مقاله انگلیسی مروری بر فناوری های توانمند برای اکوسیستم اینترنت اشیاء پزشکی
ترجمه نشده

مقاله انگلیسی مروری بر فناوری های توانمند برای اکوسیستم اینترنت اشیاء پزشکی

عنوان فارسی مقاله: مروری بر فناوری های توانمند برای اکوسیستم اینترنت اشیاء پزشکی (IoMT)
عنوان انگلیسی مقاله: A review of enabling technologies for Internet of Medical Things (IoMT) Ecosystem
مجله/کنفرانس: مجله مهندسی عین شمس - Ain Shams Engineering Journal
رشته های تحصیلی مرتبط: مهندسی فناوری اطلاعات، مهندسی پزشکی
گرایش های تحصیلی مرتبط: اینترنت و شبکه های گسترده، شبکه های کامپیوتری، سایبرنتیک پزشکی
کلمات کلیدی فارسی: اینترنت اشیا، دستگاه های جاسازی شده، شبکه های ناحیه بدن، نظارت از راه دور، سلامت الکترونیک و سلامت همراه، سیستم های زمان واقعی
کلمات کلیدی انگلیسی: IoT - Embedded Devices - Body Area Networks - Remote Monitoring - eHealth and mHealth - Real-Time Systems
نوع نگارش مقاله: مقاله مروری (Review Article)
نمایه: Scopus - Master Journals List - JCR - DOAJ - ISC
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.asej.2021.101660
دانشگاه: School of Electronic and Electrical Engineering, University of Leeds, Leeds, UK
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2022
ایمپکت فاکتور: 3.763 در سال 2020
شاخص H_index: 46 در سال 2021
شاخص SJR: 0.505 در سال 2020
شناسه ISSN: 2090-4479
شاخص Quartile (چارک): Q2 در سال 2020
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 19
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
آیا این مقاله فرضیه دارد: ندارد
کد محصول: E15910
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract


Keywords


1. Introduction


2. Sensors


3. Wireless Communication Technologies


4. Cloud Computing


5. Machine Learning Techniques


6. Fog/Edge Computing


7. Applications


8. Conclusion


Declaration of Competing Interest


References


Vitae

بخشی از مقاله (انگلیسی)

Abstract


The goal of Internet of Medical Things (IoMT) and digital healthcare systems is to provide people with the ease of receiving quality healthcare at the comfort of their homes. Hence, the aim of IoMT is the ubiquitous deployment of home-based healthcare systems. Making such systems intelligent and efficient for timely prediction of critical diseases can save millions of lives while simultaneously reducing the burden on the traditional healthcare systems e.g., hospitals. The advancement in IoT has enabled both patients and doctors to access real time data. This advancement has reduced the cost and energy consumption of digital healthcare systems by using efficient sensors and communication technologies. This paper provides a comprehensive review of various studies conducted for the development and improvement of IoMT. It analyses different sensors used for measurement of various parameters ranging from physiological to emotional signals. It also provides a detailed investigation of different communication technologies being used, their advantages, and limitations. Moreover, digital healthcare systems are now deploying machine learning technology for the prediction of health status of patients. These techniques and algorithms are also discussed. Data security and prediction accuracy are the main concerns in the development of this area. In conclusion, this paper reviews the various digital system designs in the context of healthcare, their methodology, limitations, and the present challenges faced by the e-health sector.


 


1. Introduction


Quality healthcare is a basic human right, but one which fails to be provided adequately worldwide. The economic, environmental, and social development of this world and subsequent lifestyle changes have led to a drastic increase in chronic diseases such as heart disease, cancer, and diabetes. These chronic illnesses symbolize the greatest threat to human health. Moreover, each time an infectious disease breaks out, the hospitals are flooded with people which takes a huge toll on healthcare services. For example, currently there is a continuous stress on the worlds healthcare resources with the rampant spread of COVID-19. This kind of situation leads to inefficiency in managing patients and their data.

Experts believe that digital healthcare systems in Internet of Things (IoT) environments seem to be a compelling solution to this major healthcare problem. The building blocks and general architecture of a system in the IoT environment is shown in Fig. 1. In the context of medical services, the traditionally proposed remote health monitoring system architectures are divided into three layers: the vitals data collection layer from sensors; the transmission layer; and the analysis layer. The collection layer consists of sensors in the body area network (BAN). BAN collects the sensor data and transmits it to a gateway node. The transmission layer stores that data and analyzes it using conventional threshold values to report any abnormality. Additionally, the data may also be sent to the cloud for storage and heavy computations.

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