Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Nov 25, 2020)
Date Submitted: Sep 10, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Intelligent Isolation medical observation management system based on Internet of things
ABSTRACT
Background:
Since the new coronavirus infection was found in December 2019, it has caused a large-scale spread in the world. By zero o'clock on May 24, 2020, the total number of confirmed cases in the world has exceeded 5.3 million and the number of deaths has exceeded 340000. Considering the characteristics of the new coronavirus, such as strong infectivity and long incubation period, it is very important to isolate and observe the suspicious population all day and find the suspected cases with symptoms as soon as possible.
Objective:
To use remote monitoring of vital signs such as body temperature and cough, avoid traditional on-site medical observation, and effectively reduce the workload of medical staff and the risk of infection.
Methods:
The Internet of things isolation medical observation system based on wristwatch was established. The system consists of six modules: equipment management, vital signs monitoring, remote control, early warning report, statistical analysis and multi organization user management. Generally speaking, it can collect, transmit, store and analyze the location, temperature, blood oxygen, blood pressure, heart rate, respiratory rate, cough and other vital sign information of the observed population in real time by using the wristwatch with built-in sensors, mobile Internet and cloud based database management, and give early warning for suspicious situations.
Results:
This highly customizable report design makes it easy to be embedded into the third-party management system, so that further analysis, early warning and prediction modules can be built in a larger population. Managers can log in to the platform or mobile app to monitor and manage the observed personnel. Their user-friendly interface is intuitive and easy to navigate, which will ultimately help save time and resources, and more importantly, reduce the occupational exposure risk of medical personnel.
Conclusions:
The wristwatch based medical isolation observation system can be used to screen the new coronavirus infection, which is stable and reliable.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.