@inproceedings{d72a00dee5364d5984a19a686a2694e0,
title = "Live Demo: LungSys-Automatic Digital Stethoscope System for Adventitious Respiratory Sound Detection",
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.",
author = "Yi Ma and Xinzi Xu and Qing Yu and Yuhang Zhang and Yongfu Li and Jian Zhao and Guoxing Wang",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Biomedical Circuits and Systems Conference, BioCAS 2019 ; Conference date: 17-10-2019 Through 19-10-2019",
year = "2019",
month = oct,
doi = "10.1109/BIOCAS.2019.8918752",
language = "英语",
series = "BioCAS 2019 - Biomedical Circuits and Systems Conference, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "BioCAS 2019 - Biomedical Circuits and Systems Conference, Proceedings",
address = "美国",
}