Diabetes is a chronic condition that is characterized by high blood glucose levels and can cause damage to multiple organs over time. Continuous monitoring of glucose levels is essential for both diabetic and non-diabetic individuals. There have been major developments in glucose monitoring technology over the past decade, which have been driven by research and industry efforts. Despite these significant advancements, the area of glucose biosensors still faces significant challenges. This paper presents a comprehensive summary of the latest glucose monitoring technologies, including invasive

Polluted water is one of the significant challenges facing the world nowadays, especially with the noticed water shortage recorded in the last period. Different treatment methods, physicochemical and biological, were presented for pollutant removal from polluted wastewater. This review discusses the treatment methods starting from the biological part to help reduction of organics, which are solids that appear in the wastewater. After that, the physicochemical techniques will be discussed as a second part of the treatment process to minimize the heavy metal, dyes, and other pollutants

Diabetes is a disease in which the body does not adequately process food for energy production. Most of the food we consume is converted into glucose, or sugar, which our bodies use for energy. Moreover, the pancreas, which is an organ located near the stomach, produces insulin, a hormone that aids in the transport of glucose into our bodies' cells. Diabetes occurs when your body either does not produce enough insulin or does not use its own insulin the way it is supposed to. Sugars accumulate in your blood as a result of this. This is why diabetes is often referred to as "sugar". People with

Steady State Visually Evoked Potentials (SSVEPs) are intrinsic responses to specific visual stimulus frequencies. When the retina is activated by a frequency ranging from 3.5 to 75 Hz, the brain produces electrical activity at the same frequency as the visual signal, or its multiples. Identifying the preferred frequencies of neurocortical dynamic processes is a benefit of SSVEPs. However, the time consumed during calibration sessions limits the number of training trials and gives rise to visual fatigue since there is significant human variation across and within individuals over time, which

This research paper presents the wireless data and power transfer system for optogenetics visual cortical prosthesis. The system uses the inductive coupling power transfer and 2.4GHz Bluetooth 4.0 data transfer. This system contains two hardware parts: the external headset consists of power and data transmitters, image capture, and image processing units; the subcutaneous implant PCB consists of power and data receiver and the control unit. We also present the relative image processing method for this system. The whole system could power and control the optogenetic neural stimulus of the

Piezoelectric vibration energy harvesters have attracted a lot of attention as a way to power self-sustaining electronic systems. Furthermore, as part of the growing Internet of Things (loT) paradigm, the ongoing push for downsizing and higher degrees of integration continues to constitute major drivers for autonomous sensor systems. Two of the most effective interface circuits for piezoelectric energy harvesters are synchronised switch harvesting (SSH) on inductor and synchronous electrical charge extraction; nevertheless, inductors are essential components in both interfaces. This study

The applications of Federated Learning are many, and they can be used to predict electricity consumption and, at the same time, enable smart meters to collaboratively learn a shared model while keeping all their data locally in their own private database. With this approach, the central model will see more data and will work better to predict electricity consumption more accurately than the models trained on only one local Dataset. The planning of infrastructure, grid operation, and budgeting all depend on accurate load forecasting. As a result, this paper suggests federated learning for load

Optogenetic-based neuroprosthetic therapies are increasingly being considered for human trials. However, the optoelectronic design of clinical-grade optogenetic-based neuroprosthetic probes still requires some thought. Design constraints include light penetration into the brain, stimulation efficacy, and probe/tissue heating. Optimisation can be achieved through experimental iteration. However, this is costly, time-consuming and ethically problematic. Hence it is highly desirable to have an alternative to excessive animal trials. Thus, a simulation tool for optimising probe design can be an

In order to strengthen the safety of corporate multimedia assets, a semi-fragile watermarking method is developed, which makes use of the integer wavelet transform (IWT) and the discrete cosine transform (DCT) for tamper detection and recovery. In this paper, we produce two distinct kinds of watermarks: an authentication watermark and a recovery watermark. A tamper detection methodology is utilized at the receiving end to check the watermarked image for validity and detect any assaults. If the changes are determined to be malicious, the suggested tamper recovery method is used to restore the

Harvesting the energy from environmental sources is a promising solution for perpetual and continuous operation of biomedical wearable devices. Although the energy harvesting technology ensures the availability of energy source, yet power management is crucial to ensure prolonged and stable operation under a stringent power budget. Thus, power-aware task scheduling can play a key role in minimizing energy consumption to improve system durability while maintaining device functionality. This chapter proposes a novel biosensor task scheduling of energy harvesting-based biomedical wearable devices