The Role of Spectral Analysis of Cough Sounds in the Diagnostics of Pneumonia

ORIGINAL ARTICLE
Andrey V. Budnevsky, Sergey N. Avdeev, Evgeniy S. Ovsyannikov, Avag G. Kitoyan, Sofia N. Feigelman

 
For citation: Budnevsky AV, Avdeev SN, Ovsyannikov ES, Kitoyan AG, Feigelman SN. The Role of Spectral Analysis of Cough Sounds in the Diagnostics of Pneumonia. International Journal of Biomedicine. 2026;16(2):212-216. doi:10.21103/Article16(2)_OA9
 
Originally published June 5, 2026

Abstract: 

Background: Community-acquired pneumonia (CAP) is a global healthcare problem and one of the leading causes of death and hospitalization among respiratory diseases. Cough is the most common symptom of pneumonia. Diagnosing pneumonia using cough sounds is a useful non-invasive test that can be performed outside a hospital. The objective of this study was to conduct a spectral analysis of cough sounds in patients with pneumonia compared with the cough in patients with asthma (BA), chronic obstructive pulmonary disease (COPD), coronavirus disease 2019 (COVID-19), and an induced cough in healthy individuals, using citric acid.
Methods and Results: The study’s main group consisted of 65 patients with pneumonia (81.4% men and 18.6% women; mean age of 43.5 [18.0; 70.0] years). The comparison groups consisted of patients with BA (n=38), COPD (n=35), COVID-19 (n=40), and healthy individuals (n=45). The cough sounds were recorded using the spectral tussophonobarography method based on the Fast Fourier Transform Algorithm, which provides a frequency-based distribution of sound energy. We estimated the time-frequency parameters of sounds of the entire cough episode, as well as for separated phases of the cough sound: duration (T, T1, T2, T3), the ratio of the energy of low and medium frequencies (60-600 Hz) to the energy of high frequencies (600-6000 Hz) (Q, Q1, Q2, Q3), and the frequency of maximum sound energy (Hz) (Fmax, Fmax1, Fmax2, Fmax3).
The cough parameters in the main group and the comparison groups had significant differences. In patients with pneumonia, the total cough duration (T) and T2 were significantly shorter than in all comparison groups. In contrast, T1 was significantly prolonged compared with patients with COPD, BA, COVID-19, and healthy subjects with induced cough. T3 was significantly shorter in pneumonia than in healthy individuals with experimentally induced cough. Overall, cough episodes in pneumonia were characterized by a predominance of low-frequency energy compared with BA and COVID-19. During the first cough phase, the Q coefficient was significantly higher in pneumonia than in COVID-19. In the second cough phase, energy distribution shifted toward lower frequencies compared with asthma and toward higher frequencies compared with COPD and COVID-19. In the third cough phase, pneumonia-related cough demonstrated a significantly greater proportion of high-frequency energy than induced cough in healthy subjects. The maximum frequency (Fmax) in pneumonia was significantly lower than in COVID-19 and BA. Fmax1 was significantly lower than in all comparison groups. Fmax2 was significantly lower than in BA, COPD, and COVID-19. Fmax3 was also significantly lower in pneumonia compared with COVID-19.
Conclusion: Cough in patients with pneumonia demonstrates significant differences in key frequency–time characteristics compared with cough sounds in patients with BA, COPD, and COVID-19. These findings suggest that spectral tussophonobarography may be a useful tool for differential diagnosis of pneumonia.

Keywords: 
pneumonia • cough • spectral analysis
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Received February 26, 2026.
Accepted April 20, 2026.
© 2026 The Author(s). International Journal of Biomedicine is published by IMRDC.
This is an open access article under the CC BY-NC-ND 4.0 license.