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Objective Assessment of Covid-19 Severity Affecting the Vocal and Respiratory System Using a Wearable, Autonomous Sound Collar.
Ishac, D; Matta, S; Bin, S; Aziz, H; Karam, E; Abche, A; Nassar, G.
Afiliación
  • Ishac D; Electrical Engineering Department, University of Balamand (UOB), Balamand, Lebanon.
  • Matta S; Electrical Engineering Department, University of Balamand (UOB), Balamand, Lebanon.
  • Bin S; College of Physics, University of Qingdao, Qingdao, China.
  • Aziz H; Department of Pulmonary Pathology, Sahlgrenska University Hospital, Göteborg, Sweden.
  • Karam E; Electrical Engineering Department, University of Balamand (UOB), Balamand, Lebanon.
  • Abche A; Electrical Engineering Department, University of Balamand (UOB), Balamand, Lebanon.
  • Nassar G; IEMN - CNRS UMR 8520-INSA (HdF)-Lille academic, Lille, France.
Cell Mol Bioeng ; 15(1): 67-86, 2022 Feb.
Article en En | MEDLINE | ID: mdl-34777597
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. Supplementary Information: The online version contains supplementary material available at 10.1007/s12195-021-00712-w.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cell Mol Bioeng Año: 2022 Tipo del documento: Article País de afiliación: Líbano Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cell Mol Bioeng Año: 2022 Tipo del documento: Article País de afiliación: Líbano Pais de publicación: Estados Unidos