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1.
International Journal of System Dynamics Applications ; 11(5):12, 2022.
Artigo em Inglês | Web of Science | ID: covidwho-1744840

RESUMO

This study is focussed on the design and modelling of a low-cost ventilator design that can be developed using locally sourced materials in Nigeria. This is meant to aid in the country's fight against the current COVID-19 pandemic where there is a shortage of ventilators. The ventilator design in this research was based on a mechanical AMBU bag compression principle using the volume-control ventilation (VCV) mode, which will eliminate the need for manual compression, which can be tedious and uncontrolled. The design is powered by an electric motor with variable speed and tidal volume control. It also features an alarm that alerts medical personnel of unstable conditions in the system parameters. This prototype shows that the mechanical compression systems is a viable and more economical option that provides the essential features required in the standard existing technologies.

2.
Lecture Notes on Data Engineering and Communications Technologies ; 86:283-293, 2022.
Artigo em Inglês | Scopus | ID: covidwho-1739276

RESUMO

COVID-19 since its discovery and spread have caused major disruption in the regular operation of the industries, schools, universities, business, and hospitals and eventually to the national economy of many countries. It is a highly contagious disease and spreading among communities at a very fast pace. Early detection of COVID-19 infected patients and quarantining them are few possible measures to restrict its spread. Persons infected by COVID-19 demonstrate many symptoms. However, these symptoms are somewhat similar to some of the common diseases like a common cold, viral fever, and body ache which we generally face in our day-to-day life. Hence, most of the medical experts confuse COVID-19 with some very common diseases, and when the actual cause is known by that time the situation becomes worse. In this light, this study proposed a new concept based on soft computing techniques to determine the exact symptoms responsible for COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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