Are computerised respiratory sounds in COPD gender dependent?

This study explored gender differences in normal and adventitious respiratory sounds (RS) of patients with COPD. Twenty-six patients were enrolled. RS were recorded simultaneously at posterior right/left chest and airflow standardised (0.4-0.6l/s). Breathing phases were automatically detected using the airflow signals. Normal RS, crackles and wheezes were analysed with developed algorithms. The frequency of maximum intensity and the mean intensity of inspiratory normal RS were slightly higher in females than in males. During expiration, the mean intensity was lower in females, however, a significant difference was only found at posterior left (p=0.01). The mean number of crackles and wheezes seemed to be higher in male patients, although a significant difference was only observed in expiratory crackles at posterior right chest (p=0.04). Findings suggest that minor differences exist between female and male patients with COPD regarding normal and adventitious RS. However, it is still unknown if these differences are clinically relevant.publishe

Automatic crackle detection algorithm based on fractal dimension

Crackles are adventitious respiratory sounds that provide valuable information on different respiratory conditions. Crackles automatic detection in a respiratory sound file is challenging, and thus different signal processing methodologies have been proposed. However, limited testing of such methodologies, namely in respiratory sound files collected in clinical settings, has been conducted. This study aimed to develop an algorithm for automatic crackle detection and characterisation and to evaluate its performance and accuracy against a multi-annotator gold standard. The algorithm is based on three main procedures: i) extraction of a window of interest of a potential crackle (based on fractal dimension and box filtering techniques); ii) verification of the validity of the potential crackle considering computerised respiratory sound analysis established criteria; and iii) characterisation and extraction of crackle parameters. Twenty four 10-second files, acquired in clinical settings, were selected from 10 patients with pneumonia and cystic fibrosis. The algorithm performance was assessed by comparing its results with gold standard annotations (obtained by the agreement among three experts). A set of 7 parameters was optimised. High levels of sensitivity (SE=89%), positive predictive value (PPV=95%) and overall performance (F index=92%) were achieved. This promising result highlights the potential of the algorithm for automatic crackle's detection/characterisation in respiratory sounds acquired in clinical settings

Computerized respiratory sounds are a reliable marker in COPD

Introduction: Computerized respiratory sounds (RS) have shown potential to monitor respiratory status in patients with COPD. However, variability and reliability of this promising marker in COPD are unknown. Therefore, this study assessed the variability and reliability of RS at distinct airflows and standardized anatomic locations in patients with COPD. Methods: A two-part study was conducted. Part one assessed the intra-subject reliability of RS at spontaneous and target (0.4-0.6L/s and 0.7-1L/s) airflows in 13 outpatients (69.3±8.6yrs; FEV1 70.9±21.4% predicted). Part two characterized the inter-subject variability and intrasubject reliability of RS at each standardized anatomic location, using the most reliable airflow, in a sample of 63 outpatients (67.3±10.4yrs; FEV1 75.4±22.9% predicted). RS were recorded simultaneously at seven anatomic locations (trachea, right and left: anterior, lateral and posterior chest). Airflow was recorded with a pneumotachograph. Normal RS intensity, mean number of crackl and wheezes were analyzed with developed algorithms. Inter-subject variability was assessed with the coefficient of variation (CV) and intra-subject reliability with Intraclass Correlation Coefficient (ICC) and Bland and Altman plots. Results: Relative reliability was moderate to excellent for normal RS intensity and mean number of crackles (ICCs .66-.89) and excellent for mean number of wheezes (ICCs .75-.99) at the three airflows. Absolute reliability was greater at target airflows; especially at 0.4-0.6L/s. Intersubject variability was high for all RS parameters and across locations (CV .12-2.22). RS parameters had acceptable relative and absolute intra-subject reliability at the different anatomic locations. The only exception was the mean number of crackles at trachea, which relative and absolute reliability was poor. Conclusions: RS parameters are more reliable at an airflow of 0.4-0.6L/s and overall reliable at all anatomic locations. This should be considered in future studies using computerized auscutation

Computerized respiratory sounds: a comparison between patients with stable and exacerbated COPD

INTRODUCTION: Diagnosis of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) is often challenging as it relies on patients' clinical presentation. Computerized respiratory sounds (CRS), namely crackles and wheezes, may have the potential to contribute for the objective diagnosis/monitoring of an AECOPD. OBJECTIVES: This study explored if CRS differ during stable and exacerbation periods in patients with COPD. METHODS: 13 patients with stable COPD and 14 with AECOPD were enrolled. CRS were recorded simultaneously at trachea, anterior, lateral and posterior chest locations using seven stethoscopes. Airflow (0.4-0.6l/s) was recorded with a pneumotachograph. Breathing phases were detected using airflow signals; crackles and wheezes with validated algorithms. RESULTS: At trachea, anterior and lateral chest, no significant differences were found between the two groups in the number of inspiratory/expiratory crackles or inspiratory wheeze occupation rate. At posterior chest, the number of crackles (median 2.97-3.17 vs. 0.83-1.2, P < 0.001) and wheeze occupation rate (median 3.28%-3.8% vs. 1.12%-1.77%, P = 0.014-0.016) during both inspiration and expiration were significantly higher in patients with AECOPD than in stable patients. During expiration, wheeze occupation rate was also significantly higher in patients with AECOPD at trachea (median 3.12% vs. 0.79%, P < 0.001) and anterior chest (median 3.55% vs. 1.28%, P < 0.001). CONCLUSION: Crackles and wheezes are more frequent in patients with AECOPD than in stable patients, particularly at posterior chest. These findings suggest that these CRS can contribute to the objective diagnosis/monitoring of AECOPD, which is especially valuable considering that they can be obtained by integrating computerized techniques with pulmonary auscultation, a noninvasive method that is a component of patients' physical examination

Computerized Respiratory Sounds: Novel Outcomes for Pulmonary Rehabilitation in COPD

BACKGROUND: Computerized respiratory sounds are a simple and noninvasive measure to assess lung function. Nevertheless, their potential to detect changes after pulmonary rehabilitation (PR) is unknown and needs clarification if respiratory acoustics are to be used in clinical practice. Thus, this study investigated the short- and mid-term effects of PR on computerized respiratory sounds in subjects with COPD. METHODS: Forty-one subjects with COPD completed a 12-week PR program and a 3-month follow-up. Secondary outcome measures included dyspnea, self-reported sputum, FEV1, exercise tolerance, self-reported physical activity, health-related quality of life, and peripheral muscle strength. Computerized respiratory sounds, the primary outcomes, were recorded at right/left posterior chest using 2 stethoscopes. Air flow was recorded with a pneumotachograph. Normal respiratory sounds, crackles, and wheezes were analyzed with validated algorithms. RESULTS: There was a significant effect over time in all secondary outcomes, with the exception of FEV1 and of the impact domain of the St George Respiratory Questionnaire. Inspiratory and expiratory median frequencies of normal respiratory sounds in the 100-300 Hz band were significantly lower immediately (-2.3 Hz [95% CI -4 to -0.7] and -1.9 Hz [95% CI -3.3 to -0.5]) and at 3 months (-2.1 Hz [95% CI -3.6 to -0.7] and -2 Hz [95% CI -3.6 to -0.5]) post-PR. The mean number of expiratory crackles (-0.8, 95% CI -1.3 to -0.3) and inspiratory wheeze occupation rate (median 5.9 vs 0) were significantly lower immediately post-PR. CONCLUSIONS: Computerized respiratory sounds were sensitive to short- and mid-term effects of PR in subjects with COPD. These findings are encouraging for the clinical use of respiratory acoustics. Future research is needed to strengthen these findings and explore the potential of computerized respiratory sounds to assess the effectiveness of other clinical interventions in COPD. Copyright © 2017 by Daedalus Enterprises

Integrated approach for automatic crackle detection based on fractal dimension and box filtering

Crackles are adventitious respiratory sounds (RS) that provide valuable information on different respiratory conditions. Nevertheless, crackles automatic detection in RS is challenging, mainly when collected in clinical settings. This study aimed to develop an algorithm for automatic crackle detection/characterisation and to evaluate its performance and accuracy against a multi-annotator gold standard. The algorithm is based on 4 main procedures: i) recognition of a potential crackle; ii) verification of its validity; iii) characterisation of crackles parameters; and iv) optimisation of the algorithm parameters. Twenty-four RS files acquired in clinical settings were selected from 10 patients with pneumonia and cystic fibrosis. The algorithm performance was assessed by comparing its results with a multi-annotator gold standard agreement. High level of overall performance (F-score=92%) was achieved. The results highlight the potential of the algorithm for automatic crackle detection and characterisation of RS acquired in clinical settings