مشخصات مقاله | |
ترجمه عنوان 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 |
انتشار | مقاله سال 2022 |
تعداد صفحات مقاله انگلیسی | 19 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله مروری (Review Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR – DOAJ – ISC |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
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 |
فرضیه | ندارد |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مهندسی فناوری اطلاعات، مهندسی پزشکی |
گرایش های مرتبط | اینترنت و شبکه های گسترده، شبکه های کامپیوتری، سایبرنتیک پزشکی |
نوع ارائه مقاله |
ژورنال |
مجله | مجله مهندسی عین شمس – Ain Shams Engineering Journal |
دانشگاه | School of Electronic and Electrical Engineering, University of Leeds, Leeds, UK |
کلمات کلیدی | 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 |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.asej.2021.101660 |
کد محصول | E15910 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
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 متن مقاله: |
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. |