ROMJIST Volume 23, No. S, 2020, pp. S77-S88
Gheorghe POP, Horia CUCU, Dragoş BURILEANU and Corneliu BURILEANU Cough Sound Recognition in Respiratory Disease Epidemics
ABSTRACT: The new coronavirus epidemic, which outbroke in 2019, has now grown into a full-blown pandemic, raising global concerns by its high infection speed and mortality rate. People developing the disease fill emergency hospitals, while the problem may deepen if worried general population cluster emergency rooms just for diagnosis. To control such respiratory disease epidemic, governments and medical staff usually decide to reduce virus transmission by enforcing social distance and placing in quarantine all persons suspected of carrying the virus. Everyone else is asked to stay insulated as long as possible, and refrain from calling emergency services unless relevant symptoms appear. With the medical staff shortage forced by such an epidemic, it would be very useful to have a diagnosis system capable of checking people for symptoms. As the direct contact of patients with objects used in common may raise virus transmission concerns, non-contact devices are accepted for use in evaluating a person’s health condition. Under these limitations, we present a cough sound recognition method, which, as new relevant data become available, can be extended to work more as a respiratory disease diagnostic tool.KEYWORDS: neural computing, respiratory disease epidemics, cough sound recognitionRead full text (pdf)