| Title: | Time series and fractal analyses of wheezing : a novel approach |
|---|
| Authors: | ID Swapna, Mohanachandran Nair Sindhu (Author)
ID Renjini, Ammini (Author)
ID Raj, Vimal (Author)
ID Sreejyothi, S. (Author)
ID Iyer Sankararaman, Sankaranarayana (Author) |
|---|
| Files: |
This document has no files that are freely available to the public. This document may have a physical copy in the library of the organization, check the status via COBISS.  |
|---|
| Language: | English |
|---|
| Work type: | Unknown |
|---|
| Typology: | 1.01 - Original Scientific Article |
|---|
| Organization: | UNG - University of Nova Gorica
|
|---|
| Abstract: | Since the outbreak of the pandemic Coronavirus Disease 2019, the world is in search of novel non-invasive methods for safer
and early detection of lung diseases. The pulmonary pathological symptoms refected through the lung sound opens a possibility of detection through auscultation and of employing spectral, fractal, nonlinear time series and principal component
analyses. Thirty-fve signals of vesicular and expiratory wheezing breath sound, subjected to spectral analyses shows a clear
distinction in terms of time duration, intensity, and the number of frequency components. An investigation of the dynamics
of air molecules during respiration using phase portrait, Lyapunov exponent, sample entropy, fractal dimension, and Hurst
exponent helps in understanding the degree of complexity arising due to the presence of mucus secretions and constrictions
in the respiratory airways. The feature extraction of the power spectral density data and the application of principal component analysis helps in distinguishing vesicular and expiratory wheezing and thereby, giving a ray of hope in accomplishing
an early detection of pulmonary diseases through sound signal analysis. |
|---|
| Keywords: | auscultation, wheeze, fractals, nonlinear time series analysis, sample entropy |
|---|
| Year of publishing: | 2020 |
|---|
| Number of pages: | str. 1339–1347 |
|---|
| Numbering: | Vol. 43, iss. 4 |
|---|
| PID: | 20.500.12556/RUNG-7403 |
|---|
| COBISS.SI-ID: | 113308675 |
|---|
| UDC: | 53 |
|---|
| ISSN on article: | 2662-4729 |
|---|
| DOI: | 10.1007/s13246-020-00937-5 |
|---|
| NUK URN: | URN:SI:UNG:REP:NQDYQ9WC |
|---|
| Publication date in RUNG: | 30.06.2022 |
|---|
| Views: | 2008 |
|---|
| Downloads: | 0 |
|---|
| Metadata: |    |
|---|
|
:
|
Copy citation |
|---|
| | | | Average score: | (0 votes) |
|---|
| Your score: | Voting is allowed only for logged in users. |
|---|
| Share: |  |
|---|
Hover the mouse pointer over a document title to show the abstract or click
on the title to get all document metadata. |
