Fully Automated AI-powered Contactless Cough Detection based on Pixel Value Dynamics Occurring within Facial Regions

Maciej Szankin; Alicja Kwaśniewska; Natalia Kowalczyk; Jacek Rumiński; Rey Nicolas; David Gamba

doi:10.1109/hsi52170.2021.9538788

Fully Automated AI-powered Contactless Cough Detection based on Pixel Value Dynamics Occurring within Facial Regions

Abstract

Increased interest in non-contact evaluation of the health state has led to higher expectations for delivering automated and reliable solutions that can be conveniently used during daily activities. Although some solutions for cough detection exist, they suffer from a series of limitations. Some of them rely on gesture or body pose recognition, which might not be possible in cases of occlusions, closer camera distances or impediments that prevent users from performing such movements at all. Others focus on analyzing breath using audio recordings, which cannot be easily applied in crowded or loud spaces. Many of them utilize visible light data which is prone to changing lighting conditions and can lead to various privacy concerns. Taking these into account, we propose to make use of the temporal pixel value changes occurring within specific facial areas. Due to the use of a combination of object detection and signal classification models, our system allows for fully automated classification of breathing anomalies. The benchmark evaluation performed on the newly created thermal cough data set proved the reliability of the introduced solution (precision of cough detection equals 94%). Due to the use of a lightweight deep learning model, the proposed system also has huge practical value, as it can potentially be deployed on edge devices frequently sought out in markets such as autonomous vehicles, drones, smart home or military applications.

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Authors (6)

Maciej Szankin mgr inż.
Alicja Kwaśniewska mgr inż
Natalia Kowalczyk (formerly: Natalia Głowacka) mgr inż.
Jacek Rumiński prof. dr hab. inż.
Rey Nicolas
David Gamba

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Category:: Conference activity
Type:: publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Title of issue:: 2021 14th International Conference on Human System Interaction (HSI) strony 1 - 7
Language:: English
Publication year:: 2021
Bibliographic description:: Szankin M., Kwaśniewska A., Głowacka N., Rumiński J., Nicolas R., Gamba D.: Fully Automated AI-powered Contactless Cough Detection based on Pixel Value Dynamics Occurring within Facial Regions// 2021 14th International Conference on Human System Interaction (HSI)/ : , 2021, s.1-7
DOI:: Digital Object Identifier (open in new tab) 10.1109/hsi52170.2021.9538788
Verified by:: Gdańsk University of Technology