Changes in frequency spectra of breath sounds during histamine challenge test in adult asthmatics and healthy control subjects

The acoustic characteristics of fine crackles predict honeycombing on high-resolution computed tomography

Background

Honeycombing on high-resolution computed tomography (HRCT) is a distinguishing feature of usual interstitial pneumonia and predictive of poor outcome in interstitial lung diseases (ILDs). Although fine crackles are common in ILD patients, the relationship between their acoustic features and honeycombing on HRCT has not been well characterized.

Methods

Lung sounds were digitally recorded from 71 patients with fine crackles and ILD findings on chest HRCT. Lung sounds were analyzed by fast Fourier analysis using a sound spectrometer (Easy-LSA; Fukuoka, Japan). The relationships between the acoustic features of fine crackles in inspiration phases (onset timing, number, frequency parameters, and time-expanded waveform parameters) and honeycombing in HRCT were investigated using multivariate logistic regression analysis.

Results

On analysis, the presence of honeycombing on HRCT was independently associated with onset timing (early vs. not early period; odds ratios [OR] 10.407, 95% confidence interval [95% CI] 1.366–79.298, P = 0.024), F99 value (the percentile frequency below which 99% of the total signal power is accumulated) (unit Hz = 100; OR 5.953, 95% CI 1.221–28.317, P = 0.029), and number of fine crackles in the inspiratory phase (unit number = 5; OR 4.256, 95% CI 1.098–16.507, P = 0.036). In the receiver-operating characteristic curves for number of crackles and F99 value, the cutoff levels for predicting the presence of honeycombing on HRCT were calculated as 13.2 (area under the curve [AUC], 0.913; sensitivity, 95.8%; specificity, 75.6%) and 752 Hz (AUC, 0.911; sensitivity, 91.7%; specificity, 85.2%), respectively. The multivariate logistic regression analysis additionally using these cutoff values revealed an independent association of number of fine crackles in the inspiratory phase, F99 value, and onset timing with the presence of honeycombing (OR 33.907, 95% CI 2.576–446.337, P = 0.007; OR 19.397, 95% CI 2.311–162.813, P = 0.006; and OR 12.383, 95% CI 1.443–106.293, P = 0.022; respectively).

Conclusions

The acoustic properties of fine crackles distinguish the honeycombing from the non-honeycombing group. Furthermore, onset timing, number of crackles in the inspiratory phase, and F99 value of fine crackles were independently associated with the presence of honeycombing on HRCT. Thus, auscultation routinely performed in clinical settings combined with a respiratory sound analysis may be predictive of the presence of honeycombing on HRCT.

Multichannel lung sound analysis for asthma detection

BACKGROUND AND OBJECTIVE

Lung sound signals convey valuable information of the lung status. Auscultation is an effective technique to appreciate the condition of the respiratory system using lung sound signals. The prior works on asthma detection from lung sound signals rely on the presence of wheeze. In this paper, we have classified normal and asthmatic subjects using advanced signal processing of posterior lung sound signals, even in the absence of wheeze.

METHODS

We collected lung sounds of 60 subjects (30 normal and 30 asthma) using a novel 4-channel data acquisition system from four different positions over the posterior chest, as suggested by the pulmonologist. A spectral subband based feature extraction scheme is proposed that works with artificial neural network (ANN) and support vector machine (SVM) classifiers for the multichannel signal. The power spectral density (PSD) is estimated from extracted lung sound cycle using Welch's method, which then decomposed into uniform subbands. A set of statistical features is computed from each subband and applied to ANN and SVM classifiers to classify normal and asthmatic subjects.

RESULTS

In the first part of this study, the performances of each individual channel and four channels together are evaluated where the combined channel performance is found superior to that of individual channels. Next, the performances of all possible combinations of the channels are investigated and the best classification accuracies of 89.2( ± 3.87)% and 93.3( ± 3.10)% are achieved for 2-channel and 3-channel combinations in ANN and SVM classifiers, respectively.

CONCLUSIONS

The proposed multichannel asthma detection method where the presence of wheeze in lung sound is not a necessary requirement, outperforms commonly used lung sound classification methods in this field and provides significant relative improvement. The channel combination study gives insight into the contribution of respective lung sound collection areas and their combinations in asthma detection.

Reliability, validity and minimal detectable change of computerized respiratory sounds in patients with chronic obstructive pulmonary disease

INTRODUCTION

Computerized respiratory sounds (CRS) are closely related to the movement of air within the tracheobronchial tree and are promising outcome measures in patients with chronic obstructive pulmonary disease (COPD). However, CRS measurement properties have been poorly tested.

OBJECTIVE

The aim of this study was to assess the reliability, validity and the minimal detectable changes (MDC) of CRS in patients with stable COPD.

METHODS

Fifty patients (36♂, 67.26 ± 9.31y, FEV₁ 49.52 ± 19.67%predicted) were enrolled. CRS were recorded simultaneously at seven anatomic locations (trachea; right and left anterior, lateral and posterior chest). The number of crackles, wheeze occupation rate, median frequency (F50) and maximum intensity (Imax) were processed using validated algorithms. Within-day and between-days reliability, criterion and construct validity, validity to predict exacerbations and MDC were established.

RESULTS

CRS presented moderate-to-excellent within-day reliability (ICC_1,3  ≥ 0.51; P < .05) and moderate-to-good between-days reliability (ICC_1,2  ≥ 0.47; P < .05) for most locations. Negligible-to-moderate correlations with FEV₁ %predicted were found (-0.53 < r_s  < -0.28; P < .05), and the inspiratory number of crackles were the best discriminator between mild-to-moderate and severe-to-very severe airflow limitations (area under the curve >0.78). CRS correlated poorly with patient-reported outcomes (r_s  < 0.48; P < .05) and did not predict exacerbations. Inspiratory number of crackles at posterior right chest, inspiratory F50 at trachea and anterior left chest and expiratory Imax at anterior right chest were simultaneously reliable and valid, and their MDC were 2.41, 55.27, 29.55 and 3.98, respectively.

CONCLUSION

CRS are reliable and valid. Their use, integrated with other clinical and patient-reported measures, may fill the gap of assessing small airways and contribute toward a patient's comprehensive evaluation.

Changes in inhaler inhalation acoustic features during induced bronchoconstriction: a pilot study

Asthma is a chronic respiratory disease affecting millions of people worldwide, and is consequently a major issue for global health. Exacerbations are acute events involving the worsening of asthma's primary respiratory symptoms and are a major cause of morbidity in asthma patients, largely due to the unpredictability of their onset. This study aimed to investigate the relationship between changes in acoustic features of inhaler inhalations and changes in forced expiratory volume in one second (FEV1) that occur during a simulated exacerbation, a bronchial challenge test (BCT). This is a clinical test that simulates an asthma exacerbation through the administration of a bronchoconstrictor agent. Eight patients indicated for a BCT were recruited for this study. Non-contact and tracheal microphones were employed to record Diskus™ inhaler inhalations throughout the course of a BCT. A spirometer was employed to measure inhaler peak inspiratory flow rate (PIFR). In patients responsive to the BCT (n=4), significant correlations between changes in FEV1 and acoustic features on both microphones existed, with fractal increment of Katz fractal dimension yielding the strongest correlation (R=0.58), and between FEV1 and PIFR (R=0.62). These findings suggest that inhaler inhalation acoustic features may assist in the early detection of exacerbations. Future research will determine whether this is the case in a larger cohort of patients with non-simulated exacerbations.

Treatment evaluation using lung sound analysis in asthmatic children

BACKGROUND AND OBJECTIVE

Non-invasive assessment of treatment and prediction of attacks in asthmatic children do not yet exist. Lung sound analysis can non-invasively evaluate airway obstruction. We used a recently developed technology for analysing lung sounds using ic700 (index of the chest wall at 700 Hz, sound intensity at 700 Hz) to evaluate response to inhaled corticosteroid (ICS) in asthmatic children.

METHOD

Seventy asthmatic children, including infants, underwent lung sound recording in the asymptomatic state prior to and 1, 2, 4, 6 and 8 weeks after ICS treatment, and asthma control was assessed at 10 weeks. The ic700 scores at 4, 6 and 8 weeks were compared with the presence of attack during the following 2 weeks. Subjects were divided into uncontrolled and well-controlled groups.

RESULTS

The mean ic700 scores of all subjects significantly reduced after 8 weeks of treatment. The mean scores of the uncontrolled group were significantly higher than those of the well-controlled group at 4, 6 and 8 weeks after starting treatment. The ic700 cut-off value for predicting asthma attacks within 2 weeks following the evaluation was set at 0.0. After 6 weeks of treatment, the area under the curve was 0.92 ± 0.04; the sensitivity, specificity and positive and negative predictive values were 83%, 88% and 88% and 84%, respectively. Similar results were observed at 4 and 8 weeks.

CONCLUSION

The ic700 score is useful in assessing the effects of ICS treatment, predicting attack symptoms and identifying asymptomatic asthmatic children at a high risk for asthma attack.

Lung sound analysis helps localize airway inflammation in patients with bronchial asthma

Purpose

Airway inflammation can be detected by lung sound analysis (LSA) at a single point in the posterior lower lung field. We performed LSA at 7 points to examine whether the technique could identify the location of airway inflammation in patients with asthma.

Patients and methods

Breath sounds were recorded at 7 points on the body surface of 22 asthmatic subjects. Inspiration sound pressure level (I_SPL), expiration sound pressure level (E_SPL), and the expiration-to-inspiration sound pressure ratio (E/I) were calculated in 6 frequency bands. The data were analyzed for potential correlation with spirometry, airway hyperresponsiveness (PC₂₀), and fractional exhaled nitric oxide (FeNO).

Results

The E/I data in the frequency range of 100–400 Hz (E/I low frequency [LF], E/I mid frequency [MF]) were better correlated with the spirometry, PC₂₀, and FeNO values than were the I_SPL or E_SPL data. The left anterior chest and left posterior lower recording positions were associated with the best correlations (forced expiratory volume in 1 second/forced vital capacity: r=−0.55 and r=−0.58; logPC₂₀: r=−0.46 and r=−0.45; and FeNO: r=0.42 and r=0.46, respectively). The majority of asthmatic subjects with FeNO ≥70 ppb exhibited high E/I MF levels in all lung fields (excluding the trachea) and V₅₀%pred <80%, suggesting inflammation throughout the airway. Asthmatic subjects with FeNO <70 ppb showed high or low E/I MF levels depending on the recording position, indicating uneven airway inflammation.

Conclusion

E/I LF and E/I MF are more useful LSA parameters for evaluating airway inflammation in bronchial asthma; 7-point lung sound recordings could be used to identify sites of local airway inflammation.

Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection

In the clinic, the wheezing sound is usually considered as an indicator symptom to reflect the degree of airway obstruction. The auscultation approach is the most common way to diagnose wheezing sounds, but it subjectively depends on the experience of the physician. Several previous studies attempted to extract the features of breathing sounds to detect wheezing sounds automatically. However, there is still a lack of suitable monitoring systems for real-time wheeze detection in daily life. In this study, a wearable and wireless breathing sound monitoring system for real-time wheeze detection was proposed. Moreover, a breathing sounds analysis algorithm was designed to continuously extract and analyze the features of breathing sounds to provide the objectively quantitative information of breathing sounds to professional physicians. Here, normalized spectral integration (NSI) was also designed and applied in wheeze detection. The proposed algorithm required only short-term data of breathing sounds and lower computational complexity to perform real-time wheeze detection, and is suitable to be implemented in a commercial portable device, which contains relatively low computing power and memory. From the experimental results, the proposed system could provide good performance on wheeze detection exactly and might be a useful assisting tool for analysis of breathing sounds in clinical diagnosis.

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.

Lung sound analysis can be an index of the control of bronchial asthma

BACKGROUND

We assessed whether lung sound analysis (LSA) is a valid measure of airway obstruction and inflammation in patients with bronchial asthma during treatment with inhaled corticosteroids (ICSs).

METHODS

63 good adherence patients with bronchial asthma and 18 poor adherence patients were examined by LSA, spirometry, fractional exhaled nitric oxide (FeNO), and induced sputum. The expiration-to-inspiration lung sound power ratio at low frequencies between 100 and 200 Hz (E/I LF) obtained by LSA was compared between healthy volunteers and bronchial asthma patients. Next, post-ICS treatment changes were compared in bronchial asthma patients between the good adherence patients and the poor adherence patients.

RESULTS

E/I LF was significantly higher in bronchial asthma patients (0.62 ± 0.21) than in healthy volunteers (0.44 ± 0.12, p < 0.001). The good adherence patients demonstrated a significant reduction in E/I LF from pre-treatment to post-treatment (0.55 ± 0.21 to 0.46 ± 0.16, p = 0.002), whereas the poor adherence patients did not show a significant change. The decrease of E/I LF correlated with the improvement of FEV₁/FVC ratio during the ICS treatment (r = -0.26, p = 0.04). The subjects with higher pre-treatment E/I LF values had significantly lower FEV₁/FVC and V_50,%pred (p < 0.001), and significantly higher FeNO and sputum eosinophil percentages (p = 0.008 and p < 0.001, respectively).

CONCLUSIONS

The E/I LF measurement obtained by LSA is useful as an indicator of changes in airway obstruction and inflammation and can be used for monitoring the therapeutic course of bronchial asthma patients.

Peripheral bronchial obstruction evaluation in patients with asthma by lung sound analysis and impulse oscillometry

BACKGROUND

Computer-aided lung sound analysis (LSA) has been reported to be useful for evaluating airway inflammation and obstruction in asthma patients. We investigated the relation between LSA and impulse oscillometry with the evaluation of peripheral airway obstruction.

METHODS

A total of 49 inhaled corticosteroid-naive bronchial asthma patients underwent LSA, spirometry, impulse oscillometry, and airway hyperresponsiveness testing. The data were analyzed to assess correlations between the expiration: inspiration lung sound power ratio (dB) at low frequencies between 100 and 195 Hz (E/I LF) and various parameters.

RESULTS

E/I LF and X5 were identified as independent factors that affect V˙_{50,%predicted}. E/I LF showed a positive correlation with R5 (r = 0.34, p = 0.017), R20 (r = 0.34, p = 0.018), reactance area (AX, r = 0.40, p = 0.005), and resonant frequency of reactance (Fres, r = 0.32, p = 0.024). A negative correlation was found between E/I LF and X5 (r = -0.47, p = 0.0006). E/I LF showed a negative correlation with FEV₁/FVC(%), FEV_1,%predicted, V˙_{50,%predicted}, and V˙_{25,%predicted} (r = -0.41, p = 0.003; r = -0.44, p = 0.002; r = -0.49, p = 0.0004; and r = -0.30, p = 0.024, respectively). E/I LF was negatively correlated with log PC₂₀ (r = -0.30, p = 0.024). Log PC₂₀, X5, and past smoking were identified as independent factors that affected E/I LF level.

CONCLUSIONS

E/I LF as with X5 can be an indicator of central and peripheral airway obstruction in bronchial asthma patients.

Changes in lung sounds during asthma progression in a guinea pig model

BACKGROUND

Lung sound analysis is useful for objectively evaluating airways even in children with asymptomatic asthma. However, the relationship between lung sounds and morphological changes in the airways has not been elucidated. We examined the relationship between lung sounds and chronic morphological changes in the airways during the progression of asthma from onset in guinea pigs.

METHODS

Eleven male guinea pigs were examined; of these, seven were used as asthma models and four as controls. The asthma models were sensitized and repeatedly challenged by inhaling albumin chicken egg. We measured lung sounds and lung function twice a week for 21 weeks. After the final antigen challenge, the lungs were excised for histological examination. We measured the ratio of airway wall thickness to the total airway area and the ratio of the internal area to the total airway area in the trachea, third bronchi, and terminal bronchioles.

RESULTS

Among the lungs sounds, the difference between the two groups was greatest with respect to inspiratory sound intensity. The ratio of airway wall thickness to the total airway area of the terminal bronchioles was greater in the asthma models than in the controls, and it correlated best with the changes in inspiratory sound intensity in the 501-1000-Hz range (r = 0.76, p < 0.003).

CONCLUSIONS

Lung sound intensity in the middle frequency range from 501 to 1000 Hz correlated with peripheral airway wall thickness. Inspiratory sound intensity appeared to be an indicator of morphological changes in small airways in asthma.

Influences of gender and anthropometric features on inspiratory inhaler acoustics and peak inspiratory flow rate

Inhalers are hand-held devices used to treat chronic respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD). Medication is delivered from an inhaler to the user through an inhalation maneuver. It is unclear whether gender and anthropometric features such as age, height, weight and body mass index (BMI) influence the acoustic properties of inspiratory inhaler sounds and peak inspiratory flow rate (PIFR) in inhalers. In this study, healthy male (n=9) and female (n=7) participants were asked to inhale at an inspiratory flow rate (IFR) of 60 L/min in four commonly used inhalers (Turbuhaler(™), Diskus(™), Ellipta(™) and Evohaler(™)). Ambient inspiratory sounds were recorded from the mouthpiece of each inhaler and over the trachea of each participant. Each participant's PIFR was also recorded for each of the four inhalers. Results showed that gender and anthropometric features have the potential to influence the spectral properties of ambient and tracheal inspiratory inhaler sounds. It was also observed that males achieved statistically significantly higher PIFRs in each inhaler in comparison to females (p<;0.05). Acoustic features were found to be significantly different across inhalers suggesting that acoustic features are modulated by the inhaler design and its internal resistance to airflow.

Monitoring Inhaler Inhalations Using an Acoustic Sensor Proximal to Inhaler Devices

BACKGROUND

The efficacy of drug delivery from inhalers is very much dependent on the user's peak inspiratory flow rate (PIFR). Current methods to measure PIFR in inhalers are based on subjective checklists. There is a lack of methods currently available to objectively remotely monitor PIFR in pressurized metered dose inhalers (pMDIs) and dry powder inhalers (DPIs). In this study, for the first time, non-contact acoustic methods were employed to estimate PIFR through three commonly used inhalers (Diskus™ DPI, Turbuhaler™ DPI, and Evohaler™ pMDI) with the aim of applying these methods to remotely monitor inhaler inhalation technique in future clinical applications.

METHODS

Each inhaler was placed inside an airtight container connected to a spirometer to measure PIFR. A high quality microphone was placed 5 cm from the mouthpiece of the inhalers to record inhalation sounds. Over 2000 inhaler inhalation sounds were recorded from 11 healthy participants. A range of temporal and spectral acoustic features from the inhalation sounds were correlated with PIFR. The variation of acoustic features and the repeatability of the inhalation acoustic spectral profile were investigated to further characterize inhaler inhalation sounds and to determine the reliability of acoustics to estimate PIFR.

RESULTS

All acoustic features were significantly correlated with PIFR (p < 0.001). The mean power of the inhalation sound generated the most consistent correlation across all inhalers [R² = 0.77 (Diskus™), R² = 0.7 (Turbuhaler™), R² = 0.75 (Evohaler™)]. Acoustic features generated low variation and the spectral profile of inhalation sounds was repeatable regardless of flow rate, suggesting that acoustic methods are a reliable method of estimating PIFR.

CONCLUSIONS

The methods presented in this study may be employed in a wearable monitoring device in future applications to measure inhaler PIFR. Objective monitoring of PIFR in inhalers may help patients improve their inhaler inhalation technique and therefore may be of significant clinical benefit to both patients and clinicians.

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.

A New Modality Using Breath Sound Analysis to Evaluate the Control Level of Asthma

BACKGROUND

Reliable symptom assessment is essential in asthma management. We developed new technology for analyzing breath sounds and assessed its clinical usefulness for monitoring asthmatic children.

METHODS

Eighty asthmatic children and 59 non-asthmatic children underwent breath sound analysis in an asymptomatic state. Their asthma control was assessed by the Asthma Control Test^TM or Childhood ACTTM scores and divided into two groups, namely, well-controlled (perfect) (n = 19) and not well-controlled (not perfect) (n = 61). Breath sounds were recorded using two sensors, located on the right anterior chest and trachea. We calculated the acoustic transfer characteristics between the two points, which indicated the relationship between frequencies and attenuation during breath sound propagation. Two indices of sound parameters, the chest wall sound index (CWI) and the tracheal sound index (TRI), were calculated from the transfer characteristics and tracheal sounds. We also developed a new parameter, the breath sound index (BSI), on a 2-dimensional diagram of CWI and TRI and tried to determine whether BSI may clarify asthma control better than CWI or TRI alone.

RESULTS

There was a significant difference in TRI and BSI between asthmatic and non-asthmatic children (p = 0.007, p < 0.001). There was a significant difference in CWI and TRI between the well-controlled and not-wellcontrolled groups (p < 0.001). BSI discriminated between the two groups accurately (p < 0.001). The sensitivity and specificity of BSI for asthma control were 83.6% and 84.2%, respectively.

CONCLUSIONS

Asthma control could be evaluated using a new index calculated from breath sound analysis.

Evaluation of airflow limitation using a new modality of lung sound analysis in asthmatic children

BACKGROUND

Reliable assessment of not only symptoms but also lung function is essential in asthma management. We developed a new technology for analyzing lung sounds and assessed its clinical usefulness in asthmatic children.

METHODS

Forty-four children underwent lung sound recording with simultaneous airflow measurement using a sensor on the upper right anterior chest. We calculated a sound parameter index from the amplitude of inspiratory lung sounds at 700 Hz (ic700). ic700 were compared depending on flow and body size. In addition, 184 asthmatic children and 16 non-asthmatic children underwent lung sound analysis and lung function test in an asymptomatic state. In the asthma group, 135 children received treatment continually. The untreated asthma group included 28 children who had never received treatment continually and 21 children who had not been treated for at least 1 year. The asthmatic children were divided into four classes according to asthma severity. ic700 were compared depending on spirometric parameters and asthma severity classification.

RESULTS

The influences of flow and body size were negligible for ic700. ic700 correlated with FEV1%, MMF and FEF50 (r = -0.436, -0.339 and -0.302, respectively). There was a significant difference of ic700 between asthmatic and non-asthmatic children (p < 0.001), and ic700 correlated with the classification of asthma severity (p < 0.001). The ic700 scores of the severe group were higher than those of the intermittent group and non-asthmatic children.

CONCLUSIONS

It was possible to evaluate airway dysfunction of asthma using ic700, which was calculated non-invasively by analyzing lung sounds alone, without measuring body size and airflow.

Prediction of airway inflammation in patients with asymptomatic asthma by using lung sound analysis

BACKGROUND

The intensity and frequency of sounds in a lung sound analysis (LSA) may be related to airway constriction; however, whether any factors of an LSA can predict airway eosinophilic inflammation in patients with asthma is unknown.

OBJECTIVE

To determine whether an LSA can predict airway eosinophilic inflammation in patients with asymptomatic asthma.

METHODS

The expiratory-inspiratory ratios of sound power in the low-frequency range (E-I LF) from 36 patients with asymptomatic asthma were compared with those of 14 healthy controls. The relations of E-I LF with airway eosinophilic inflammation were analyzed. The E-I LF cutoff value for predicting airway eosinophilic inflammation also was analyzed.

RESULTS

The mean ± SD E-I LF was higher in the patients with asthma and with increased sputum eosinophils than in those patients without increased sputum eosinophils (0.45 ± 0.24 vs 0.20 ± 0.12; P < .001) or in the healthy controls (0.25 ± 0.10; P = .003). A multiple regression analysis showed that the sputum eosinophil ratio and exhaled nitric oxide were independently correlated with E-I LF, P = .0003 and P = .032, respectively. For the prediction of increased sputum eosinophils and increased fractional exhaled nitric oxide levels, the E-I LF thresholds of 0.29 and 0.30 showed sensitivities of 0.80 and 0.74 and specificities of 0.83 and 0.77, respectively.

CONCLUSIONS

We showed that LSAs can safely predict airway inflammation of patients with asymptomatic asthma.

Physiological acoustic sensing based on accelerometers: a survey for mobile healthcare

This paper reviews the applications of accelerometers on the detection of physiological acoustic signals such as heart sounds, respiratory sounds, and gastrointestinal sounds. These acoustic signals contain a rich reservoir of vital physiological and pathological information. Accelerometer-based systems enable continuous, mobile, low-cost, and unobtrusive monitoring of physiological acoustic signals and thus can play significant roles in the emerging mobile healthcare. In this review, we first briefly explain the operation principle of accelerometers and specifications that are important for mobile healthcare. Applications of accelerometer-based monitoring systems are then presented. Next, we review a variety of accelerometers which have been reported in literatures for physiological acoustic sensing, including both commercial products and research prototypes. Finally, we discuss some challenges and our vision for future development.

The development of an automated device for asthma monitoring for adolescents: methodologic approach and user acceptability

BACKGROUND

Many adolescents suffer serious asthma related morbidity that can be prevented by adequate self-management of the disease. The accurate symptom monitoring by patients is the most fundamental antecedent to effective asthma management. Nonetheless, the adequacy and effectiveness of current methods of symptom self-monitoring have been challenged due to the individuals' fallible symptom perception, poor adherence, and inadequate technique. Recognition of these limitations led to the development of an innovative device that can facilitate continuous and accurate monitoring of asthma symptoms with minimal disruption of daily routines, thus increasing acceptability to adolescents.

OBJECTIVE

The objectives of this study were to: (1) describe the development of a novel symptom monitoring device for teenagers (teens), and (2) assess their perspectives on the usability and acceptability of the device.

METHODS

Adolescents (13-17 years old) with and without asthma participated in the evolution of an automated device for asthma monitoring (ADAM), which comprised three phases, including development (Phase 1, n=37), validation/user acceptability (Phase 2, n=84), and post hoc validation (Phase 3, n=10). In Phase 1, symptom algorithms were identified based on the acoustic analysis of raw symptom sounds and programmed into a popular mobile system, the iPod. Phase 2 involved a 7 day trial of ADAM in vivo, and the evaluation of user acceptance using an acceptance survey and individual interviews. ADAM was further modified and enhanced in Phase 3.

RESULTS

Through ADAM, incoming audio data were digitized and processed in two steps involving the extraction of a sequence of descriptive feature vectors, and the processing of these sequences by a hidden Markov model-based Viterbi decoder to differentiate symptom sounds from background noise. The number and times of detected symptoms were stored and displayed in the device. The sensitivity (true positive) of the updated cough algorithm was 70% (21/30), and, on average, 2 coughs per hour were identified as false positive. ADAM also kept track of the their activity level throughout the day using the mobile system's built in accelerometer function. Overall, the device was well received by participants who perceived it as attractive, convenient, and helpful. The participants recognized the potential benefits of the device in asthma care, and were eager to use it for their asthma management.

CONCLUSIONS

ADAM can potentially automate daily symptom monitoring with minimal intrusiveness and maximal objectivity. The users' acceptance of the device based on its recognized convenience, user-friendliness, and usefulness in increasing symptom awareness underscores ADAM's potential to overcome the issues of symptom monitoring including poor adherence, inadequate technique, and poor symptom perception in adolescents. Further refinement of the algorithm is warranted to improve the accuracy of the device. Future study is also needed to assess the efficacy of the device in promoting self-management and asthma outcomes.

Lung sounds in bronchial asthma

Modern understanding of lung sounds started with a historical article by Forgacs. Since then, many studies have clarified the changes of lung sounds due to airway narrowing as well as the mechanism of genesis for these sounds. Studies using bronchoprovocation have shown that an increase of the frequency and/or intensity of lung sounds was a common finding of airway narrowing and correlated well with lung function. Bronchoprovocation studies have also disclosed that wheezing may not be as sensitive as changes in basic lung sounds in acute airway narrowing. A forced expiratory wheeze (FEW) may be an early sign of airway obstruction in patients with bronchial asthma. Studies of FEW showed that airway wall oscillation and vortex shedding in central airways are the most likely mechanisms of the generation of expiratory wheezes. Studies on the genesis of wheezes have disclosed that inspiratory and expiratory wheezes may have the same mechanism of generation as a flutter/flow limitation mechanism, either localized or generalized. In lung sound analysis, the narrower the airways are, the higher the frequency of breathing sounds is, and, if a patient has higher than normal breathing sounds, i.e., bronchial sounds, he or she may have airway narrowing or airway inflammation. It is sometimes difficult to detect subtle changes in lung sounds; therefore, we anticipate that automated analysis of lung sounds will be used to overcome these difficulties in the near future.

Elimination of vesicular sounds from pulmonary crackle waveforms

Pulmonary crackles and their parameters are very useful in the diagnosis of pulmonary disorders. A new automatic method has been proposed for the elimination of background vesicular sound from crackle signal with a view to introduce minimum distortion to crackle parameters. A region of interest is designated and a distortion metric based on the correlation between raw and filtered waveforms in that region is defined. Filter cut-off frequency is estimated based on the distortion metric. To reduce computational cost, a regression analysis is also realized which predicts a new fitted cut-off frequency from the estimated cut-off frequency. As a comparison basis, wavelet filtering is also applied on the same data. The algorithm is validated on simulated crackles superimposed on recorded vesicular sound with results indicating that filtering is achieved with minimal distortion of crackle parameters. The algorithm is also applied on real crackles from subjects with various respiratory disorders. The results show the extent of the effect of vesicular sound on crackle parameters, emphasizing the significance of proper filtering in crackle studies.

Limitations in the use of median frequency for lung sound analysis

The aim of this paper is to investigate methods of standardizing lung sound analysis, with a view to supplementing traditional spirometric air flow measurements to help in the diagnosis of asthma and to provide a measure of the effectiveness of treatment. Lung sounds were measured in nine patients with asthma and five control subjects, alongside air flow measurements of forced expiratory volume (FEV1) and forced vital capacity (FVC). The patients were administered the bronchodilator, salbutamol, to assess how effective these measurement techniques were for quantifying its effect. The results agree with previous studies, that analysis of lung sounds is a potentially useful tool for indicating air flow changes. The results, however, also demonstrate that the emerging standard of 'F50' or 'median frequency' should be treated with great caution because of its high sensitivity to the measurement frequency range. F50 is very unlikely to provide a reliable single indicator of lung condition.

Classification of asthmatic breath sounds: preliminary results of the classifying capacity of human examiners versus artificial neural networks

For continuous monitoring of the respiratory condition of patients, e.g., at the intensive care unit, computer assistance is required. Existing mechanical devices, such as the peak expiratory flow meter, provide only with incidental measurements. Moreover, such methods require cooperation of the patient, which at, e.g., the ICU is usually not possible. The evaluation of complicated phenomena such as asthmatic respiratory sounds may be accomplished by use of artificial neural networks. To investigate the merit of artificial neural networks, the capacities of neural networks and human examiners to classify breath sounds were compared in this study. Breath sounds were in vivo recorded from 50 school-age children with asthma and from 10 controls. Sound intervals with a duration of 20 seconds were randomly sampled from asthmatics during exacerbation, asthmatics in remission, and controls. The samples were digitized and related to peak expiratory flow. From each interval, two full breath cycles were selected. Of each selected breath cycle, a Fourier power spectrum was calculated. The so-obtained set of spectral vectors was classified by means of artificial neural networks. Humans evaluated graphic displays of the spectra. Human examiners could not clearly discriminate between the three groups by inspecting the spectrograms. Classification by self-classifying neural networks confirmed the existence of at least three classes; however, discrimination of 11 classes seemed more appropriate. Good results were obtained with supervised networks: as much as 95% of the training vectors could be classified correctly, and 43% of the test vectors. The three patient groups, as discriminated in advance, do not correspond with three sharply separated sets of spectrograms. More than three classes seem to be present. Humans cannot take up the spectral complexity and showed negative classification results. Artificial neural networks, however, are able to handle classification tasks and show positive results.

Analysis of tracheal sounds during forced exhalation in asthma patients and normal subjects: bronchodilator response effect

PURPOSE

During the past 10 years, the acoustic analysis of breath sounds has been used as a diagnostic tool in patients suffering from obstructive respiratory diseases. Acoustic analysis might be able to monitor the response to bronchodilator therapy in a clinical setting. So far, few studies have been carried out in asthmatic patients. To assess the responses of a sampling of asthma patients to an inhaled bronchodilator (terbutaline) by means of spectral analysis of the tracheal sound performed during forced expiratory maneuvers.

MATERIAL AND METHODS

Seventeen nonsmoking asthma patients (9 were male, 8 were female) who had been suffering from the disease for > or = 15 years were included in the study, as were 15 normal subjects (7 were male, 8 were female). The average age (+/- SD) was 56.5 +/- 15.2 years (FVC, 2.7 +/- 0.9 L [63.4%]; FEV1, 1.5 +/- 0.6 L [53.0%]). The tracheal sounds were collected during three forced expiratory maneuvers with a sampling frequency of 5,000 Hz and were analyzed by applying a 16-parameter autoregressive model.

RESULTS

The centroid frequency decreased after the bronchodilator was given at different flow segments between 1.2 and 0.4 L/s, with significant changes between 0.6 and 0.4 L/s.

CONCLUSIONS

Patients with asthma showed changes in the spectral acoustic analysis frequencies after the administration of a bronchodilator drug (terbutaline) during forced expiratory maneuvers.

Characteristics and diagnostic significance of spontaneous wheezing in children with asthma: results of continuous in vivo sound recording

The characteristics and diagnostics of wheezing during induced airway obstruction are well documented. The present study addressed (a) the characteristics of spontaneous wheezing with respect to a possible distinction between wheezes during in vivo versus induced airway obstruction, and (b) the relationship between in vivo wheezing and fluctuations in peak expiratory flow (PEF). Tracheal sounds were continuously recorded from 50 children and adolescents with asthma and 10 without asthma in the home environment. Wheezes underwent a qualitative analysis, including their concomitant sound frequencies. Presence of wheezing was scored by two examiners independently and was related to PEF. Spontaneous wheeze varied from solitary rhonchi to prolonged rhythms of loud stridor, and resembled the "induced" wheezes recorded previously. Power spectra showed that the spectral contents (frequency distribution) were comparable, although the in vivo patterns were more prolonged in duration. The diagnostic sensitivity and specificity of wheezing for a reduction in PEF of >20% were 88% and 92%, respectively. It was concluded that in vivo wheeze resembled induced wheeze and was a diagnostically reliable symptom with respect to asthma exacerbations.

Auscultation revisited: the waveform and spectral characteristics of breath sounds during general anesthesia

Although auscultation is commonly used as a continuous monitoring tool during anesthesia, the breath sounds of anesthetized patients have never been systematically studied. In this investigation we used digital audio technology to record and analyze the breath sounds of 14 healthy adult patients receiving general anesthesia with positive pressure ventilation. Sounds recorded from inside the esophagus were compared to those recorded from the surface of the chest, and corresponding airflow was measured with a pneumotachograph. The sound samples associated with inspiratory and expiratory phases were analyzed in the time domain (RMS amplitude) and frequency domain (peak frequency, spectral edge, and power ratios). There was a positive linear correlation (R2 > 0.9) between inspiratory flow and sound amplitude in the precordial and esophageal samples of all patients. The RMS amplitude of the inspiratory and expiratory sounds was approximately 13 times greater when recorded from inside the esophagus than from the surface of the chest in all patients at all flows (p < 0.001). The peak frequency (Hz) was significantly higher in the esophageal recordings than the precordial samples (298 +/- 9 vs 181 +/- 10, P < 0.0001), as was the 97% spectral edge (Hz) (740 +/- 7 vs 348 +/- 16, P < 0.0001). In the adult population esophageal stethoscopes yield higher frequencies and greater amplitude than precordial stethoscopes. Quantification of lung sounds may provide for improved monitoring and diagnostic capability during anesthesia and surgery.

Chest surface mapping of lung sounds during methacholine challenge

Wheeze as an indicator of airway obstruction during bronchoprovocation lacks sensitivity. We therefore studied whether induced airway narrowing is revealed by changes in normal (vesicular) lung sounds. Fifteen subjects with asthma and nine healthy controls, aged 8-16 years, performed a standardized methacholine challenge. Respiratory sounds were recorded with eight contact sensors, placed posteriorly over the right and left superior and basal lower lobes, and anteriorly over both upper lobes, the right middle lobe, and the trachea. Average spectra of normal inspiratory and expiratory sounds, excluding wheeze, were characterized in 12 asthmatics and 9 controls at flows of 1 +/- 0.2 L/sec. Airway narrowing was accompanied by significant changes in lung sounds, but not in tracheal sounds. Lung sounds showed a decrease in power at low frequencies during inspiration and an increase in power at high frequencies during expiration. These changes already occurred at a decrease in forced expiratory volume in 1 sec of less than 10% from baseline and were fully reversed after inhalation of salbutamol. Thus, lung sounds were sensitive to changes in airway caliber, but were not specific indicators of bronchial hyperresponsiveness.

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

STUDY OBJECTIVE

To obtain a basis for assessment of changes in breath sound spectra in patients with pulmonary diseases, short-term and day-to-day repeatability of spectral parameters was studied.

DESIGN

Breath sounds were recorded simultaneously from the trachea and from the chest twice at an interval of 15 min (short-term repeatability) and of 1 to 3 days (day-to-day repeatability). During recordings, air flow at the mouth was controlled, the target inspiratory and expiratory peak flow being 1.25 L/s. Inspiratory and expiratory breath sound spectra were averaged over 7 to 10 successive respiratory cycles. The repeatability of sound intensity (RMS), frequency of maximum intensity (Fmax), and median frequency (F50) was analyzed with analysis of variance.

PARTICIPANTS

Short-term repeatability was studied in 10 healthy nonsmoking men (age 25 to 44 years), and day-to-day repeatability was studied in 10 healthy nonsmoking men (age 23 to 41 years) and in 12 patients with clinically stable fibrosing alveolitis (age 35 to 82 years).

RESULTS

Short-term coefficient of variation (CoV) of Fmax and F50 was 2.6 to 6.7% when recorded from the chest, and 6.2 to 8.7% when recorded from the trachea. Day-to-day CoV of Fmax and F50 in healthy subjects was 4.7 to 8.5% and 5.0 to 8.7% recorded from the chest or from the trachea, respectively. Inspiratory day-to-day variation in those parameters was higher in patients with fibrosing alveolitis. CoV of RMS was high, ranging from 18 to 47% in different subject groups and sampling situations.

CONCLUSIONS

Repeatability of F50 of averaged flow-controlled lung sound spectra is good both in healthy subjects and in patients with fibrosing alveolitis. Thus, F50 of respiratory sound spectra may be useful in monitoring of changes induced by respiratory diseases and interventions. These results emphasize the importance of standardization of recording conditions and of analyzing techniques.

Classification of lung sounds in patients with asthma, emphysema, fibrosing alveolitis and healthy lungs by using self-organizing maps

The performance of the self-organizing map (SOM), an artificial neural network, was evaluated in the classification of lung sounds. Patients with asthma (n = 8), emphysema (n = 8) and fibrosing alveolitis (n = 8), and patients with healthy lungs (n = 8) were selected for the study. Fast Fourier transform (FFT) spectra from midinspiratory breath sounds recorded at the right lower lobe area were used to construct feature vectors in the learning and classification process of SOM. The sound segments did not contain wheezing sounds. The lung sounds of 25/32 (78%) patients were classified correctly, with an overall kappa (kappa) value of 0.71. The agreement between the clinical and proposed diagnoses based on classification of lung sounds was good among patients with emphysema (kappa = 0.92) and those with healthy lungs (kappa = 0.83), but only moderate among patients with asthma (kappa = 0.52) and fibrosing alveolitis (kappa = 0.54). This is due to the limitations in distinguishing breath sounds of asthmatics without wheezing sounds from those with crackles in fibrosing alveolitis by the spectral pattern alone. The results indicate that SOM based on FFT spectra is potentially useful in the classification of lung sounds, e.g. in health screening or in differential diagnosis of pulmonary disorders. To enhance the performance of SOM, other features of lung sounds should be combined with FFT spectra.

Significant differences in flow standardised breath sound spectra in patients with chronic obstructive pulmonary disease, stable asthma, and healthy lungs

BACKGROUND

Spectral characteristics of breath sounds in asthma and chronic obstructive pulmonary disease (COPD) have not previously been compared, although the structural differences in these disorders might be reflected in breath sounds.

METHODS

Flow standardised inspiratory breath sounds in patients with COPD (n = 17) and stable asthma (n = 10) with significant airways obstruction and in control patients without any respiratory disorders (n = 11) were compared in terms of estimates of the power spectrum. Breath sounds were recorded simultaneously at the chest and at the trachea.

RESULTS

The median frequency (F50) of the mean (SD) breath sound spectra recorded at the chest was higher in asthmatics (239 (19) Hz) than in both the control patients (206 (14) Hz) and the patients with COPD (201 (21) Hz). The total spectral power of breath sounds recorded at the chest in terms of root mean square (RMS) was higher in asthmatics than in patients with COPD. In patients with COPD the spectral parameters were not statistically different from those of control patients. The F50 recorded at the trachea in the asthmatics was significantly related to forced expiratory volume in one second (FEV1) (r = -0.77), but this was not seen in the other groups.

CONCLUSIONS

The observed differences in frequency content of breath sounds in patients with asthma and COPD may reflect altered sound generation or transmission due to structural changes of the bronchi and the surrounding lung tissue in these diseases. Spectral analysis of breath sounds may provide a new non-invasive method for differential diagnosis of obstructive pulmonary diseases.

Potential for lung sound monitoring during bronchial provocation testing

BACKGROUND

The use of lung sound monitoring during bronchial provocation testing has not been clearly demonstrated. The appearance of wheeze and changes in inspiratory breath sound intensity have been analysed and related to changes in spirometric parameters and to airways hyperresponsiveness.

METHODS

Lung sounds were recorded in 38 patients undergoing a routine carbachol airway challenge (CAC) test. Spirometric testing was performed before and after the inhalation of each of five cumulative doses of 320 micrograms carbachol; a fall in forced expiratory volume in one second (FEV1) by 20% or more was considered as significant. Lung sound analysis was carried out using a computerised system.

RESULTS

The CAC test was positive (CAC+) in 21 patients and negative (CAC-) in 17. At the final stage of the challenge, wheeze was identified in 10 positive patients (48%) and in one negative patient (6%); in non-wheezers the inspiratory breath sound intensity decreased significantly from baseline in 11 CAC+ patients (mean (SD) change -35 (24%)) but not in 16 CAC- patients (mean (SD) change 5 (24%)). In all non-wheezers a linear relationship was found between breath sound intensity and the squared inspiratory airflow (r = 0.53-0.92) which became looser after the inhalation of carbachol.

CONCLUSION

When unertaking bronchial provocation testing the accurate identification of wheeze may prove useful in avoiding or shortening the test because of the presumed relationship between wheeze and airways hyperresponsiveness. Changes in breath sound intensity may also be useful, but further studies are required to define the threshold for significant changes in this index.

Frequency distribution of breath sounds as an indicator of bronchoconstriction during histamine challenge test in asthmatic children

In order to study changes in respiratory sounds associated with acute bronchoconstriction and -dilatation, breath sounds of 11 children with asthma (age range, 10-14 years) were recorded at the chest and at the trachea during histamine challenge test and after subsequent bronchodilatation. The changes in frequency spectra of breath sounds were compared with simultaneous changes in forced expiratory volume in 1 second (FEV1). In seven children who responded to histamine with a decrease in FEV1 of more than 15%, there was a significant relationship between percentage change in FEV1 (delta FEV1) and percentage change in median frequency (delta F50) of expiratory breath sounds recorded at the chest (r = 0.865; beta = -0.706, P = 0.0001) and at the trachea (r = 0.888; beta = -1.12, P = 0.0001). The association between breath sound intensity and FEV1 was weaker. Based on ANOVA, the increase of F50 during the challenge test was significantly larger in children who responded to histamine than in those who were non-responsive (P = 0.0016). At the chest, a decrease of 15% in FEV1 corresponded to an increase of 8% in expiratory F50. The provocative dose of histamine inducing a decrease of 15% in FEV1 (PD15FEV1) and the provocative dose causing an increase of 8% in F50 (PD8F50) were significantly related (r = 0.927, P = 0.003). We conclude that spectral analysis of breath sounds can be used to indicate airway obstruction during bronchial challenge tests in children, and may be adapted for tests in pre-school children. The results suggest that the same mechanisms that induce airflow limitation due to inhaled histamine may generate an increase in frequency content of breath sounds in children with asthma.