Analysis of wheeze sounds during tidal breathing according to severity levels in asthma patients.

Clicks: 314
ID: 102401
2020
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #10 of 12 articles by views in the journal of asthma : official journal of the association for the care of asthma

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
: This study aimed to statistically analyze the behavior of time-frequency features in digital recordings of wheeze sounds obtained from patients with various levels of asthma severity (mild, moderate, and severe), and this analysis was based on the auscultation location and/or breath phase. : Segmented and validated wheeze sounds were collected from the trachea and lower lung base (LLB) of 55 asthmatic patients during tidal breathing maneuvers and grouped into nine different datasets. The quartile frequencies , , , and , mean frequency (MF) and average power (AP) were computed as features, and a univariate statistical analysis was then performed to analyze the behavior of the time-frequency features. : All features generally showed statistical significance in most of the datasets for all severity levels [ = 6.021-71.65,  < 0.05, η = 0.01-0.52]. Of the seven investigated features, only AP showed statistical significance in all the datasets. , , and exhibited statistical significance in at least six datasets [ = 4.852-65.63,  < 0.05, η = 0.01-0.52], and , and MF showed statistical significance with a large η in all trachea-related datasets [ = 13.54-55.32,  < 0.05, η = 0.13-0.33]. : The results obtained for the time-frequency features revealed that (1) the asthma severity levels of patients can be identified through a set of selected features with tidal breathing, (2) tracheal wheeze sounds are more sensitive and specific predictors of severity levels and (3) inspiratory and expiratory wheeze sounds are almost equally informative.
Reference Key
nabi2020analysisthe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Nabi, Fizza Ghulam;Sundaraj, Kenneth;Lam, Chee Kiang;Palaniappan, Rajkumar;
Journal the journal of asthma : official journal of the association for the care of asthma
Year 2020
DOI
10.1080/02770903.2019.1576193
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.