Averaged and time-gated spectral analysis of respiratory sounds. Repeatability of spectral parameters in healthy men and in patients with fibrosing alveolitis

Changes in the breath sound spectrum with bronchodilation in children with asthma

BACKGROUND

Breath sound parameters have been suggested to be new biomarkers of airway function in patients with asthma.

METHODS

We investigated the effect of bronchodilation on breath sound parameters in sixty-four children (mean age, 8.9 years; range, 6-16 years) using a breath sound analyzer. The breath sound parameters included frequency limiting 50% and 99% of the power spectrum (F₅₀ and F₉₉), roll-off from 600-1200 Hz (slope), and spectrum curve indices such as the ratios of the third and fourth power area to the total area of the power spectrum (P₃/P_T and P₄/P_T), total area under the curve (A₃/A_T and B₄/A_T), and the ratio of power and frequency at 50% and 75% of the highest frequency of the power spectrum (RPF₇₅ and RPF₅₀). Lung function was assessed using spirometry and the forced oscillation technique (FOT). All variables were assessed before and after inhalation of a β₂-agonist.

RESULTS

The spectrum curve indices, A₃/A_T, B₄/A_T, RPF₇₅, and RPF₅₀, showed statistically significant increase following β₂-agonist inhalation. The increase in RPF₅₀ was correlated with the decrease in the difference between resistance at 5 Hz and 20 Hz, R5-R20, measured by FOT. In the multiple regression analysis adjusted for the effect of ΔRPF₇₅, the changes in A₃/A_T and B₄/A_T were positively correlated with that in the forced expiratory volume in one second.

CONCLUSIONS

The spectrum curve indices indicated bronchodilation, and may be useful for the assessment of bronchial reversibility in children with asthma.

Changes in the breath sound spectrum during methacholine inhalation in children with asthma

BACKGROUND AND OBJECTIVE

An effort-independent breath sound analysis is expected to be a safe and simple method for clinical assessment of changes in airway function. The effects of bronchoconstriction and bronchodilation on novel breath sound parameters in asthmatic children were investigated.

METHODS

The study population included 49 children with atopic asthma (male = 33; mean age: 10.2 years). We evaluated breath sound parameters of the highest frequency of the power spectrum (HFp), frequency limiting 50% and 99% of the power spectrum (F₅₀ and F₉₉ ) and roll-off from 600 Hz to the HFp (Slope). We also assessed new parameters obtained using the ratios of sound spectrum parameters (spectrum curve indices), such as the ratio of the third and fourth power area to the total power area (P₃ /P_T and P₄ /P_T ), the ratio of the third and fourth areas to the total area under the curve (A₃ /A_T and B₄ /A_T ) and the ratio of power and frequency at 75% of HFp and 50% of HFp (RPF₇₅ and RPF₅₀ ). This was measured before and after methacholine inhalation challenge and after β₂ agonist inhalation.

RESULTS

The parameters, F₅₀ and F₉₉ , showed no changes after methacholine inhalation. Conversely, the A₃ /A_T (12.5-10.0%, P < 0.001), B₄ /A_T (7.6-5.5%, P < 0.001), RPF₇₅ (6.7-4.0 dBm/Hz, P < 0.001) and RPF₅₀ (5.8-4.3 dBm/Hz, P < 0.001) were significantly decreased. These values returned to the original level after β₂ agonist inhalation.

CONCLUSION

Spectrum curve indices indicate bronchoconstriction and bronchodilation. These parameters may play a role in the assessment of airway narrowing in asthmatic children.

A clinical method for detecting bronchial reversibility using a breath sound spectrum analysis in infants

BACKGROUND

Using a breath sound analyzer, we investigated clinical parameters for detecting bronchial reversibility in infants.

METHODS

A total of 59 infants (4-39 months, mean age 7.8 months) were included. In Study 1, the intra- and inter-observer variability was measured in 23 of 59 infants. Breath sound parameters, the frequency at 99% of the maximum frequency (F₉₉), frequency at 25%, 50%, and 75% of the power spectrum (Q₂₅, Q₅₀, and Q₇₅), and highest frequency of inspiratory breath sounds (HFI), and parameters obtained using the ratio of parameters, i.e. spectrum curve indices, the ratio of the third and fourth area to total area (A₃/A_T and B₄/A_T, respectively) and ratio of power and frequency at F₇₅ and F₅₀ (RPF₇₅ and RPF₅₀), were calculated. In Study 2, the relationship between parameters of breath sounds and age and stature were studied. In Study 3, breath sounds were studied before and after β₂ agonist inhalation.

RESULTS

In Study 1, the data showed statistical intra- and inter-observer reliability in A₃/A_T (p=0.042 and 0.034, respectively) and RPF₅₀ (p=0.001 and 0.001, respectively). In Study 2, there were no significant relationships between age, height, weight, and BMI. In Study 3, A₃/A_T and RPF₅₀ significantly changed after β₂ agonist inhalation (p=0.001 and p<0.001, respectively).

CONCLUSIONS

Breath sound analysis can be performed in infants, as in older children, and the spectrum curve indices are not significantly affected by age-related factors. These sound parameters may play a role in the assessment of bronchial reversibility in infants.

A novel method for detecting airway narrowing using breath sound spectrum analysis in children

BACKGROUND

Using a breath sound analyzer, we investigated new clinical parameters that are rarely affected by airflow in young children.

METHODS

A total of 65 children with asthma participated in this study (mean age 9.6 years). In Study 1, the intra- and inter-observer variability was measured. Common breath sound parameters, frequency at 99%, 75%, and 50% of the maximum frequency (F99, F75, and F50) and the highest frequency of inspiratory breath sounds were calculated. In addition, new parameters obtained using the ratio of sound spectra parameters, i.e., the spectrum curve indexes including the ratio of the third and fourth area to the total area and the ratio of power and frequency at F75 and F50, were calculated. In Study 2, 51 children underwent breath sound analyses. In Study 3, breath sounds were studied before and after methacholine inhalation.

RESULTS

In Study 1, the data showed good inter- and intra-observer reliability. In Study 2, there were significant relationships between the airflow rate, age, height, and spirometric and common breath sound parameters. However, there were no significant relationships between the airflow rate and the spectrum curve indexes. Moreover, the spectrum curve indexes showed no relationships with age, height, or spirometric parameters. In Study 3, all parameters significantly changed after methacholine inhalation.

CONCLUSIONS

Some spectrum curve indexes are not significantly affected by the airflow rate at the mouth, although they successfully indicate airway narrowing. These parameters may play a role in the assessment of bronchoconstriction in children.

Novel algorithm to identify and differentiate specific digital signature of breath sound in patients with diffuse parenchymal lung disease

BACKGROUND AND OBJECTIVE

Auscultation is an important part of the clinical examination of different lung diseases. Objective analysis of lung sounds based on underlying characteristics and its subsequent automatic interpretations may help a clinical practice.

METHODS

We collected the breath sounds from 8 normal subjects and 20 diffuse parenchymal lung disease (DPLD) patients using a newly developed instrument and then filtered off the heart sounds using a novel technology. The collected sounds were thereafter analysed digitally on several characteristics as dynamical complexity, texture information and regularity index to find and define their unique digital signatures for differentiating normality and abnormality. For convenience of testing, these characteristic signatures of normal and DPLD lung sounds were transformed into coloured visual representations. The predictive power of these images has been validated by six independent observers that include three physicians.

RESULTS

The proposed method gives a classification accuracy of 100% for composite features for both the normal as well as lung sound signals from DPLD patients. When tested by independent observers on the visually transformed images, the positive predictive value to diagnose the normality and DPLD remained 100%.

CONCLUSIONS

The lung sounds from the normal and DPLD subjects could be differentiated and expressed according to their digital signatures. On visual transformation to coloured images, they retain 100% predictive power. This technique may assist physicians to diagnose DPLD from visual images bearing the digital signature of the condition.

The reliability of lung crackle characteristics in cystic fibrosis and bronchiectasis patients in a clinical setting

Lung sounds provide useful information for assessing and monitoring respiratory patients, but standard auscultation is subjective. Computer aided lung sound analysis (CALSA) enables the quantification and characterisation of added lung sounds (e.g. crackles). At present, little is known about the reliability of these sound characteristics. Therefore, the aim of this study was to explore the reliability of crackle initial deflection width (IDW) and two-cycle deflection (2CD) in a clinical population. Fifty-four subjects (37 bronchiectasis, 17 cystic fibrosis) were recruited from out-patient clinics. Three repeated lung sound recordings were taken at seven anatomical sites with a digital stethoscope connected to a laptop computer. The intra-subject reliability of crackle IDW and 2CD was found to be 'good' to 'excellent', estimated by the analysis of variance, intraclass correlation coefficient (IDW 0.76;0.85, 2CD 0.83;0.94), Bland and Altman 95% limits of agreement (IDW -0.50;0.47 ms, 2CD -2.12;1.87 ms) and smallest real difference (IDW 0.30;0.66 ms, 2CD 1.57;2.42 ms). Crackle 2CD was found to be more reliable than IDW. It is concluded that crackle IDW and 2CD characterized by CALSA have good test-retest reliability. This technique requires further evaluation since CALSA has potential to diagnose or monitor respiratory conditions, and provide an objective physiological measure for respiratory interventions.

Reproducibility of dynamically represented acoustic lung images from healthy individuals

Background and aim:

Acoustic lung imaging offers a unique method for visualising the lung. This study was designed to demonstrate reproducibility of acoustic lung images recorded from healthy individuals at different time points and to assess intra- and inter-rater agreement in the assessment of dynamically represented acoustic lung images.

Methods:

Recordings from 29 healthy volunteers were made on three separate occasions using vibration response imaging. Reproducibility was measured using quantitative, computerised assessment of vibration energy. Dynamically represented acoustic lung images were scored by six blinded raters.

Results:

Quantitative measurement of acoustic recordings was highly reproducible with an intraclass correlation score of 0.86 (very good agreement). Intraclass correlations for inter-rater agreement and reproducibility were 0.61 (good agreement) and 0.86 (very good agreement), respectively. There was no significant difference found between the six raters at any time point. Raters ranged from 88% to 95% in their ability to identically evaluate the different features of the same image presented to them blinded on two separate occasions.

Conclusion:

Acoustic lung imaging is reproducible in healthy individuals. Graphic representation of lung images can be interpreted with a high degree of accuracy by the same and by different reviewers.

Combining neural network and genetic algorithm for prediction of lung sounds

Recognition of lung sounds is an important goal in pulmonary medicine. In this work, we present a study for neural networks-genetic algorithm approach intended to aid in lung sound classification. Lung sound was captured from the chest wall of The subjects with different pulmonary diseases and also from the healthy subjects. Sound intervals with duration of 15-20 s were sampled from subjects. From each interval, full breath cycles were selected. Of each selected breath cycle, a 256-point Fourier Power Spectrum Density (PSD) was calculated. Total of 129 data values calculated by the spectral analysis are selected by genetic algorithm and applied to neural network. Multilayer perceptron (MLP) neural network employing backpropagation training algorithm was used to predict the presence or absence of adventitious sounds (wheeze and crackle). We used genetic algorithms to search for optimal structure and training parameters of neural network for a better predicting of lung sounds. This application resulted in designing of optimum network structure and, hence reducing the processing load and time.

Tracheal and lung sounds repeatability in normal adults

Tracheal and lung sounds measurements for clinical applications depends on their intrasubject repeatability. Our objectives were to characterize tracheal and lung sounds and to investigate the temporal variability in normal adults. Tracheal sounds were studied in 7 subjects and lung sounds in 10 adults. Acoustic measurements were done in five occasions over a month for tracheal sounds and on seven occasions over a year for lung sounds. Sounds were recorded using contact sensors on the suprasternal notch and on the posterior right lower lobe. Subjects breathed through a pneumotachograph at flows of 0.9-1.1 l/s. Signals were low-pass filtered, amplified and Fourier analysis was applied to sounds within a target flow range. We measured the frequencies below which 25% (F25), 50% (F median), 75% (F75) and 99% (SEF99) of the spectral power between 100 and 2000 Hz. There were no differences between the measurements obtained at different days comparing each subject (P = ns, ANOVA). Our results show that the spectral pattern of tracheal and lung sounds are stable with low intrasubject variability.

The relationship between normal lung sounds, age, and gender

Auscultation is one of the most important noninvasive and feasible methods for the detection of lung diseases. Systematic changes in breathing sounds with increasing age are of diagnostic importance. To investigate these changes, we recorded lung sounds taken from four locations in the posterior thorax of 162 subjects, together with airflow. The data were analyzed according to age, sex, and smoking habit. In order to describe the power spectrum of the lung sounds, we calculated mean and median frequency, frequency with the highest power, and a ratio (Q) of relative power of the two frequency bands of 330 to 600 Hz and 60 to 330 Hz. Linear regression analysis was used as a measurement of age-dependence of these variables. Significant differences in Q were found in men versus women (p < 0.05), but not in smokers versus nonsmokers. Within the groups, a small but significant correlation existed between Q and age (r(2) </= 0.1, p < 0.05). For both men and women, a slight increase of the relative power in the frequency band of 330 to 600 Hz was recorded with increasing age. However, on the basis of large individual variations, these small changes (DeltaQ approximately 5%, SD(Q) >/= +/- 5%) have no clinical significance and need not to be considered in the automatic detection of lung diseases by analyzing lung sounds.

A bioacoustic method for timing of the different phases of the breathing cycle and monitoring of breathing frequency

It is well known that the flow of air through the trachea during respiration causes vibrations in the tissue near the trachea, which propagate to the surface of the body and can be picked up by a microphone placed on the throat over the trachea. Since the vibrations are a direct result of the airflow, accurate timing of inspiration and expiration is possible. This paper presents a signal analysis solution for automated monitoring of breathing and calculation of the breathing frequency. The signal analysis approach uses tracheal sound variables in the time and frequency domains, as well as the characteristics of the disturbances that can be used to discriminate tracheal sound from noise. One problem associated with the bioacoustic method is its sensitivity for acoustic disturbances, because the microphone tends to pick up all vibrations, independent of their origin. A signal processing method was developed that makes the bioacoustic method clinically useful in a broad variety of situations, for example in intensive care and during certain heart examinations, where information about both the precise timing and the phases of breathing is crucial.