Recipient
Carleton UniversityDepartment
National Research Council CanadaAmount
$70.0K
Province
ONType
Grant
Agreement Number
172-2020-2021-Q3-960943
Purpose
The Project consists of two components: AI-enabled cough diagnostics: Cough is a symptom and mechanism for COVID-19 and viral spread. This project aims to distinguish cough types (dry, wet, wheeze and whooping) with data-driven approaches on previously collected cough data. The Recipient will collaborate with the NRC to integrate the models within a system for clinical validation. The COVID-19 cough will be explored to understand if there are unique features. Multimodal contactless vital signs monitoring: Thermal and Red Green Blue (RGB) imaging have the potential to be used for non-contact assessment of vital signs (heart rate and respiration rate) through measurement of small changes in temperature or skin color. The Recipient has prior experience using thermal and RGB cameras within residential settings and will apply this to public space applications. The Recipient will compare the performance of the cameras individually and in combination using pre-existing and/or new datasets.
Carleton University × National Research Council Canada
85 grants totalling $13.1M
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
1,000 grants totalling $355.2M
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