Auditory Detection of Simulated Crackles in Breath Sounds

Kiyokawa, Hiroshi; Greenberg, Matthew; Shirota, Kazuhiko; Pasterkamp, Hans

doi:10.1378/chest.119.6.1886

Cited by 75 publications

(52 citation statements)

References 29 publications

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“…not normally occurring) breath sounds has been standardised. Crackles (often referred to as crepitations in the UK and as rales in the USA), best detected during slow, deep breaths [9], are discontinuous, short explosive non-musical sounds predominating during inspiration and best heard over dependent lung regions [10,11] and sometimes associated with expiratory crackles [12]. They are considered to be produced by the sudden opening of abnormally closed small airways [12,13].…”

mentioning

confidence: 99%

Velcro crackles: the key for early diagnosis of idiopathic pulmonary fibrosis?

2012

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mentioning

confidence: 99%

Velcro crackles: the key for early diagnosis of idiopathic pulmonary fibrosis?

2012

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“…The inter-and intra-subject reliability of crackle IDW and 2CD measured using CALSA has never been previously investigated. There is, however, a consensus that the inter and intra-observer reliability of the detection of added lung sounds among health professionals using tape-recorders, audio-files or standard auscultation is generally poor (Elphick et al, 2004, Kiyokawa et al, 2001). The inter-subject reliability for both crackle variables studied (IDW and 2CD) in this research was found to be low, as shown by the uniformly significant ANOVA (p<0.001), indicating variability of mean crackles parameters across subjects.…”

Section: Discussionmentioning

confidence: 99%

“…Despite decades of subsequent research this theory has never been refuted. Currently, a crackle sound is believed to originate from the acoustic energy generated by pressure equalisation, resulting from a change in elastic stress after a sudden opening or closing of airways (Vyshedskiy et al, 2008, Nath andCapel, 1974), or when there is inflammation or oedema in the lungs (Kiyokawa et al, 2001). Crackles' short duration and, often, low intensity makes their discrimination and characterisation by standard auscultation difficult; and their detection becomes even more difficult when other breath sounds have greater intensity (Kiyokawa et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

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

2009

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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 Cycles 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 7 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;0.47ms; 2CD -2.12;1.87ms) and Smallest Real Difference (IDW 0.30;0.66ms; 2CD 1.57;2.42ms). 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.

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“…It is interesting to note that most of the actual studies related to crackles utilize the counting obtained by clinical experts using TEWA to validate the results. However, it has been shown that physicians have visual and auditory limitations to detect fine or coarse crackles [17]. Here, we hypothesize that 2D imaging of crackles distribution on the thoracic surface is feasible by processing multichannel acoustic information.…”

Section: Introductionmentioning

confidence: 94%

Acoustic thoracic image of crackle sounds using linear and nonlinear processing techniques

Charleston-Villalobos

Dorantes-Méndez

González-Camarena

et al. 2010

Med Biol Eng Comput

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In this study, a novel approach is proposed, the imaging of crackle sounds distribution on the thorax based on processing techniques that could contend with the detection and count of crackles; hence, the normalized fractal dimension (NFD), the univariate AR modeling combined with a supervised neural network (UAR-SNN), and the time-variant autoregressive (TVAR) model were assessed. The proposed processing schemes were tested inserting simulated crackles in normal lung sounds acquired by a multichannel system on the posterior thoracic surface. In order to evaluate the robustness of the processing schemes, different scenarios were created by manipulating the number of crackles, the type of crackles, the spatial distribution, and the signal to noise ratio (SNR) at different pulmonary regions. The results indicate that TVAR scheme showed the best performance, compared with NFD and UAR-SNN schemes, for detecting and counting simulated crackles with an average specificity very close to 100%, and average sensitivity of 98 ± 7.5% even with overlapped crackles and with SNR corresponding to a scaling factor as low as 1.5. Finally, the performance of the TVAR scheme was tested against a human expert using simulated and real acoustic information. We conclude that a confident image of crackle sounds distribution by crackles counting using TVAR on the thoracic surface is thoroughly possible. The crackles imaging might represent an aid to the clinical evaluation of pulmonary diseases that produce this sort of adventitious discontinuous lung sounds.

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Auditory Detection of Simulated Crackles in Breath Sounds

Cited by 75 publications

References 29 publications

Velcro crackles: the key for early diagnosis of idiopathic pulmonary fibrosis?

Velcro crackles: the key for early diagnosis of idiopathic pulmonary fibrosis?

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

Acoustic thoracic image of crackle sounds using linear and nonlinear processing techniques

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