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间质性肺炎患者肺音的小波分析
引用本文:何庆华,洪新,毕玉田,龙露.间质性肺炎患者肺音的小波分析[J].中国医学物理学杂志,2014(3):4924-4928.
作者姓名:何庆华  洪新  毕玉田  龙露
作者单位:[1]第三军医大学大坪医院野战外科研究所创伤烧伤复合伤国家重点实验室,重庆400042 [2]英国剑桥大学医学系呼吸疾病研究组,英国剑桥
基金项目:重庆市科委国际科技合作项目cstc2012gg-gjhz0023
摘    要:目的:探索一种间质性肺炎患者肺音的的定量化评估分析方法。方法:采集第三军医大学第三附属医院呼吸科2名间质性肺炎患者的肺音,对肺音信号进行小波分析,首先进行归一化处理,然后采用db3小波进行6尺度小波分解,计算肺音小波分解各分量的能量。结果:间质性肺炎患者的爆烈音主要集中在小波分解的D3,D4和D5分量中。患者A治疗前肺音及治疗半年后的D3、D4和D5的能量和的平均值分别为0.25和0.057。患者B是在同一时期记录不同部位的肺音,患者的右上背与右下背记录的肺音D3+D4+D5的能量和均值分别为0.085和0.128,右下肺较右上肺的病情更严重。结论:肺音属于非平稳的随机信号,在时域和频域都有特征信息,适合采用小波时频分析方法来进行信号处理。肺音小波分量D3,D4和D5的能量和可以在一定程度反映爆烈音的多少,从而反映间质性肺炎患者的病情严重程度的不同。肺音检测安全,方法简单,成本低,便于重复检测,适合于监测间质性肺炎患者的病情程度。

关 键 词:肺音  间质性肺炎  小波

Wavelet Analysis of the Lung Sounds of Interstitial Pneumonia Patients
HE Qing-hua,HONG Xin,BI Yu-tian,LONG Lu.Wavelet Analysis of the Lung Sounds of Interstitial Pneumonia Patients[J].Chinese Journal of Medical Physics,2014(3):4924-4928.
Authors:HE Qing-hua  HONG Xin  BI Yu-tian  LONG Lu
Institution:1 .State Key Laboratory of Trauma, Bums and Combined Injury, Daping Hospital, Surgery Institute of the Third Mil- itary Medical University, Chongqing 400042, China; 2.Respiratory Medicine, University of Cambridge, Cambridge CB2 2QQ, United Kingdom)
Abstract:Objective: To establish a quantitative analysis method of lung sound in interstitial pneumonia patients. Methods: The data of lung sounds were collected from two interstitial pneumonia patients in Respiratory Deaprtment of Daping Hospital, the Third Military Medical University. The lung sound data was processed by wavelet analysis. After normalization, the lung sound signals were decomposed into 6 scales using db3 wavelet, and then the energy of each wavelet decomposition component was computed. Results: The crackle of interstitial pneumonia patients mainly distribute in D3, D4 and D5 wavelet component. The average energy of D3, 94 and D5 of patient A's lung sounds before treatment and at the end of a half-year's treatment was 0.25 and 0.057 respectively. The average energy of D3, 134 and D5 of patient B' s lung sounds recorded on the upper right back and the lower right back was 0.085 and 0.128 respectively. Patient B's lower right lung was worse than his upper right lung. Conclu- sions: Lung sounds are non-stationary random signals which have characteristics in both time and frequency domain, which are suitable for signal processing using wavelet time frequency analysis method. The energy of D3, 94 and D~ of interstitial pneumo- nia patient's lung sounds could reflect the strength of crackle in certain degrees, and the latter was a marker of the severity of the disease. Detection of lung sounds is a safe, simple, cheap and highly reproducible method, and may be suitable for monitor- ing the severity of interstitial pneumonia.
Keywords:lung sound  interstitial pneumonia  wavelet
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