Time-expanded Waveform Analysis Research Articles

Feature Extraction and Classification Methods for Lung Sounds

The lung sounds is a non-stationary signal. It is a major challenge to analyze and differentiate the type of pulmonary disorder based on lung sounds. This paper presents a detailed review of existing methods of feature extraction and classification of Lung sounds for diagnosing the various types of pulmonary disorder. The different methods like spectral analysis, Cepstrum and Mel- Cepstrum, Hilbert Huang Transform, Spectrogram and 2D representation, Wavelet method, time expanded waveform analysis, Hidden Markov model, Auto Regressive model, and Neural Network are being discussed here. All the discussed methods automatically recognise the different types of lung sounds and pulmonary disorder based on features extracted from recorded lung sounds. The paper covered all the suited existing methods which can effectively detect the lung diseases. As per the result of this analysis, it has been found that still more work is required to be done in the screening and classification of chronic Lung diseases. Chronic lung diseases, having similar symptoms and which are very hard to be distinguished and classified. So, therefore, some suitable work needed to be done so that it could effectively support the physicians for taking diagnosis decisions and for giving the correct treatment without any delay in such chronic diseases also.

A new versatile PC-based lung sound analyzer with automatic crackle analysis (HeLSA); repeatability of spectral parameters and sound amplitude in healthy subjects

A versatile PC-based lung sound analyzer has been developed for short-term recording and analysis of respiratory sounds in research and clinical applications. The system consists of two sound sensors, a flow sensor, a filtering signal amplifier and a PC with a data acquisition card and software for measurement and analysis of the sounds. The analyses include phonopneumography, time expanded waveform analysis, spectral analysis with time averaged Fast Fourier Transform, frequency analysis in time domain (sonogram), and automatic detection and waveform analysis of crackles. Short-term repeatability of spectral parameters of tracheal and lung sounds was studied in 10 healthy subjects. The coefficients of variation (CoV) of the averaged quartile frequencies (F25, F50 and F75) of lung sounds during flow-controlled tidal breathing were 3.7, 4.0 and 8.9% in expiration and 2.7, 3.5 and 4.5% in inspiration, respectively. CoVs of the averaged F25, F50 and F75 of expiratory tracheal sounds were 6.9, 3.0 and 2.4%, and those of inspiratory tracheal sounds 6.3, 2.6 and 3.3%, respectively. Examples of lung sound analysis of samples containing adventitious sounds such as crackles and wheezes are presented. The results indicate that the median frequency has the best repeatability of quartile frequencies of breath sounds and they suggest that the variations of those parameters are low enough for diagnostic purposes. The results also suggest that the analyzer can be a useful new tool for pulmonary research in the fields of physiological and clinical short-term studies of respiratory sounds.

Crackles: recording, analysis and clinical significance.

Crackles are short interrupted breath sounds usually associated with pulmonary disorders. According to present opinion, a crackle is generated when an abnormally closed airway opens during inspiration or closes at the end of expiration. The timing of crackles in breathing cycles can be assessed with phonopneumography, their duration with time-expanded waveform analysis, and their pitch with analysis of frequency spectra. The timing, pitch and waveform of crackles are different in pulmonary disorders reflecting different pulmonary pathophysiology. This review deals with the genesis, auscultation, recording and analysis of crackles, with an emphasis on modern signal-processing methods.

Assessment of prosthetic heart valve sounds using time expanded wave form analysis

Assessment of prosthetic heart valve sounds using time expanded wave form analysis

Clinical utility of chest auscultation in common pulmonary diseases.

In this investigation we applied the techniques of lung sound mapping and time-expanded wave-form analysis to four common diseases that involve the lung: interstitial pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), and pneumonia (Pn). Twenty subjects were studied in each group. We also studied 15 subjects without evidence of lung disease. Differences in timing, character, and location were observed, which allowed separation among these groups. Multiple logistic regression models were created and tested by the bootstrap method. Regression models correctly classified 68 and 79% of subjects. Area under the receiver operating curve ranged from 0.96 for IPF and CHF to 0.80 for COPD. We conclude that auscultatory differences exist among common pulmonary conditions and that statistical models based on auscultatory data perform well in predicting diagnostic categories.

Lung crackle characteristics in patients with asbestosis, asbestos-related pleural disease and left ventricular failure using a time-expanded waveform analysis — a comparative study

The aim of this study is to investigate lung crackle characteristics by time-expanded waveform (TEW) analysis in patients with asbestosis (AS), asbestos-related pleural disease (ARPD) and left ventricular failure (LVF). TEW was performed on a 33 s recording from each of 40 patients (12 AS, 17 ARPD and 11 LVF). They were 38 men and two women. Crackles on TEW were counted during inspiration and expiration, and the timing of clusters of crackles with respect to inspiration and expiration was noted. A total of 1117 crackles were identified. The initial deflection width (IDW) and the two cycle duration (2CD) were calculated for all crackles within one respiratory cycle for each patient (total of 298 crackles). Crackles were detected by TEW in all patients with AS, in seven patients with ARPD and in nine patients with LVF. Crackles in AS were mainly fine, mid- to late-inspiratory. Crackles in LVF took three patterns; in the first there were repetitive mid- to late inspiratory crackles similar to those seen in AS except that the crackles in LVF tended to be medium and coarse as well as fine (three patients); in the second crackles started early in inspiration followed by a crackle-free period then by another cluster of crackles lasting to the end of inspiration and to the early third of expiration (four patients) and in the third there were repetitive expiratory crackles with no or few inspiratory crackles (two patients). Crackles in ARPD generally took the configuration of fine crackles but another type of crackle preceded by a sharp deflection followed by an M-shape oscillation then by the largest oscillation was also found. IDW and 2CD for inspiratory crackles in ARPD were shorter than those in AS and LVF (for IDW P < 0·009 and P < 0·003 compared with AS and LVF respectively and for 2CD, P < 0·006 and P < 0·003 compared with AS and LVF respectively). IDW and 2CD in AS tended to be shorter than these for LVF but these results did not reach statistical significance. It is concluded that many differences exist between crackles in AS, LVF and ARPD. Differences in nature and timing of crackles may reflect differences in the pathophysiology and mechanism giving rise to lung crackles in these conditions. TEW provides informations of diagnostic value.

The Prevalence of Auscultatory Crackles in Subjects Without Lung Disease

Crackles heard during auscultation of the lungs are generally considered an abnormal physical finding. This study was done to see if crackles could be induced to occur in the lungs of normal subjects. We studied 52 nonsmoking normal subjects by listening at the right and left posterior bases and over the lower right anterior chest during inspiration from functional residual capacity (FRC) and then during inspiration from residual volume (RV). Crackles were recorded on magnetic tape for subsequent time-expanded waveform analysis. No crackles were heard at any of the three sites during inhalation from FRC. Of 52 subjects, 26 had crackles over the anterior site when inhaling from RV. These crackles were often profuse, loud, and easily recorded. Waveform analysis revealed these crackles in normal subjects to be similar to those occurring in patients with interstitial lung diseases. We conclude that crackles, heard over the anterior chest during inspiration from low lung volumes, are not necessarily adventitious sounds.

Visual lung-sound characterization by time-expanded wave-form analysis.

To characterize lung sounds objectively, we examined, by means of time-amplitude plots, selected tape recordings of auscultatory phenomena considered by six observers to be typical of those in a standard classification. Normal lung sounds could not consistently be visually distinguished from adventitious sounds at conventional chart recorder speeds of 100 mm per second or less, but the differentiation was easily achieved when the time scale of the plots was raised to 800 mm per second. When discontinuous sounds (rales, crackles or crepitations) were heard clinically, the time-expanded wave forms showed intermittent "discontinuous" deflections usually less than 10 msec in duration. When continuous sounds (rhonchi or wheezes) were heard, the deflections were usually more than 250 msec. Time-expanded wave form analysis provides reproducible visual displays that allow documentation of the differentiating features of lung sounds and enhances the diagnostic utility of the sounds.