allowed limit of 0.4 W/kg for workers.

Human activity recognition (HAR) is a classification process that is used for recognizing human motions. A comprehensive review of currently considered approaches in each stage of HAR, as well as the influence of each HAR stage on energy consumption and latency is presented in this paper. It highlights various methods for the optimization of energy consumption and latency in each stage of HAR that has been used in literature and was analyzed in order to provide direction for the implementation of HAR in health and wellbeing applications. This paper analyses if and how each stage of the HAR process affects energy consumption and latency. It shows that data collection and filtering and data segmentation and classification stand out as key stages in achieving a balance between energy consumption and latency. Since latency is only critical for real-time HAR applications, the energy consumption of sensors and devices stands out as a key challenge for HAR implementation in health and wellbeing applications. Most of the approaches in overcoming challenges related to HAR implementation take place in the data collection, filtering and classification stages, while the data segmentation stage needs further exploration. Finally, this paper recommends a balance between energy consumption and latency for HAR in health and wellbeing applications, which takes into account the context and health of the target population.