Grant: Alliance Grants
Ryerson University
$50,000.00
COVID-19 - AI Based Screening and Monitoring of COVID-19 Respiration Patterns using Acoustic Sensors
EF 2020-21
Résumé
As COVID-19 testing and symptom monitoring in communities have been in extremely high demand, it is now an urgency and priority to develop a fast and convenient way to conduct preliminary COVID-19 screening. In this project, we aim to develop an AI based algorithm and system that can perform screenings of respiration patterns for COVID-19 infections through acoustic sensors, e.g., microphone/sound recorders. The acoustic sensors record the breathing sounds in real-time. The resulting product can perform fast real-time preliminary COVID-19 screening and monitoring on large-scale populations at home or in group settings like senior care centers. Such products can potentially help the government distribute COVID-19 related medical supplies more efficiently by prioritizing testing and treatment to the individuals with high probabilities of COVID-19 infection and respiration symptoms. By working with our highly qualified team at Ryerson University and with our partner organization, AltumView, the research outcome of this innovative project can timely meet the urgent COVID-19 healthcare demands and significantly benefit Canadian society as well as the economy.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
550079-2020
Name nom
Zhang, Xiao-Ping
Department département
Electrical, Computer and Biomedical Engineering
Organization id
43
Institution établissement
Ryerson University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2020
Award amount
50000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1101
Area of application group en
Health, education and social services
Area of application group fr
Santé publique, éducation et services sociaux
Area of application en
Human health (including medically-related psychological research)
Area of application fr
Santé publique (y compris recherche psychologique liée à la médecine)
Research subject code
2514
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Digital signal processing
Research subject fr
Traitement des signaux numériques
Installment
inst:1 - 1
Partie
1
Nb partie
1
Application title
COVID-19 - AI Based Screening and Monitoring of COVID-19 Respiration Patterns using Acoustic Sensors
Keyword
NSERC
Application summary
As COVID-19 testing and symptom monitoring in communities have been in extremely high demand, it is now an urgency and priority to develop a fast and convenient way to conduct preliminary COVID-19 screening. In this project, we aim to develop an AI based algorithm and system that can perform screenings of respiration patterns for COVID-19 infections through acoustic sensors, e.g., microphone/sound recorders. The acoustic sensors record the breathing sounds in real-time. The resulting product can perform fast real-time preliminary COVID-19 screening and monitoring on large-scale populations at home or in group settings like senior care centers. Such products can potentially help the government distribute COVID-19 related medical supplies more efficiently by prioritizing testing and treatment to the individuals with high probabilities of COVID-19 infection and respiration symptoms. By working with our highly qualified team at Ryerson University and with our partner organization, AltumView, the research outcome of this innovative project can timely meet the urgent COVID-19 healthcare demands and significantly benefit Canadian society as well as the economy.
