This paper presents a thorough review of the main techniques used for wireless power transfer (WPT) in implantable medical devices (IMDs) with a specific focus on the techniques that employ implantable antennas for energy harvesting (electromagnetic (EM) WPT techniques). The techniques are first analysed and compared based on the IMD application, power transfer efficiency (PTE), transfer distance, implantation depth, implant size, operating frequency, and specific absorption rate (SAR). The study provides a critical analysis of the main WPT system’s as well as implantable antennas’ design parameters that control the PTE and hence the charging rate of the IMD. The investigated design parameters include the WPT TX-RX antennas’ gain, WPT-RX size, transfer distance, and the WPT TX-RX antennas’ alignment. Tutorial simulation examples are included to showcase the impact of these design parameters on the amount of power coupled to the IMD. The paper also discusses recent techniques used for improving the amount of power received by implantable antennas, and hence higher PTE and IMDs charging rate, namely, the use of implantable MIMO WPT-RX antennas to mitigate antennas misalignment and the use of metamaterial surfaces to focus the power emitted from WPT-TX antennas towards the implantable WPT-RX antennas. The findings and observations reported in this study serve as a valuable resource for designers and researchers to comprehend the effect of various WPT TX-RX antennas design parameters on PTE. The analysis and full-wave simulation examples, included in the paper, are shown very useful in understanding the challenges associated with WPT in IMDs and in proposing potential solutions.

This paper presents a very compact, wideband, and enhanced-gain antenna for 5G applications. A simple single-layer millimeter wave (mm-wave) metamaterial lens (meta-lens) is used to improve the gain, aperture efficiency, and gain bandwidth of a slotted-patch antenna over a wide range of frequencies from 25 GHz to 31 GHz. The lens exhibits a metamaterial negative refractive index behavior, which is attributed to a substantial gain enhancement of around 4–5 dBi over the whole band compared to the gain values of the slotted patch antenna alone. The lens’s unit cell comprises a simple single-layer split ring resonator (SRR) whose dimensions are carefully chosen to improve transmitted power and suppress absorbed and reflected power. The meta-lens consists of $8\times 8$ subwavelength SRR unit cells. Each cell has an area of $1.6\times 1.6$ mm2, it is located in the near-field region closely above a slotted patch antenna to produce a total antenna size of $12.8\times 12.8\times 7.27$ mm3 ( $1.2~\lambda \times 1.2~\lambda \times 0.68~\lambda $ , where $\lambda $ is the free space wavelength at 28 GHz). The maximum gain of the proposed antenna is 12.7 dBi, the 1 dB gain bandwidth is 18%, the maximum aperture efficiency is 92%, and the −10 dB impedance bandwidth (10 dB B.W.) is 17%. This excellent combination of essential metrics is hard to realize at mm-wave using narrowband antenna structures (microstrip patch antennas), and the aperture efficiency is the highest thus far for such a class of antennas.

Ultra-wideband radar technology (UWB) has demonstrated its vital role through various applications in surveillance, search and rescue, health monitoring, and the military. Unlike conventional radars, UWB radars use high-frequency, wide-bandwidth pulses, enabling long-range detection and penetrating obstacles. This work presents an in-depth review of UWB radar systems for recognizing human activities in a room and through-the-wall (TTW) with other diverse applications. After briefly discussing different UWB radar working principles and architectures, the study explores their role in various TTW applications in real-world scenarios. An extensive performance comparison of the legacy studies is presented, focusing on detection tools, signal processing, and imaging algorithms. The discussion includes an analysis of the integration of machine learning models. The primary focus is on the detection, movement, monitoring of vital signs, and nonhuman classifications in the context of Through-The-Wall (TTW) scenarios. This study contributes to a better understanding of evolving technology capabilities by integrating artificial intelligence (AI) and robotics to automate and precisely locate the target in various scenarios. Furthermore, the discussion includes the impact of UWB technology on society, future industry trends, the commercial landscape, and ethical issues to understand and future research.

This paper presents a critical review of modern 4G, 4G/5G, and 5G antennas, which employ PIN diodes and Varactors for polarization or frequency reconfiguration. For the reviewed 4G and 5G polarization reconfigurable antennas, a new parameter named spectrum utilization "AR/ S ₁₁ B.W." is defined for the first time to predict the shared spectrum between the impedance bandwidth and the axial ratio bandwidth for circularly polarized antennas. The calculated spectrum utilization for many designs revealed that the majority of implementations failed to achieve full utilization of the available bandwidth. Besides, employing multiple PIN diodes is shown useful in improving the spectrum utilization and in supporting multiple polarization states. For the reviewed 4G, 4G/5G and 5G frequency reconfigurable antennas, the focus is mainly on comparing the available tuning range, fractional bandwidth and the Fractional Bandwidth Change (FBWC) upon tuning. The latter parameter, is defined and calculated in this work to measure the change in the FBW upon tuning. Utilizing multiple Varactors is shown promising in improving a 4G antenna’s fractional bandwidth, while combining Multiple PINs and Varactors in one design is found efficient in improving the FBWC and the tuning range in the 5G spectrum.

In this study, the mutual coupling in multiple-input-multiple-output (MIMO) dielectric resonator antenna (DRA) is reduced by employing closed metallic loops. The loops are wrapped around the adjacent edges of the dielectric resonators (DR) where magnetic coupling is significant. The proposed method employs only the conductive metallic strips for mutual coupling reduction and this makes the entire design very simple and compact. The impedance bandwidth varies from 4.73 to 5.1 GHz, covering the Sub–6 GHz 5G band. The realized MIMO DRA has an isolation of 28 dB at the resonant frequency with a measured peak gain at each port of 3.5 dBi and a peak radiation efficiency of 93%. The obtained measured results yield a low correlation coefficient (< 0.05) mostly at the entire band that contribute to diversity gain ( $ > 9.8$ dB) to increase the capacity of communication system, is reported in this paper. The proposed antenna was fabricated and the closed loop strip is wrapped around using in house facility. Furthermore, some issues related to the fabrications tolerance have been investigated to justify the difference between some simulated and measured results.

Parkinson’s Disease (PD) is a complex neurodegenerative disorder characterized by a spectrum of motor and non-motor symptoms, prominently featuring the freezing of gait (FOG), which significantly impairs patients’ quality of life. Despite extensive research, the precise mechanisms underlying FOG remain elusive, posing challenges for effective management and treatment. This paper presents a comprehensive meta-analysis of FOG prediction and detection methodologies, with a focus on the integration of wearable sensor technology and machine learning (ML) approaches. Through an exhaustive review of the literature, this study identifies key trends, datasets, preprocessing techniques, feature extraction methods, evaluation metrics, and comparative analyses between ML and non-ML approaches. The analysis also explores the utilization of cueing devices. The limited adoption of explainable AI (XAI) approaches in FOG prediction research represents a significant gap. Improving user acceptance and comprehension requires an understanding of the logic underlying algorithm predictions. Current FOG detection and prediction research has a number of limitations, which are identified in the discussion. These include issues with cueing devices, dataset constraints, ethical and privacy concerns, financial and accessibility restrictions, and the requirement for multidisciplinary collaboration. Future research avenues center on refining explainability, expanding and diversifying datasets, adhering to user requirements, and increasing detection and prediction accuracy. The findings contribute to advancing the understanding of FOG and offer valuable guidance for the development of more effective detection and prediction methodologies, ultimately benefiting individuals affected by PD.