{"title":"Voice Analysis Framework for Asthma-COVID-19 Early Diagnosis and Prediction: AI-based Mobile Cloud Computing Application","authors":"A. O. Popadina, Al‐Majeed Salah, Karami Jalal","doi":"10.1109/ElConRus51938.2021.9396367","DOIUrl":null,"url":null,"abstract":"Asthma patients come through coronavirus with higher risk, where both COVID-19 and asthma cause changes in vocal patterns, which can be detected in different ways. Monitoring systems focused on asthmatic voice quality for diagnosis are essential. However, voice monitoring has the potential to be the most accurate tool for lung early prediction of the disease. Asthma patient has a peak flow meter for daily use as an alternative for disease state monitoring, which has no special devices to detect COVID-19. This paper considers mixture methods of voice analysis for early diseases detection and their perspectives in developing for asthma and COVID-19 application, based diagnostics recognition. Mobile Cloud Computing and Artificial Intelligence used into analysis of voice parameters suitable to design an asthma oriented system for both attack prediction and COVID-19 recognition.","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ElConRus51938.2021.9396367","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Asthma patients come through coronavirus with higher risk, where both COVID-19 and asthma cause changes in vocal patterns, which can be detected in different ways. Monitoring systems focused on asthmatic voice quality for diagnosis are essential. However, voice monitoring has the potential to be the most accurate tool for lung early prediction of the disease. Asthma patient has a peak flow meter for daily use as an alternative for disease state monitoring, which has no special devices to detect COVID-19. This paper considers mixture methods of voice analysis for early diseases detection and their perspectives in developing for asthma and COVID-19 application, based diagnostics recognition. Mobile Cloud Computing and Artificial Intelligence used into analysis of voice parameters suitable to design an asthma oriented system for both attack prediction and COVID-19 recognition.