Automated Spectral Characterization of Wheezing in Asthmatic Children
TL;DR: Wheezing was found to be strongly dependent upon air flow, and generally followed the changes in pulmonary function as indicated by the forced expiratory volume at 1 s (FEV1).
Abstract: Breath sounds were recorded in normal and asthmatic children over the chest and trachea. The power spectra of the sounds were analyzed for peaks of high amplitude and high frequency as indications of wheezing. The percent of inspiration and expiration spent wheezing was used as an indication of the severity of bronchial obstruction. Wheezing was found to be strongly dependent upon air flow, and generally followed the changes in pulmonary function as indicated by the forced expiratory volume at 1 s (FEV1). The trachea was found to be a better location for analyzing wheezes than the lung.
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622 citations
16 May 2008
TL;DR: The study includes a description of the various techniques that are being used to collect auscultation sounds, a physical description of known pathologic sounds for which automatic detection tools were developed, and a search for new markers to increase the efficiency of decision aid algorithms and tools.
Abstract: Objective: This paper describes state of the art, scientific publications and ongoing research related to the methods of analysis of respiratory sounds.
Methods and material: Review of the current medical and technological literature using Pubmed and personal experience.
Results: The study includes a description of the various techniques that are being used to collect auscultation sounds, a physical description of known pathologic sounds for which automatic detection tools were developed. Modern tools are based on artificial intelligence and on technics such as artificial neural networks, fuzzy systems, and genetic algorithms…
Conclusion: The next step will consist in finding new markers so as to increase the efficiency of decision aid algorithms and tools.
216 citations
Cites background from "Automated Spectral Characterization..."
...- Infections such as croup (infection that generally affects infants from less than three years), whooping cough, laryngitis, acute tracheobronchilis - Laryngo-, tracheo-, or bronchomalacia - Laryngeal or tracheal tumours - Tracheal stenosis - Emotional laryngeal stenosis - Foreign body aspiration - Airway compression - Asthma: wheeze detection in asthma [34], identifi cation of nocturnal asthma [35],....
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...Non stationary signals linked to lungs’ air volume variations The static characterisation of the process evolves in respiratory cycle [34][76]....
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TL;DR: An automatic technique for wheeze detection and monitoring using spectral analysis and the experimental and testing results justified the efficient performance and high noise robustness of the TF-WD.
206 citations
Cites background from "Automated Spectral Characterization..."
...Due to the difference in the filter properties of trachea and chest [28], wheezes recorded from sensors located at P2–P5 were distinguished from those acquired from sensors located at P1, in order to separately estimate the sensitivity and specificity indices....
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01 Jan 2000
TL;DR: The terms collected in this paper of the ComputerizedRespiratory Sound Analysis (CORSA) guidelines includeterms of respiratory diseases, pulmonary physiology, acoustics, automatic data handling and instrumentation, as well as general terms that have not yet been definedclearly in the literature, or deﷁned in a controversial way.
Abstract: Computerized lung sound analysis is a multidiscipli-nary field. Work in this field would be easier if the terms tobe used were clearly defined. This chapter is meant fordoctors, engineers and other persons who are workingwith respiratory sound analysis.The terms collected in this paper of the ComputerizedRespiratory Sound Analysis (CORSA) guidelines includeterms of respiratory diseases, pulmonary physiology,acoustics, automatic data handling and instrumentation.The list includes terms that have not yet been definedclearly in the literature, or defined in a controversial way.Some terms included have been defined elsewhere, e.g .the terms of lung function variables, but were regardeduseful to be included in this selection in order to improvethe readability. Some general terms have also beenincluded in cases where the common sense meaning ofthat term is different from the specific meaning in the dis-cipline of respiratory sound research.Each definition of a term includes, as a rule, a short for-mal definition, some additional characteristics and refer-ences if available. Official guidelines (European Respir atorySociety Guidelines for Lung Function Studies, AmericanThoracic Society publications) position papers, statementsand reports of international societies as well as originalpapers and review articles in scientific international jour-nals have been used as references. Handbooks have alsobeen used.The terms defined are listed in alphabetical order, andhave been used systematically in the CORSA guidelines.For the definition of different kinds of sounds, anattempt has been made to make clear distinctions betweenadjectives indicating locations (like lung, trachea, etc.),
169 citations
Cites methods from "Automated Spectral Characterization..."
...Angular accelerometers are used for rotary motion [1]....
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TL;DR: A wearable and wireless breathing sound monitoring system for real-time wheeze detection and a breathing sounds analysis algorithm was designed to continuously extract and analyze the features of breathingSounds to provide the objectively quantitative information of breathing sounds to professional physicians.
Abstract: 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.
92 citations
Cites result from "Automated Spectral Characterization..."
...40 ms, and this also fits the results in previous studies (over 150 ms) [23,25]....
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References
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TL;DR: The theoretical approach to the "waterfall effect" leads to selection of the analogy of constricted open-channel flow to apply to the elastic network of airway tubes, and results are derived for the case of negligible friction by use of the Bernoulli principle.
Abstract: The mechanism limiting forced expiratory flow is explained on the basis that a local flow velocity reaches the local speed of wave propagation at a point, called the choke point, in intrathoracic a...
361 citations
TL;DR: Breath sounds picked up over the trachea were characterized by power spectra typical to a broad spectrum sound with a sharp decrease of power at a cut-off frequency that varied between 850 and 1,600 Hz among the 10 healthy subjects studied.
Abstract: An objective and accurate measurement and characterization of breath sounds was carried out by a fast-Fourier-transform frequency-domain analysis. Normal vesicular breath sounds, picked up over the chest wall of 10 healthy subjects showed a characteristic pattern: the power of the signal decreased exponentially as frequency increased. Since the log amplitude vs. log frequency relationships were linear, they could be characterized by the values of the slope and the maximal frequency. The average slope of the power spectrum curves was found to be (in dB/oct +/- SD) 13.0 +/- 1.4 over the base of the right lung, 12.6 +/- 2.4 over the base of the left lung, 9.8 +/- 1.4 over the interscapular region, and 14.4 +/- 4.3 over the right anterior chest. The maximal frequencies of inspiratory and expiratory breath sounds, picked up over the base of the right lung, were (in Hz +/- SD) 446 +/- 143 and 286 +/- 53 (P less than 0.01), over the base of the left lung 475 +/- 115 and 284 +/- 47 (P less than 0.01), over the interscapular region 434 +/- 130 and 338 +/- 77 (P less than 0.05), and over the right anterior chest 604 +/- 302 and 406 +/- 205 (P less than 0.05). Breath sounds picked up over the trachea were characterized by power spectra typical to a broad spectrum sound with a sharp decrease of power at a cut-off frequency that varied between 850 and 1,600 Hz among the 10 healthy subjects studied.
193 citations
TL;DR: 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.
Abstract: 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. (N Engl J Med 296:968–...
183 citations
TL;DR: Although characterization of wheezing has a general relationship to the severity of airway obstruction, an objective measurement of expiratory flow rate is necessary for the evaluation of each patient's condition.
Abstract: Ninety-three asthmatic patients were examined on 320 occasions for wheezing and peak expiratory flow rate (PEFR). The presence of a wheeze (either reported by the patient or found on examination) was associated with a significantly lower PEFR. Expiratory wheezing was usually accompanied by inspiratory wheezing; this biphasic wheezing was associated with a lower PEFR than only expiratory wheezing. Loudness and the high pitch of wheezing were associated with more severe obstruction. Most expiratory wheezing lasted throughout the entire expiration. Expiratory or inspiratory wheezing of high pitch, moderate to severe intensity, and spanning the entire phase of the breath was associated with a lower PEFR than wheezing without these characteristics. Although characterization of wheezing has a general relationship to the severity of airway obstruction, an objective measurement of expiratory flow rate is necessary for the evaluation of each patient's condition.
143 citations
97 citations