Method for automatic detection of wheezing in lung sounds
Method for automatic detection of wheezing in lung sounds
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DOI：
10.1590/s0100-879x2009000700013
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发表时间：
2009-07-01
影响因子：
2.3
通讯作者：
Maia, J.M.
中科院分区：
文献类型：
--
作者：
Riella, R.J.;Nohama, P.;Maia, J.M.
本报告介绍了一种技术的发展，自动识别喘息的数字记录肺音。该方法基于从呼吸周期中提取和处理光谱信息，并将这些数据用于用户反馈和自动识别。首先对呼吸周期进行预处理，以使其频谱信息归一化，然后计算其频谱图。在此过程之后，频谱图图像通过二维卷积滤波器和半阈值处理，以分别增加对比度和分离其最高幅度分量。因此，为了生成更多的压缩数据以进行自动识别，计算来自经处理的谱图的谱投影并将其存储为阵列。然后定位阵列的较高幅度值及其相应的谱值，并将其用作多层感知器人工神经网络的输入，这导致关于喘息存在的自动指示。为了验证方法，使用了从三个不同的存储库记录的肺音。结果表明，所提出的技术实现了84.82%的准确性，在一个孤立的呼吸周期检测喘息和92.86%的准确性检测喘息时，进行检测，使用从同一个人获得的呼吸周期组。此外，该系统还提供了原始记录的声音和后处理的声谱图图像，供用户从数据中得出自己的结论。
The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. 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. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. 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. 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. 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. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.