{"title":"基于圆形麦克风阵列的人体声音径向滤波听诊器","authors":"Mudasir Ahmad Sheikh, L. Kumar, M. Beg","doi":"10.1109/ICPECA47973.2019.8975663","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of extraction of body sounds with a stethoscope having a single mechanical, less acoustic diaphragm by introducing a highly acoustic circular microphone array. This circular microphone array due to its exclusive advantages like signal enhancement, beamforming and steenng property, is capable of receiving sound signals from a desired direction and attenuates all other signals from other directions. In this paper, heart and lung are assumed as point sources, with a point on the sternum and just above its apex as a reference point to define the sphencal coordinates (r, $\\theta,\\ \\phi$) of heait and lung sound.This paper uses Multiple Signal Classification (MUSIC) algorithm for Direction of Arrival (DOA) estimation of heart and lung sound sources. For radial filtenng or extraction of desired sound (say heart sound) from a mixed signal of heart and lung sound, an adaptive beamformer, like Linearly Constrained Mimmum Variance (LCMV) beamformer is adopted. Real-time data is received by Umform Circular Array (UCA) and then recorded by an adobe audition software in a noise-free enviromnent. Results are simulated by Matlab. Though the results are obtained for heart and lung sound, but it can be extended to extract all other body sounds like bowel sounds, fetus sound etc. and hence leads to develop a universal body sound analyzer.","PeriodicalId":6761,"journal":{"name":"2019 International Conference on Power Electronics, Control and Automation (ICPECA)","volume":"43 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Circular Microphone Array Based Stethoscope for Radial Filtering of Body Sounds\",\"authors\":\"Mudasir Ahmad Sheikh, L. Kumar, M. Beg\",\"doi\":\"10.1109/ICPECA47973.2019.8975663\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses the problem of extraction of body sounds with a stethoscope having a single mechanical, less acoustic diaphragm by introducing a highly acoustic circular microphone array. This circular microphone array due to its exclusive advantages like signal enhancement, beamforming and steenng property, is capable of receiving sound signals from a desired direction and attenuates all other signals from other directions. In this paper, heart and lung are assumed as point sources, with a point on the sternum and just above its apex as a reference point to define the sphencal coordinates (r, $\\\\theta,\\\\ \\\\phi$) of heait and lung sound.This paper uses Multiple Signal Classification (MUSIC) algorithm for Direction of Arrival (DOA) estimation of heart and lung sound sources. For radial filtenng or extraction of desired sound (say heart sound) from a mixed signal of heart and lung sound, an adaptive beamformer, like Linearly Constrained Mimmum Variance (LCMV) beamformer is adopted. Real-time data is received by Umform Circular Array (UCA) and then recorded by an adobe audition software in a noise-free enviromnent. Results are simulated by Matlab. Though the results are obtained for heart and lung sound, but it can be extended to extract all other body sounds like bowel sounds, fetus sound etc. and hence leads to develop a universal body sound analyzer.\",\"PeriodicalId\":6761,\"journal\":{\"name\":\"2019 International Conference on Power Electronics, Control and Automation (ICPECA)\",\"volume\":\"43 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Power Electronics, Control and Automation (ICPECA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPECA47973.2019.8975663\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Power Electronics, Control and Automation (ICPECA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPECA47973.2019.8975663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Circular Microphone Array Based Stethoscope for Radial Filtering of Body Sounds
This paper addresses the problem of extraction of body sounds with a stethoscope having a single mechanical, less acoustic diaphragm by introducing a highly acoustic circular microphone array. This circular microphone array due to its exclusive advantages like signal enhancement, beamforming and steenng property, is capable of receiving sound signals from a desired direction and attenuates all other signals from other directions. In this paper, heart and lung are assumed as point sources, with a point on the sternum and just above its apex as a reference point to define the sphencal coordinates (r, $\theta,\ \phi$) of heait and lung sound.This paper uses Multiple Signal Classification (MUSIC) algorithm for Direction of Arrival (DOA) estimation of heart and lung sound sources. For radial filtenng or extraction of desired sound (say heart sound) from a mixed signal of heart and lung sound, an adaptive beamformer, like Linearly Constrained Mimmum Variance (LCMV) beamformer is adopted. Real-time data is received by Umform Circular Array (UCA) and then recorded by an adobe audition software in a noise-free enviromnent. Results are simulated by Matlab. Though the results are obtained for heart and lung sound, but it can be extended to extract all other body sounds like bowel sounds, fetus sound etc. and hence leads to develop a universal body sound analyzer.