Yi Ma, Xinzi Xu, Qing Yu, Yuhang Zhang, Yongfu Li, Jian Zhao, Guoxing Wang
{"title":"Live Demo: LungSys - Automatic Digital Stethoscope System For Adventitious Respiratory Sound Detection","authors":"Yi Ma, Xinzi Xu, Qing Yu, Yuhang Zhang, Yongfu Li, Jian Zhao, Guoxing Wang","doi":"10.1109/BIOCAS.2019.8918752","DOIUrl":null,"url":null,"abstract":"We demonstrate a new digital stethoscope system, LungSys, for our users to detect adventitious respiratory sounds automatically. LungSys includes a commercial digital stethoscope and a software application installed on an Android mobile tablet. The digital stethoscope converts an acoustic sound from the users’ chest to electronic signals and transmits the signals to a mobile tablet through a built-in Bluetooth device. Our custom software application in the tablet provides a real-time analysis of the lung sound using our proposed neural network model bi-ResNet(BRN) and identifies any adventitious respiratory sound to users. Since LungSys is based on a non-invasive digital stethoscope and our proprietary deep learning algorithm, it allows users who do not have any professional skill to perform respiratory diagnosis conveniently.","PeriodicalId":222264,"journal":{"name":"2019 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Biomedical Circuits and Systems Conference (BioCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIOCAS.2019.8918752","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
We demonstrate a new digital stethoscope system, LungSys, for our users to detect adventitious respiratory sounds automatically. LungSys includes a commercial digital stethoscope and a software application installed on an Android mobile tablet. The digital stethoscope converts an acoustic sound from the users’ chest to electronic signals and transmits the signals to a mobile tablet through a built-in Bluetooth device. Our custom software application in the tablet provides a real-time analysis of the lung sound using our proposed neural network model bi-ResNet(BRN) and identifies any adventitious respiratory sound to users. Since LungSys is based on a non-invasive digital stethoscope and our proprietary deep learning algorithm, it allows users who do not have any professional skill to perform respiratory diagnosis conveniently.