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Leukemia is a type of cancer that affects the body's blood-forming tissue, where the bone marrow produces an excessive amount of abnormal white blood cells (WBCs) that do not function properly. The diagnosis of leukemia is typically done by a trained expert who visually observes unique features and determines the type of cancer. However, digital image processing techniques have been improving in the healthcare system, particularly in diagnosing different types of diseases and helping doctors make treatment decisions. This paper presents a system for detecting leukemia in blood microscopic images and classifying them as normal or abnormal (with leukemia) automatically. Two main techniques were used: counting the number of WBCs around red blood cells (RBCs) and measuring the average area of WBCs around a bounding box around each cell. The classification accuracy was calculated at 91.7 and 88.8% for the two techniques, respectively. These techniques can be used as features in machine learning applications, and the system presented is faster and more efficient than traditional diagnostic processes used in hospitals.

Tissue engineering is a relatively new area of research that combines medical, biological, and engineering fundamentals to create tissue-engineered constructs that regenerate, preserve, or slightly increase the functions of tissues. To create mature tissue, the extracellular matrix should be imitated by engineered structures, allow for oxygen and nutrient transmission, and release toxins during tissue repair. Numerous recent studies have been devoted to developing three-dimensional nanostructures for tissue engineering. One of the most effective of these methods is electrospinning. Numerous nanofibrous scaffolds have been constructed over the last few decades for tissue repair and restoration. The current review gives an overview of attempts to construct nanofibrous meshes as tissue-engineered scaffolds for various tissues such as bone, cartilage, cardiovascular, and skin tissues. Also, the current article addresses the recent improvements and difficulties in tissue regeneration using electrospinning.

In recent years, the development of biomedical monitoring systems, including respiration monitoring systems, has been accelerated. Wearable and implantable medical devices are becoming increasingly important in the diagnosis and management of disease and illness. Respiration can be monitored using a variety of biosensors and systems. Auto-charged sensors have a number of advantages, including low cost, ease of preparation, design flexibility, and a wide range of applications. It is possible to use the auto-charged sensors to directly convert mechanical energy from the airflow into electricity. The ability to monitor and diagnose one’s own health is a major goal of auto-charged sensors and systems. Respiratory disease model output signals have not been thoroughly investigated and clearly understood. As a result, figuring out their exact interrelationship is a difficult and important research question. This review summarized recent developments in auto-charged respiratory sensors and systems in terms of their device principle, output property, detecting index, and so on. Researchers with an interest in auto-charged sensors can use the information presented here to better understand the difficulties and opportunities that lie ahead.

Electrospinning enables simple and cost-effective production of polymer nanofibers from different polymer materials. Drug delivery systems are capable of achieving maximum drug treatment benefits by significantly reducing adverse complications. Electrospun nanofibers have recently attracted considerable attention owing to their distinctive properties, including flexibility and biocompatibility. The implementation of functional constituents within nanostructure fibers blends is an effective technique for the administration of a variety of drugs in animal research, broadening the nanofiber capability and reliability. The nanofibrous mesh and its various application purposes are discussed in terms of a summary of recent research, emphasizing the ease of streaming and a large number of combinations of this approach, which could lead to a breakthrough in targeted therapy.

Recently, there has been an evolution toward a science-supported medicine, which uses replicable results from comprehensive studies to assist clinical decision-making. Reliable techniques are required to improve the consistency and replicability of studies assessing the effectiveness of clinical guidelines, mostly in muscular and therapeutic healthcare. In scientific research, surface electromyography (sEMG) is prevalent but underutilized as a valuable tool for physical medicine and rehabilitation. Other electrophysiological signals (e.g., from electrocardiogram (ECG), electroencephalogram (EEG), and needle EMG) are regularly monitored by medical specialists; nevertheless, the sEMG technique has not yet been effectively implemented in practical medical settings. However, sEMG has considerable clinical promise in evaluating muscle condition and operation; nevertheless, precise data extraction requires the definition of the procedures for tracking and interpreting sEMG and understanding the fundamental biophysics. This review is centered around the application of sEMG in rehabilitation and health monitoring systems, evaluating their technical specifications, including wearability. At first, this study examines methods and systems for tele-rehabilitation applications (i.e., neuromuscular, post-stroke, and sports) based on detecting EMG signals. Then, the fundamentals of EMG signal processing techniques and architectures commonly used to acquire and elaborate EMG signals are discussed. Afterward, a comprehensive and updated survey of wearable devices for sEMG detection, both reported in the scientific literature and on the market, is provided, mainly applied in rehabilitation training and physiological tracking. Discussions and comparisons about the examined solutions are presented to emphasize how rehabilitation professionals can reap the aid of neurobiological detection systems and identify perspectives in this field. These analyses contribute to identifying the key requirements of the next generation of wearable or portable sEMG devices employed in the healthcare field.

Applications of terahertz (THz) imaging technologies have advanced significantly in the disciplines of biology, medical diagnostics, and non- destructive testing in the past several decades. Significant progress has been made in THz biomedical imaging, allowing for the label-free diagnosis of malignant tumors. Terahertz frequencies, which lie between those of the microwave and infrared, are highly sensitive to water concentration and are significantly muted by water. Terahertz radiation does not cause ionization of biological tissues because of its low photon energy. Recently, terahertz spectra, including spectroscopic investigations of cancer, have been reported at an increasing rate due to the growing interest in their biological applications sparked by these unique features. To improve cancer diagnosis with terahertz imaging, an appropriate differentiation technique is required to increased blood supply and localized rise in tissue water content that commonly accompany the presence of malignancy. Terahertz imaging has been found to benefit from structural alterations in afflicted tissues. This study provides an overview of terahertz technology and briefly discusses the use of terahertz imaging techniques in the detection of skin cancer. Research into the promise and perils of terahertz imaging will also be discussed.

Cardiovascular disease consistently occupies a prominent position among the leading global causes of mortality. Continuous and real-time monitoring of cardiovascular signs over an extended duration is necessary to identify irregularities and prompt timely intervention. Due to this reason, researchers have invested heavily in developing adaptive sensors that may be worn or implanted and continuously monitor numerous vital physiological characteristics. Mechanical sensors represent a category of devices capable of precisely capturing the temporal variations in pressure within the heart and arteries. Mechanical sensors possess inherent advantages such as exceptional precision and a wide range of adaptability. This article examines four distinct mechanical sensor technologies that rely on capacitive, piezoresistive, piezoelectric, and triboelectric principles. These technologies show great potential as novel approaches for monitoring the cardiovascular system. The subsequent section provides a comprehensive analysis of the biomechanical components of the cardiovascular system, accompanied by an in-depth examination of the methods employed to monitor these intricate systems. These systems measure blood and endocardial pressure, pulse wave, and heart rhythm. Finally, we discuss the potential benefits of continuing health monitoring in vascular disease treatment and the challenges of integrating it into clinical settings.

Powered exoskeleton technology helps turns dreams of recovering mobility after paralysis into reality. One of the most common problems encountered in the use of powered exoskeletons is the detection of the motion intentions of the user. Many approaches to conquering this problem have been developed using Electromyography (EMG) sensors, Electroencephalography (EEG) sensors, Center of Pressure (COP), and so forth. When a method, such as the surface EMG, is contaminated with noise during acquisition, it is important to process that raw EMG signal. Doing so usually takes time, and time delays in such a system can lead to a loss in synchronization between the wearer and the exoskeleton. Many algorithms have been developed for data acquisition and the filtering of raw EMG signals as well as accelerometer data. Our approach involves designing an almost sensor-less low limb exoskeleton that is powered by an electric Direct Current (DC) motor, and the same motor is used to detect motion via monitoring the voltage and the current variation. Experimental results are obtained for the actuating knee flexion-to-extension then extension-to-flexion of a sitting person using the National Instrument (NI) MyRIO as a data acquisition system with NI-LabView. The results support the hypothesis that the developed system can detect human motion and drive the motor in the necessary direction without the use of uncomfortable electrodes (sensors) and their connections. Additionally, the system supported the wearer to move his leg up (extension) without having too much effort to do so. In order to identify muscle activation with the change in the angle along the sagittal plane, an accelerometer has been attached to the system. The proposed approach could help open a new pathway along which researchers could develop low-cost and easy-to-wear powered exoskeletons which could emulate precisely the normal gait of a human.

The Covid-19 pandemic is the worst crisis the international tourism sector is facing, and UNWTO has revised its 2020 forecast. Full closure of borders led to a collapse in international tourism to Egypt with a loss in GDP and employment. UNWTO affirms that tourism will recover, but it won't be the same as before, which presents a gap to be filled. This paper aims to identify the changes in tourism industry components post COVID-19 pandemic as perceived by Egyptian Tour Operators. Survey data using questionnaires were collected from 373 employees. The results show that tourism will be more domestic, face mask and social distancing will become the new norm, tourist will choose hotels with an effective hygiene system, and health-check will be a must to enter airports and airplanes, which present a significant contribution to the understanding of the future of the tourism industry by policymakers, stakeholders and tourism researchers.