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A Novel AI-enabled Framework to Diagnose Coronavirus COVID 19 using Smartphone Embedded Sensors: Design Study
arXiv - CS - Machine Learning Pub Date : 2020-03-16 , DOI: arxiv-2003.07434 Halgurd S. Maghdid and Kayhan Zrar Ghafoor and Ali Safaa Sadiq and Kevin Curran and Danda B. Rawat and Khaled Rabie
arXiv - CS - Machine Learning Pub Date : 2020-03-16 , DOI: arxiv-2003.07434 Halgurd S. Maghdid and Kayhan Zrar Ghafoor and Ali Safaa Sadiq and Kevin Curran and Danda B. Rawat and Khaled Rabie
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.
更新日期:2020-06-02