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The Identification of Sputum Situation Based on the Sound from the Respiratory Tract

机译:基于呼吸道声音的痰液状况识别

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摘要

In ICU (Intensive Care Unit), the trachea of patients with ventilator should be supervised all time to avoid the sputum depositing. The sputum situation identification by using traditional lung auscultation is time-consuming and related skill is difficult to acquire. Therefore it needs the medical staff to have a good training and experience. In this paper, an automatic sputum situation detection method is proposed. A system which is used to acquire respiratory sound was also developed. 46 features were extracted from the respiratory sounds based upon Empirical Mode Decomposition (EMD). And then Random Forest classifier is used as the classifier for recognition of sputum situation. In the experiment, 803 respiratory sound samples were collected from 14 patients, with each sample corresponding to one respiratory cycles. The classification results shows that this algorithm can achieve the accuracy of 92.02%.
机译:在ICU(加护病房)中,应始终对呼吸机患者的气管进行监督,以免痰液沉积。使用传统的肺部听诊进行痰液状况识别很费时,并且相关技能难以掌握。因此,需要医务人员进行良好的培训和经验。本文提出了一种自动的痰液状况检测方法。还开发了用于获取呼吸声的系统。基于经验模式分解(EMD)从呼吸声中提取了46个特征。然后使用随机森林分类器作为识别痰液情况的分类器。在该实验中,从14位患者中收集了803个呼吸音样本,每个样本对应一个呼吸周期。分类结果表明,该算法可以达到92.02%的精度。

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