For validation of the methodology, lung sounds recorded from three different repositories were used. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. Spontaneous breathing was not inferior to standardized breathing in reflecting lung disease.Īuscultation crackles lung sounds respiratory air flow wheezes.Ĭopyright © 2018 by Daedalus Enterprises.The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. Although adventitious sounds were found with similar frequency between the modes of breathing, less than half of these subjects were identified with both methods. The mode of breathing had an impact on both adventitious and normal lung sounds. During spontaneous breathing, increased mean intensity and median frequency during expiration were associated with an increased reporting of heart/lung diseases ( P =. Dyspnea was more frequently reported when expiratory wheezes were present, but this association was only statistically significant during standardized breathing ( P =. The mean intensity and median frequency of normal lung sounds were significantly higher during standardized breathing than during spontaneous breathing, both at inspiration (23.1 dB vs 20.1 dB and 391.6 Hz vs 367.3 Hz) and expiration (20 dB vs17.6 dB and 376.3 Hz vs 355 Hz). ![]() Nine subjects were identified with both methods (kappa = 0.32). Expiratory wheezes were heard in 18 subjects (15.5%) during spontaneous breathing and in 23 subjects during standardized breathing (19.8%). Only 5 subjects were identified with both methods (kappa = 0.13). Inspiratory crackles were heard in 19 subjects (16.4%) during spontaneous breathing and in 18 subjects during standardized breathing (15.5%). ![]() Intensity and frequency of normal lung sounds in the 100-2,000 Hz band were determined. Crackles and wheezes were identified by 4 observers. Lung sounds were recorded at 6 chest locations, first during spontaneous breathing and then during breathing with a standardized air flow of 1.5 L/s. The subjects reported heart/lung diseases and the degree of dyspnea, and spirometry was carried out. This study evaluated whether the presence of adventitious lung sounds and the characteristics of normal lung sounds differ between spontaneous and standardized breathing in a general population.Ī cross-sectional study was conducted with 116 subjects (53.4% female, mean age 59.2 ± 11.6 y). ![]() For clinical practice and research, it would be easier to auscultate lung sounds without simultaneously measuring air flow.
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