Remote Analysis of Respiratory Sounds in Patients With COVID-19: Development of Fast Fourier Transform-Based Computer-Assisted Diagnostic Methods.

Gregory Furman Evgeny Furman Artem Charushin Ekaterina Eirikh Sergey Malinin Valery Sheludko Vladimir Sokolovsky David Shtivelman

Published in: JMIR formative research (2022)

The 2 proposed computer-assisted diagnostic methods, based on the analysis of the respiratory sound FFT spectra of patients and volunteers, allow one to automatically diagnose specific acoustic phenomena associated with COVID-19 with sufficiently high diagnostic values. These methods can be applied to develop noninvasive screening self-testing kits for COVID-19.

Keyphrases

coronavirus disease
sars cov
end stage renal disease
ejection fraction
chronic kidney disease
newly diagnosed
prognostic factors
patient reported outcomes
patient reported