Fabricating orientated nanofibrous meshes with a bespoke ultra-cost-effective electrospinning machine.

Electrospinning's production method has been streamlined and perfected because to advancements in technology and increased demand. While working with electrospun fibers, it is crucial to ensure that they are collected in the correct orientation. Electrospun fibers can be either aligned or random. In contrast to randomly oriented fibers, all aligned ones will point in the same direction. Our results show that a low-cost, tailored electrospinning device can achieve equivalent performance to that of a commercially available system. High voltage (up to 36 kV) and nanofiber orientation adjustments are now being made to the proposed device. A high-voltage direct-current electrical power supply that is custom-built per order and wired by hand. Two specialized collectors, one portable and manufactured from conductive material for random nanofibers, and the other an inexpensive rotational drum collector for aligned nanofibers, have been developed to allow for precise orientation control. By applying Image J software to scanning electron micrographs, we were able to determine the average diameter and orientation of the fibers produced by the electrospinning apparatus, demonstrating its potential to produce nanoscale directed fibers. Because of this research, it's possible that schools will be able to afford an electrospinning system at a price far lower than the current market price.

IoT Solutions and AI-Based Frameworks for Masked-Face and Face Recognition to Fight the COVID-19 Pandemic.

A global health emergency resulted from the COVID-19 epidemic. Image recognition techniques are a useful tool for limiting the spread of the pandemic; indeed, the World Health Organization (WHO) recommends the use of face masks in public places as a form of protection against contagion. Hence, innovative systems and algorithms were deployed to rapidly screen a large number of people with faces covered by masks. In this article, we analyze the current state of research and future directions in algorithms and systems for masked-face recognition. First, the paper discusses the importance and applications of facial and face mask recognition, introducing the main approaches. Afterward, we review the recent facial recognition frameworks and systems based on Convolution Neural Networks, deep learning, machine learning, and MobilNet techniques. In detail, we analyze and critically discuss recent scientific works and systems which employ machine learning (ML) and deep learning tools for promptly recognizing masked faces. Also, Internet of Things (IoT)-based sensors, implementing ML and DL algorithms, were described to keep track of the number of persons donning face masks and notify the proper authorities. Afterward, the main challenges and open issues that should be solved in future studies and systems are discussed. Finally, comparative analysis and discussion are reported, providing useful insights for outlining the next generation of face recognition systems.

Social Media Devices' Influence on User Neck Pain during the COVID-19 Pandemic: Collaborating Vertebral-GLCM Extracted Features with a Decision Tree.

The prevalence of neck pain, a chronic musculoskeletal disease, has significantly increased due to the uncontrollable use of social media (SM) devices. The use of SM devices by younger generations increased enormously during the COVID-19 pandemic, being-in some cases-the only possibility for maintaining interpersonal, social, and friendship relationships. This study aimed to predict the occurrence of neck pain and its correlation with the intensive use of SM devices. It is based on nine quantitative parameters extracted from the retrospective X-ray images. The three parameters related to angle_1 (i.e., the angle between the global horizontal and the vector pointing from C7 vertebra to the occipito-cervical joint), angle_2 (i.e., the angle between the global horizontal and the vector pointing from C1 vertebra to the occipito-cervical joint), and the area between them were measured from the shape of the neck vertebrae, while the rest of the parameters were extracted from the images using the gray-level co-occurrence matrix (GLCM). In addition, the users' ages and the duration of the SM usage (H.mean) were also considered. The decision tree (DT) machine-learning algorithm was employed to predict the abnormal cases (painful subjects) against the normal ones (no pain). The results showed that angle_1, area, and the image contrast significantly increased statistically with the time of SM-device usage, precisely in the range of 2 to 9 h. The DT showed a promising result demonstrated by classification accuracy and F1-scores of 94% and 0.95, respectively. Our findings confirmed that the objectively detected parameters, which elucidate the negative impacts of SM-device usage on neck pain, can be predicted by DT machine learning.

Developments and Clinical Applications of Noninvasive Optical Technologies for Skin Cancer Diagnosis.

Skin cancer has shown a sharp increase in prevalence over the past few decades and currently accounts for one-third of all cancers diagnosed. The most lethal form of skin cancer is melanoma, which develops in 4% of individuals. The rising prevalence and increased number of fatalities of skin cancer put a significant burden on healthcare resources and the economy. However, early detection and treatment greatly improve survival rates for patients with skin cancer. Since the rising rates of both the incidence and mortality have been particularly noticeable with melanoma, significant resources have been allocated to research aimed at earlier diagnosis and a deeper knowledge of the disease. Dermoscopy, reflectance confocal microscopy, optical coherence tomography, multiphoton-excited fluorescence imaging, and dermatofluorescence are only a few of the optical modalities reviewed here that have been employed to enhance noninvasive diagnosis of skin cancer in recent years. This review article discusses the methodology behind newly emerging noninvasive optical diagnostic technologies, their clinical applications, and advantages and disadvantages of these techniques, as well as the potential for their further advancement in the future.

Biomechanical Sensing Systems for Cardiac Activity Monitoring.

Cardiovascular disease is consistently ranked high among the causes of death on a global scale. Monitoring of cardiovascular signs throughout the course of a long period of time and in real time is necessary in order to discover anomalies and begin early intervention at the appropriate time. To this purpose, a significant amount of interest among researchers has been directed toward the creation of flexible sensors that may be worn or implanted and are capable of constant, immediate observation of a variety of main physiological indicators. The real-time readings of the heart and arteries' pressure fluctuations can be reflected directly by mechanical sensors, which are one of the many types of sensors. Potential benefits of mechanical sensors include excellent accuracy and considerable versatility. Capacitive, piezoresistive, piezoelectric, and triboelectric principles are the foundations of the four types of mechanical sensors that are discussed in this article as recent developments for the purpose of monitoring the cardiovascular system. The biomechanical systems that are present in the cardiovascular system are then detailed, along with their monitoring, and this includes blood and endocardial pressure, pulse wave, and heart rhythm. In conclusion, we examine the usefulness of the use of continuous health monitoring for the treatment of vascular disease and highlight the difficulties associated with its translation into clinical practice.

Emerging Development of Auto-Charging Sensors for Respiration Monitoring.

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.

Validation of earlobe site as an alternative blood glucose testing approach.

BACKGROUND: Drawing blood from the fingertips for glucose testing is painful and likely to cause tissue damage over time. Earlobes are an alternative site for glucose measurement. OBJECTIVE: This work aims to validate the earlobe as an alternate test site for blood glucose testing by demonstrating valid and reliable statistically significant differences between the earlobes and standard reference sites. METHODS: Blood glucose concentrations from 50 volunteers were measured and statistically analysed from the reference sites (forearm and fingertip) and earlobe. The analysis included: 1) one-way analysis of variance (ANOVA), 2) regression analysis, 3) Bland Altman analysis, and 4) Clarke Error Grid analysis. RESULTS: The results indicated that there is no statistically significant difference between the three blood glucose-testing methods. For the forearm-earlobe and fingertip-earlobe, all measurements were grouped around the mean of 3.7 ± 1.96 SD and 2.96± 1.96 SD, respectively. Error grid analysis showed > 97% of all earlobe and references measurements fell in Zones A and B and were in the clinically acceptable level. CONCLUSIONS: The results have shown that the earlobe is a valid substitute for blood glucose measurements.

Recent Applications of Electrospun Nanofibrous Scaffold in Tissue Engineering.

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.

Autocharging Techniques for Implantable Medical Applications.

Implantable devices have successfully proven their reliability and efficiency in the medical field due to their immense support in a variety of aspects concerning the monitoring of patients and treatment in many ways. Moreover, they assist the medical field in disease diagnosis and prevention. However, the devices' power sources rely on batteries, and with this reliance, comes certain complications. For example, their depletion may lead to surgical interference or leakage into the human body. Implicit studies have found ways to reduce the battery size or in some cases to eliminate its use entirely; these studies suggest the use of biocompatible harvesters that can support the device consumption by generating power. Harvesting mechanisms can be executed using a variety of biocompatible materials, namely, piezoelectric and triboelectric nanogenerators, biofuel cells, and environmental sources. As with all methods for implementing biocompatible harvesters, some of them are low in terms of power consumption and some are dependent on the device and the place of implantation. In this review, we discuss the application of harvesters into implantable devices and evaluate the different materials and methods and examine how new and improved circuits will help in assisting the generators to sustain the function of medical devices.