Literature DB >> 29862758

[Computer-aided Diagnosis and New Electronic Stethoscope].

Mei Huang1, Hongying Liu1,2, Xitian Pi1,3, Yilu Ao1, Zi Wang1.   

Abstract

Auscultation is an important method in early-diagnosis of cardiovascular disease and respiratory system disease. This paper presents a computer-aided diagnosis of new electronic auscultation system. It has developed an electronic stethoscope based on condenser microphone and the relevant intelligent analysis software. It has implemented many functions that combined with Bluetooth, OLED, SD card storage technologies, such as real-time heart and lung sounds auscultation in three modes, recording and playback, auscultation volume control, wireless transmission. The intelligent analysis software based on PC computer utilizes C# programming language and adopts SQL Server as the background database. It has realized play and waveform display of the auscultation sound. By calculating the heart rate, extracting the characteristic parameters of T1, T2, T12, T11, it can analyze whether the heart sound is normal, and then generate diagnosis report. Finally the auscultation sound and diagnosis report can be sent to mailbox of other doctors, which can carry out remote diagnosis. The whole system has features of fully function, high portability, good user experience, and it is beneficial to promote the use of electronic stethoscope in the hospital, at the same time, the system can also be applied to auscultate teaching and other occasions.

Entities:  

Keywords:  computer-aided diagnosis; electronic stethoscope; intelligent analysis

Mesh:

Year:  2017        PMID: 29862758     DOI: 10.3969/j.issn.1671-7104.2017.03.002

Source DB:  PubMed          Journal:  Zhongguo Yi Liao Qi Xie Za Zhi        ISSN: 1671-7104


  2 in total

1.  Electronic Stethoscope Filtering Mimics the Perceived Sound Characteristics of Acoustic Stethoscope.

Authors:  Valerie Rennoll; Ian McLane; Dimitra Emmanouilidou; James West; Mounya Elhilali
Journal:  IEEE J Biomed Health Inform       Date:  2021-05-11       Impact factor: 5.772

2.  A Lung Sound Category Recognition Method Based on Wavelet Decomposition and BP Neural Network.

Authors:  Yan Shi; Yuqian Li; Maolin Cai; Xiaohua Douglas Zhang
Journal:  Int J Biol Sci       Date:  2019-01-01       Impact factor: 6.580

  2 in total

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