The role of spectral analysis of cough sounds in the diagnosis of COVID-19

Abstract

Aim. To evaluate the possibility of using spectral analysis of cough sounds in the diagnosis of a new coronavirus infection COVID-19. Materials and methods. Spectral toussophonobarography was performed in 218 patients with COVID-19 [48.56% men, 51.44% women, average age 40.2 (32.4; 51.0)], in 60 healthy individuals [50% men, 50% women, average age 41.7 (32.2; 53.0)] with induced cough (by inhalation of citric acid solution at a concentration of 20 g/l through a nebulizer). The recording was made using a contact microphone located on a special tripod at a distance of 15–20 cm from the face of the subject. The resulting recordings were processed in a computer program, after which spectral analysis of cough sounds was performed using Fourier transform algorithms. The following parameters of cough sounds were evaluated: the duration of the cough act (ms), the ratio of the energy of low frequencies (60–600 Hz) to the energy of high frequencies (600–6000 Hz), the frequency of the maximum energy of the cough sound (Hz). Results. After statistical processing, it was found out that the parameters of the cough sound of COVID-19 patients differ from the cough of healthy individuals. The obtained data were substituted into the developed regression equation. Rounded to integers, the resulting number had the following interpretation: "0" – there is no COVID-19, "1" – there is COVID-19. Conclusion. The technique showed high levels of sensitivity and specificity. In addition, the method is characterized by sufficient ease of use and does not require expensive equipment, therefore it can be used in practice for timely diagnosis of COVID-19.