论文标题

使用智能手机嵌入式传感器诊断冠状病毒19诊断冠状病毒19的新型框架:设计研究

A Novel AI-enabled Framework to Diagnose Coronavirus COVID 19 using Smartphone Embedded Sensors: Design Study

论文作者

Maghdid, Halgurd S., Ghafoor, Kayhan Zrar, Sadiq, Ali Safaa, Curran, Kevin, Rawat, Danda B., Rabie, Khaled

论文摘要

冠状病毒是一种著名的病毒家族,在人和动物中引起疾病​​。新型冠状病毒Covid-19首先在中国武汉发现。但是,最近,该病毒已在世界上大部分地区广泛传播,并根据世界卫生组织(WHO)引起大流行。此外,如今,所有世界国家都在努力控制Covid-19。有许多检测冠状病毒的机制,包括对胸部CT扫描图像和血液测​​试结果的临床分析。确认的Covid-19患者表现为发烧,疲倦和干咳嗽。特别是,可以使用几种技术来检测病毒的初始结果,例如医疗检测试剂盒。但是,这样的设备会产生巨大的成本,需要时间安装它们并使用。因此,在本文中,提出了一个新的框架,以使用内置智能手机传感器检测COVID-19。该提案提供了低成本的解决方案,因为大多数放射科医生已经持有不同日常用途的智能手机。不仅如此,而且普通人还可以将其智能手机框架用于病毒检测目的。如今,智能手机具有现有计算的处理器,内存空间和大量传感器,包括相机,麦克风,温度传感器,惯性传感器,接近性,颜色传感器,湿度传感器和无线芯片组/传感器。设计的人工智能(AI)启用框架读取智能手机传感器信号测量值,以预测肺炎的严重程度,并预测疾病的结果。

Coronaviruses are a famous family of viruses that cause illness in both humans and animals. The new type of coronavirus COVID-19 was firstly discovered in Wuhan, China. However, recently, the virus has widely spread in most of the world and causing a pandemic according to the World Health Organization (WHO). Further, nowadays, all the world countries are striving to control the COVID-19. There are many mechanisms to detect coronavirus including clinical analysis of chest CT scan images and blood test results. The confirmed COVID-19 patient manifests as fever, tiredness, and dry cough. Particularly, several techniques can be used to detect the initial results of the virus such as medical detection Kits. However, such devices are incurring huge cost, taking time to install them and use. Therefore, in this paper, a new framework is proposed to detect COVID-19 using built-in smartphone sensors. The proposal provides a low-cost solution, since most of radiologists have already held smartphones for different daily-purposes. Not only that but also ordinary people can use the framework on their smartphones for the virus detection purposes. Nowadays Smartphones are powerful with existing computation-rich processors, memory space, and large number of sensors including cameras, microphone, temperature sensor, inertial sensors, proximity, colour-sensor, humidity-sensor, and wireless chipsets/sensors. The designed Artificial Intelligence (AI) enabled framework reads the smartphone sensors signal measurements to predict the grade of severity of the pneumonia as well as predicting the result of the disease.

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