{'fraction_non_alphanumeric': 0.048898071625344354, 'fraction_numerical': 0.028236914600550965, 'mean_word_length': 4.322344322344322, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Detection of bronchial breathing caused by pneumonia.

The classic auscultation with stethoscope is the established clinical method for the detection of lung diseases. The interpretation of the sounds depends on the experience of the investigating physician. Therefore, a new computer-based method has been developed to classify breath sounds from digital lung sound recordings. Lung sounds of 11 patients with one-sided pneumonia and bronchial breathing were recorded on both the pneumonia side and on contralateral healthy side simultaneously using two microphones. The spectral power for the 300-600 Hz frequency band was computed for four respiratory cycles and normalized. For each breath, the ratio R between the time-segments (duration = 0.1 s) with the highest inspiratory and highest expiratory flow was calculated and averaged. We found significant differences in R between the pneumonia side (R = 1.4 +/- 1.3) and the healthy side (R = 0.5 +/- 0.5; p = 0.003 Wilcoxon-test) of lung. In 218 healthy volunteers we found R = 0.3 +/- 0.2 as a reference-value. The differences of ratio R (delta R) between the pneumonia side and the healthy side (delta R = 1.0 +/- 0.9) were significantly higher compared to follow-up studies after recovery (delta R = 0.0 +/- 0.1, p = 0.005 Wilcoxon-test). The computer based detection of bronchial breathing can be considered useful as part of a quantitative monitoring of patients at risk to develop pneumonia.