BioSenHealth 1.0: A Novel Internet of Medical Things (IoMT)-Based Patient Health Monitoring System

Engineered two-dimensional nanomaterials based diagnostics integrated with internet of medical things (IoMT) for COVID-19

More than four years have passed since an inimitable coronavirus disease (COVID-19) pandemic hit the globe in 2019 after an uncontrolled transmission of the severe acute respiratory syndrome (SARS-CoV-2) infection. The occurrence of this highly contagious respiratory infectious disease led to chaos and mortality all over the world. The peak paradigm shift of the researchers was inclined towards the accurate and rapid detection of diseases. Since 2019, there has been a boost in the diagnostics of COVID-19 via numerous conventional diagnostic tools like RT-PCR, ELISA, etc., and advanced biosensing kits like LFIA, etc. For the same reason, the use of nanotechnology and two-dimensional nanomaterials (2DNMs) has aided in the fabrication of efficient diagnostic tools to combat COVID-19. This article discusses the engineering techniques utilized for fabricating chemically active E2DNMs that are exceptionally thin and irregular. The techniques encompass the introduction of heteroatoms, intercalation of ions, and the design of strain and defects. E2DNMs possess unique characteristics, including a substantial surface area and controllable electrical, optical, and bioactive properties. These characteristics enable the development of sophisticated diagnostic platforms for real-time biosensors with exceptional sensitivity in detecting SARS-CoV-2. Integrating the Internet of Medical Things (IoMT) with these E2DNMs-based advanced diagnostics has led to the development of portable, real-time, scalable, more accurate, and cost-effective SARS-CoV-2 diagnostic platforms. These diagnostic platforms have the potential to revolutionize SARS-CoV-2 diagnosis by making it faster, easier, and more accessible to people worldwide, thus making them ideal for resource-limited settings. These advanced IoMT diagnostic platforms may help with combating SARS-CoV-2 as well as tracking and predicting the spread of future pandemics, ultimately saving lives and mitigating their impact on global health systems.

Multirole of the internet of medical things (IoMT) in biomedical systems for managing smart healthcare systems: An overview of current and future innovative trends

Internet of Medical Things (IoMT) is an emerging subset of Internet of Things (IoT), often called as IoT in healthcare, refers to medical devices and applications with internet connectivity, is exponentially gaining researchers' attention due to its wide-ranging applicability in biomedical systems for Smart Healthcare systems. IoMT facilitates remote health biomedical system and plays a crucial role within the healthcare industry to enhance precision, reliability, consistency and productivity of electronic devices used for various healthcare purposes. It comprises a conceptualized architecture for providing information retrieval strategies to extract the data from patient records using sensors for biomedical analysis and diagnostics against manifold diseases to provide cost-effective medical solutions, quick hospital treatments, and personalized healthcare. This article provides a comprehensive overview of IoMT with special emphasis on its current and future trends used in biomedical systems, such as deep learning, machine learning, blockchains, artificial intelligence, radio frequency identification, and industry 5.0.

GSM and Arduino Based Vital Sign Monitoring System

Aims:

Analysis of the vital signs of patients can aid in early disease diagnosis and care. There are many illnesses which can be diagnosed and managed by monitoring this medical information periodically.

Background:

Detection of various early-stage medical diseases can be simply done by monitoring Human vital signs, as they show the standard body's essential functions, indicating the status of an individual's health condition.

Objective:

In many cases it so happens that patients do not receive appropriate medical treatment on time, as a result of which unexpected incidents happen due to ignorance of one’s health status. Since pulse rate and vital sign area unit are the foremost crucial parameters, an affordable device to detect such parameters is useful for human health.

Methods:

Photoplethysmography (PPG) is a photosensitive technique that measures difference in blood volume of the pulse (usually in the body's soft tissues) by specifically interfering with the differences in the photo-emitter's absorption, reflection, volume and dispersion of light, and then it is registered by the photoreceptor. Then, the PPG waveform reflects shifts in arterial blood supply. The waveform obtained with a pulse oximeter illuminates skin and processes variations in the absorption of light.

Results:

The embedded systems-Arduino, GSM module and the various sensors used in this research provide a simple monitoring method which does not require a smartphone or internet connectivity.

Conclusion:

This paper aims at illustrating the significance of constantly monitoring vital signs. The device proposed has been developed as an Arduino program that is straightforward and inexpensive, a conveyable system that acquires the vital signs data and sends a text message as warning messages during a health emergency.

On Development of MySignals based prototype for application in health vitals monitoring

India's health infrastructure is under pressure since the daily COVID-19 cases have crossed the milestone of 4 Lakhs cases per day which surpass the previous years' peak. Patients with mild symptoms have been advised for home treatment since most of the hospitals are running out of bed. In this situation delivering healthcare to people has become revolutionizing due to the rapid advancement of embedded systems, communication, and informatics technologies. Integration of different health sensors, handheld devices, and internet can be a great potential for significant improvement of the quality of remote healthcare. This paper discusses the use of MySignals HW shield which is a hardware development platform for medical devices to build e-health monitoring system. Wearable health monitoring system prototype has been developed in this work. To conduct experiments, health vitals such as body temperature, ECG, oxygen saturation level, and pulse rate from 5 volunteers have been measured, collected, and stored in a cloud database using the system prototype. To evaluate the performance of the prototype, transmission delay has been recorded in both wired (Ethernet) and wireless (Wi-Fi) communication modes. It is observed that it takes 2.71 ms and 5.18 ms of time to collect and store the health vitals to the cloud database in wired and wireless mode respectively. Comparing the collected health vitals with the normal range of health vitals, no abnormality is found in all volunteer's health. Finally, a framework for contactless monitoring of COVID-affected patients is proposed. Contactless monitoring of health vitals can reduce the chance of community spread.

Analysis of physical health with internet of things-based computational narrowband physical health framework

BACKGROUND

Physical health is vital to the improvement of our skills and the enhancement of eye movements. The coordination of good body movement helps to establish a safe position of the body. The challenging characteristics of physical education include insufficient time allocation, inadequately trained teachers, and inadequate provision of the equipment is considered as an important factor.

OBJECTIVE

In this paper, IoT-based Computational Narrowband Physical Health Framework (IoT-CNPHF) has been proposed to strengthen adequate time allocation, appropriately qualified teachers, and sustainable provision in the physical education system.

METHOD

Massive extended range analysis is introduced to enhance the duration and time allotted for physical activity that helps in creating awareness about the importance of physical activities and sports in our daily life. The multimodal supervised technique is incorporated with IoT-CNPHF to improve the knowledge of physical education for the teachers and to provide suitable provision for students in the physical education system.

RESULTS

The simulation analysis is performed based on accuracy, performance, and its efficiency proves the reliability of the proposed framework.