Analysis Of Wheeze Sounds During Tidal Breathing According To Severity Levels In Asthma Patients

Nabi, Fizza Ghulam and Sundaraj, Kenneth and Chee, Kiang Lam and Palaniappan, Rajkumar (2019) Analysis Of Wheeze Sounds During Tidal Breathing According To Severity Levels In Asthma Patients. Journal of Asthma, 57 (4). 353- 365. ISSN 0277-0903

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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. Method: 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 F25, F50, F75, F90 and F99, 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. Results: All features generally showed statistical significance in most of the datasets for all severity levels [v2 ¼ 6.021–71.65, p < 0.05, g2 ¼ 0.01–0.52]. Of the seven investigated features, only AP showed statistical significance in all the datasets. F25, F75, F90 and F99 exhibited statistical significance in at least six datasets [v2 ¼ 4.852–65.63, p < 0.05, g2 ¼ 0.01–0.52], and F25, F50 and MF showed statistical significance with a large g2 in all trachea-related datasets [v2 ¼ 13.54–55.32, p < 0.05, g2 ¼ 0.13–0.33]. Conclusion: The results obtained for the time-frequency features revealed that (1) the asthma severity levels ofn 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

Item Type:	Article
Uncontrolled Keywords:	Asthma, Breath Sounds, Wheeze Detection, Airway Obstruction, Severity Level
Divisions:	Faculty of Electronics and Computer Engineering > Department of Industrial Electronics
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	28 Oct 2020 14:05
Last Modified:	28 Oct 2020 14:05
URI:	http://eprints.utem.edu.my/id/eprint/24364
Statistic Details:	View Download Statistic

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