Wearable continuous glucose monitoring sensors: A revolution in diabetes treatment

Worldwide, the number of people affected by diabetes is rapidly increasing due to aging populations and sedentary lifestyles, with the prospect of exceeding 500 million cases in 2030, resulting in one of the most challenging socio-health emergencies of the third millennium. Daily management of diabetes by patients relies on the capability of correctly measuring glucose concentration levels in the blood by using suitable sensors. In recent years, glucose monitoring has been revolutionized by the development of Continuous Glucose Monitoring (CGM) sensors, wearable non/minimally-invasive devices that measure glucose concentration by exploiting different physical principles, e.g., glucose-oxidase, fluorescence, or skin dielectric properties, and provide real-time measurements every 1–5 min. CGM opened new challenges in different disciplines, e.g., medicine, physics, electronics, chemistry, ergonomics, data/signal processing, and software development to mention but a few. This paper first makes an overview of wearable CGM sensor technologies, covering both commercial devices and research prototypes. Then, the role of CGM in the actual evolution of decision support systems for diabetes therapy is discussed. Finally, the paper presents new possible horizons for wearable CGM sensor applications and perspectives in terms of big data analytics for personalized and proactive medicine

Smart Health Internet of Thing for Continuous Glucose Monitoring: a Survey

Health monitoring system allows patients to monitor the health-related problem to avoid further complications which could result in loss of life. Smart health is one of the categories of a health monitoring system that uses Smartphone’s and sensors to effectively monitor patient health status. However, the smart health internet of thing methods for glucose monitoring still does not provide accurate glucose reading. Hence, diabetes patient can easily loss life. To help understand this challenge, a comprehensive survey focused on smart health internet of thing methods for continuous glucose monitoring was conducted. The paper discusses the benefit and challenge of each method applicable to glucose monitoring. It was observed that several smart health methods required sensor to function. Smart vehicles and remote monitoring have less attention. However, when accommodates can provide future opportunities

How 5G wireless (and concomitant technologies) will revolutionize healthcare?

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution

Designing the Health-related Internet of Things: Ethical Principles and Guidelines

The conjunction of wireless computing, ubiquitous Internet access, and the miniaturisation of sensors have opened the door for technological applications that can monitor health and well-being outside of formal healthcare systems. The health-related Internet of Things (H-IoT) increasingly plays a key role in health management by providing real-time tele-monitoring of patients, testing of treatments, actuation of medical devices, and fitness and well-being monitoring. Given its numerous applications and proposed benefits, adoption by medical and social care institutions and consumers may be rapid. However, a host of ethical concerns are also raised that must be addressed. The inherent sensitivity of health-related data being generated and latent risks of Internet-enabled devices pose serious challenges. Users, already in a vulnerable position as patients, face a seemingly impossible task to retain control over their data due to the scale, scope and complexity of systems that create, aggregate, and analyse personal health data. In response, the H-IoT must be designed to be technologically robust and scientifically reliable, while also remaining ethically responsible, trustworthy, and respectful of user rights and interests. To assist developers of the H-IoT, this paper describes nine principles and nine guidelines for ethical design of H-IoT devices and data protocols

Research Opportunities and Visions for Smart and Pervasive Health

Improving the health of the nation's population and increasing the capabilities of the US healthcare system to support diagnosis, treatment, and prevention of disease is a critical national and societal priority. In the past decade, tremendous advances in expanding computing capabilities--sensors, data analytics, networks, advanced imaging, and cyber-physical systems--have, and will continue to, enhance healthcare and health research, with resulting improvements in health and wellness. However, the cost and complexity of healthcare continues to rise alongside the impact of poor health on productivity and quality of life. What is lacking are transformative capabilities that address significant health and healthcare trends: the growing demands and costs of chronic disease, the greater responsibility placed on patients and informal caregivers, and the increasing complexity of health challenges in the US, including mental health, that are deeply rooted in a person's social and environmental context.Comment: A Computing Community Consortium (CCC) white paper, 12 page

E-health-IoT Universe: A Review

The Internet of Things (IoT) devices are able to collect and share data directly with other devices through the cloud environment, providing a huge amount of information to be gathered, stored and analyzed for data-analytics processes. The scenarios in which the IoT devices may be useful are amazing varying, from automotive, to industrial automation or remote monitoring of domestic environment. Furthermore, has been proved that healthcare applications represent an important field of interest for IoT devices, due to the capability of improving the access to care, reducing the cost of healthcare and most importantly increasing the quality of life of the patients. In this paper, we analyze the state-of-art of IoT in medical environment, illustrating an extended range of IoT-driven healthcare applications that, however, still need innovative and high technology-based solutions to be considered ready to market. In particular, problems regarding characteristics of response-time and precision will be examined.  Furthermore, wearable and energy saving properties will be investigated in this paper and also the IT architectures able to ensure security and privacy during the all data-transmission process. Finally, considerations about data mining applications, such as risks prediction, classification and clustering will be provided, that are considered fundamental issues to ensure the accuracy of the care processes

Cushing's Disease Management: Glimpse Into 2051

Major advancements are expected in medicine and healthcare in the 21st century- "Digital Age", mainly due to the application of data technologies and artificial intelligence into healthcare. In this perspective article we share a short story depicting the future Cushings' Disease patient and the postulated diagnostic and management approaches. In the discussion, we explain the advances in recent times which makes this future state plausible. We postulate that endocrinology care will be completely reinvented in the Digital Age

Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges

Chronic diseases are becoming more widespread. Treatment and monitoring of these diseases require going to hospitals frequently, which increases the burdens of hospitals and patients. Presently, advancements in wearable sensors and communication protocol contribute to enriching the healthcare system in a way that will reshape healthcare services shortly. Remote patient monitoring (RPM) is the foremost of these advancements. RPM systems are based on the collection of patient vital signs extracted using invasive and noninvasive techniques, then sending them in real-time to physicians. These data may help physicians in taking the right decision at the right time. The main objective of this paper is to outline research directions on remote patient monitoring, explain the role of AI in building RPM systems, make an overview of the state of the art of RPM, its advantages, its challenges, and its probable future directions. For studying the literature, five databases have been chosen (i.e., science direct, IEEE-Explore, Springer, PubMed, and science.gov). We followed the (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) PRISMA, which is a standard methodology for systematic reviews and meta-analyses. A total of 56 articles are reviewed based on the combination of a set of selected search terms including RPM, data mining, clinical decision support system, electronic health record, cloud computing, internet of things, and wireless body area network. The result of this study approved the effectiveness of RPM in improving healthcare delivery, increase diagnosis speed, and reduce costs. To this end, we also present the chronic disease monitoring system as a case study to provide enhanced solutions for RPMsThis research work was partially supported by the Sejong University Research Faculty Program (20212023)S