Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/5346
Title: Objective Assessment of Covid-19 Severity Affecting the Vocal and Respiratory System Using a Wearable, Autonomous Sound Collar
Authors: Ishac, D
Matta, S
Bin, S
Aziz, H
Karam, Elie 
Abche, Antoine 
Nassar, G
Affiliations: Department of Electrical Engineering 
Department of Electrical Engineering 
Keywords: Autonomous sound systems
Covid-19
Electromechanical sensors
Mechanical variables measurement
Sound signal processing
Issue Date: 2022-02
Publisher: Springer
Part of: Cellular and Molecular Bioengineering
Volume: 15
Issue: 67
Start page: 86
Abstract: 
Introduction
Since the outbreak began in January 2020, Covid-19 has affected more than 161 million people worldwide and resulted in about 3.3 million deaths. Despite efforts to detect human infection with the virus as early as possible, the confirmatory test still requires the analysis of sputum or blood with estimated results available within approximately 30 minutes; this may potentially be followed by clinical referral if the patient shows signs of aggravated pneumonia. This work aims to implement a soft collar as a sound device dedicated to the objective evaluation of the pathophysiological state resulting from dysphonia of laryngeal origin or respiratory failure of inflammatory origin, in particular caused by Covid-19.

Methods
In this study, we exploit the vibrations of waves generated by the vocal and respiratory system of 30 people. A biocompatible acoustic sensor embedded in a soft collar around the neck collects these waves. The collar is also equipped with thermal sensors and a cross-data analysis module in both the temporal and frequency domains (STFT). The optimal coupling conditions and the electrical and dimensional characteristics of the sensors were defined based on a mathematical approach using a matrix formalism.

Results
The characteristics of the signals in the time domain combined with the quantities obtained from the STFT offer multidimensional information and a decision support tool for determining a pathophysiological state representative of the symptoms explored. The device, tested on 30 people, was able to differentiate patients with mild symptoms from those who had developed acute signs of respiratory failure on a severity scale of 1 to 10.

Conclusion
With the health constraints imposed by the effects of Covid-19, the heavy organization to be implemented resulting from the flow of diagnostics, tests and clinical management, it was urgent to develop innovative and safe biomedical technologies. This passive listening technique will contribute to the non-invasive assessment and dynamic observation of lesions. Moreover, it merits further examination to provide support for medical operators to improve clinical management.
URI: https://scholarhub.balamand.edu.lb/handle/uob/5346
ISSN: 1865-5025
DOI: 10.1007/s12195-021-00712-w
Ezproxy URL: Link to full text
Type: Journal Article
Appears in Collections:Department of Electrical Engineering

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