Electronic Academic Department (DAELN), Federal Institute of Santa Catarina (IFSC), Av. Mauro Ramos, 950, Florianopolis/SC, 88020-300, Brazil.
Electrical and Electronic Engineering Department (EEL), Federal University of Santa Catarina (UFSC), Campus Universitario Reitor João David Ferreira Lima, Rua Delfino Conti, s/n, Trindade, Florianopolis/SC, 88040-370, Brazil.
Comput Biol Med. 2018 Nov 1;102:21-29. doi: 10.1016/j.compbiomed.2018.09.007. Epub 2018 Sep 12.
Crackle is a lung sound widely employed by health staff to identify respiratory diseases. The two-cycle duration (2CD) is a quantitative index pointed out by the American Thoracic Society and the European Respiratory Society to classify respiratory crackles as fine or coarse. However, this index, measured in the time domain, is highly affected by noise and filters of recording systems. Such factors hamper the analysis of data reported by different research groups. This work proposes a new index based on the instantaneous frequency of crackles estimated by means of discrete-time pseudo Wigner-Ville distribution.
Comparisons between 2CD and the proposed index were carried out for simulated and actual crackles. Normal breathing sounds were added to simulated crackles; the resulting signals were then applied to a band-pass filter that mimics those belonging to lung sound acquisition systems. Thus, the impact of noise and filtering on these two indices was assessed for simulated crackles. Kruskal-Wallis and Dunn's tests as well as Gaussian mixture model (GMM) were applied to the two indices measured from 382 actual crackles belonging to open databases.
The proposed index is much less susceptible to waveform distortions due to noise and filtering when compared to the 2CD. Thus, the statistical analyses allow the identification of two classes of crackles from actual databases; the same does not occur when using 2CD.
The new proposed index has the potential to contribute for a better characterization of crackles generated by different respiratory diseases, assisting their diagnosis during clinical exams.
爆裂音是一种被卫生保健人员广泛用于识别呼吸疾病的肺部声音。双周期持续时间（2CD）是美国胸科学会和欧洲呼吸学会指出的一个定量指标，用于将呼吸爆裂音分类为细或粗。然而，这个在时域中测量的指标，受到噪声和记录系统滤波器的高度影响。这些因素阻碍了不同研究小组报告的数据的分析。这项工作提出了一种新的指标，该指标基于通过离散时间伪魏格纳-维尔分布估计的爆裂音的瞬时频率。
对模拟和实际爆裂音进行了 2CD 和所提出的指标之间的比较。正常呼吸声被添加到模拟爆裂音中；然后将得到的信号应用于带通滤波器，该滤波器模拟属于肺部声音采集系统的滤波器。因此，评估了噪声和滤波对模拟爆裂音这两个指标的影响。Kruskal-Wallis 和 Dunn 检验以及高斯混合模型（GMM）被应用于来自开放数据库的 382 个实际爆裂音的两个指标的测量。
与 2CD 相比，所提出的指标受噪声和滤波引起的波形失真的影响要小得多。因此，统计分析允许从实际数据库中识别出两种爆裂音类别；而使用 2CD 则不会发生这种情况。
新提出的指标有可能有助于更好地描述不同呼吸疾病产生的爆裂音，在临床检查中协助对其进行诊断。
