This article presents a sub-6GHz ISM-band flexible wearable MIMO antenna array for wireless body area networks (WBANs) and biomedical telemetry devices. The array is based on metasurface inspired technology. The antenna array consists of 2×2 matrix of triangular-shaped radiation elements that were realized on 0.8 mm thick Rogers RT/duroid 5880 substrate. Radiation characteristics of the array are enhanced by isolating the surface current interaction between the individual radiators in the array. This is achieved by inserting an electromagnetic bandgap (EBG) decoupling structure between the radiating elements. The radiating elements were transformed into a metasurface by etching sub-wavelength slots inside them. The periodic arrangement of slots acts like resonant scatterers that manipulate the electromagnetic response of the surface. Results confirm that by employing the decoupling structure and sub-wavelength slots the isolation between the radiators is significantly improved (>34.8 dB). Moreover, there is an improvement in the array's fractional bandwidth, gain and the radiation efficiency. The optimized array design for operation over 5.0-6.6 GHz has an average gain and efficiency of 10 dBi and 83%, respectively. Results show that the array's performance is not greatly affected by a certain amount of bending. In fact, the antenna maintains a gain between 8.65-10.5 dBi and the efficiency between 77-83%. The proposed MIMO antenna array is relatively compact, can be easily fabricated on one side of a dielectric material, allows easy integration with RF circuitry, is robust, and maintains its characteristics with some bending. These features make it suitable for various wearable applications and biomedical telemetry devices.INDEX TERMS On-body antennas, wearable antennas, flexible antennas, metasurface (MTS) antennas, electromagnetic bandgap (EBG) devices, biomedical telemetry devices, wireless body area network (WBAN), MIMO antenna array.

Wearable devices with 5G technology are currently more ingrained in our daily lives, and they will now be a part of our bodies too. The requirement for personal health monitoring and preventive disease is increasing due to the predictable dramatic increase in the number of aging people. Technologies with 5G in wearables and healthcare can intensely reduce the cost of diagnosing and preventing diseases and saving patient lives. This paper reviewed the benefits of 5G technologies, which are implemented in healthcare and wearable devices such as patient health monitoring using 5G, continuous monitoring of chronic diseases using 5G, management of preventing infectious diseases using 5G, robotic surgery using 5G, and 5G with future of wearables. It has the potential to have a direct effect on clinical decision making. This technology could improve patient rehabilitation outside of hospitals and monitor human physical activity continuously. This paper draws the conclusion that the widespread adoption of 5G technology by healthcare systems enables sick people to access specialists who would be unavailable and receive correct care more conveniently.

In this paper, we propose a new Modified Laplacian Vector Median Filter (MLVMF) for real-time denoising complex images corrupted by “salt and pepper” impulsive noise. The method consists of two rounds with three steps each: the first round starts with the identification of pixels that may be contaminated by noise using a Modified Laplacian Filter. Then, corrupted pixels pass a neighborhood-based validation test. Finally, the Vector Median Filter is used to replace noisy pixels. The MLVMF uses a 5 × 5 window to observe the intensity variations around each pixel of the image with a rotation step of π/8 while the classic Laplacian filters often use rotation steps of π/2 or π/4. We see better identification of noise-corrupted pixels thanks to this rotation step refinement. Despite this advantage, a high percentage of the impulsive noise may cause two or more corrupted pixels (with the same intensity) to collide, preventing the identification of noise-corrupted pixels. A second round is then necessary using a second set of filters, still based on the Laplacian operator, but allowing focusing only on the collision phenomenon. To validate our method, MLVMF is firstly tested on standard images, with a noise percentage varying from 3% to 30%. Obtained performances in terms of processing time, as well as image restoration quality through the PSNR (Peak Signal to Noise Ratio) and the NCD (Normalized Color Difference) metrics, are compared to the performances of VMF (Vector Median Filter), VMRHF (Vector Median-Rational Hybrid Filter), and MSMF (Modified Switching Median Filter). A second test is performed on several noisy chest x-ray images used in cardiovascular disease diagnosis as well as COVID-19 diagnosis. The proposed method shows a very good quality of restoration on this type of image, particularly when the percentage of noise is high. The MLVMF provides a high PSNR value of 5.5% and a low NCD value of 18.2%. Finally, an optimized Field-Programmable Gate Array (FPGA) design is proposed to implement the proposed method for real-time processing. The proposed hardware implementation allows an execution time equal to 9 ms per 256 × 256 color image.

Microgrids have benefited energy systems by getting rid of the abundant use of traditional energy resources, replacing them with distributed generations (DGs). The use of DGs in microgrids not only provides clean and green energy but also reduces the gigantic losses in transmission and distribution lines. Widespread adoption of renewable energy in microgrids saves customers from high fuel prices and provides a sustainable replacement for future fossil fuel depletion. Microgrids have proven to be the latest and most advanced power systems due to their new capabilities to operate in both grid-connected and isolated modes. Microgrids use multiple energy sources simultaneously, which can offset the intermittent behavior of renewable energy sources. In this study, we planned and optimized an industrial microgrid with an annual increase in load, which contains dispatchable generation, non-dispatched generation, and energy storage. In addition, to test the different behavior of a microgrid operating independently or in grid-tied mode, four typical days were selected to show the load demand and solar and wind energy forecast data for the entire year. The power output curves for each typical day were analyzed for every year in both stand-alone and grid-connected modes. Furthermore, to validate the feasibility of the microgrid, the investment and operations costs were also calculated in the paper.