呼吸声分类技术研究及检测系统设计  

Research on respiratory sound classification technology and detection system design

作　　者：张书文 侯猛 刘泽华 张锦龙[1] ZHANG Shuwen;HOU Meng;LIU Zehua;ZHANG Jinlong(School of Physics and Electronics,Henan University,Kaifeng 475001,China)

机构地区：[1]河南大学物理与电子学院,开封475001

出　　处：《应用声学》2023年第3期659-666,共8页Journal of Applied Acoustics

基　　金：国家自然科学基金面上项目(61675063,61975052);河南大学一流学科培育项目(2019YLZD06);河南省科技攻关项目(162102210021)。

摘　　要：患有呼吸疾病的病人由于呼吸道腺体不受意识控制、异物或者其本身肺部病变等原因会出现呼吸异常。医护人员通过病人的呼吸状况可以找寻和分析病人出现呼吸异常的原因。以往呼吸声的诊断方式是专业的医护人员通过使用听诊器对病人进行肺部听诊,但听诊的结果取决于医护人员的经验与相关参数。在初级诊断治疗阶段,初级医生识别听诊声的准确率很低,一般从20%80%不等,因此会存在10%20%的高误诊率(漏诊、错诊和延误)。该文提出了一种利用聚偏二氟乙烯(PVDF)薄膜传感器提取语声特征的检测系统,该检测系统根据病人发出声音的不同,提取呼吸声特征值判断病人的呼吸状况。通过PVDF传感器采集的微弱呼吸声经过K最邻近分类之后的二分类平均识别率可达96.56%,种类较多的四分类平均识别率为89.84%。综上表明,相比于传统听诊方式通过PVDF传感器采集识别的结果其具有更高的准确性和可靠性,其判断呼吸状况的结果可以为医护人员提供参考,更好地监测病人的呼吸状况。Patients with respiratory diseases may experience breathing abnormalities due to unconsciousness of respiratory glands,foreign matter or their own lung lesions.Medical staff can find and analyze the causes of the patient’s abnormal breathing through the patient’s respiratory condition.In the past,the diagnosis method of respiratory sound was that professional medical staff auscultated the patient’s lungs by using stethoscope.However,the result of auscultation depends on the experience and relevant parameters.In the primary diagnosis and treatment stage,the accuracy of primary doctors in identifying auscultation sounds is very low,generally ranging from 20%to 80%.Therefore,there will be a high misdiagnosis rate of 10%to 20%(missed diagnosis,wrong diagnosis and delay diagnosis).In this paper,a detection system using polyvinylidene difluoride(PVDF)thin film sensor to extract speech features is proposed.According to the different sounds of patients,the eigenvalues of sounds are extracted to judge the respiratory status of patients.After K-nearest neighbor classification,the average recognition rate of the two classification of the weak respiratory sounds collected by by PVDF sensor can reach 96.56%,and the average recognition rate of the four classification with more species is 89.84%.In conclusion,compared with the traditional auscultation method,the results collected and identified by PVDF sensor have higher accuracy and reliability.The results of its judgment of respiratory status can provide reference for medical staff and it can better monitor respiratory status of patients.

关 键 词：呼吸异常 薄膜传感器 声音特征 呼吸状态 

分 类 号：TN911.71[电子电信—通信与信息系统]