Breathing sound intelligent diagnosis and treatment system and method based on deep learning

Abstract

The invention discloses a breathing sound intelligent diagnosis and treatment system and method based on deep learning. The system comprises breathing sound acquisition equipment, a user side upper computer and a cloud server, wherein the breathing sound acquisition equipment is used for acquiring a breathing sound signal of a user in real time, converting the sound into a digital signal and transmitting the digital signal to the upper computer; the user side upper computer is used for transmitting user data to the cloud server through a communication module; the cloud server is used for deploying the breathing sound intelligent diagnosis method based on deep learning, namely the cloud server receives breathing sound data uploaded by the upper computer and sends the breathing sound data into a data assembly line of a diagnosis party, so that possible abnormal symptoms are automatically identified according to the breathing sound data uploaded by the upper computer, and a diagnosis result is fed back to the user side upper computer. The method can be implemented based on the system. The system and the method have the advantages of simple principle, high automation degree, wide application range and the like.

Description

technical field [0001] The present invention mainly relates to the technical field of respiratory monitoring, in particular to a system and method for intelligent diagnosis and treatment of respiratory sounds based on deep learning. Background technique [0002] Respiratory diseases have become a hot issue in modern medicine. Based on disability-adjusted life-year calculations, the largest burden of disease in my country is respiratory diseases, followed by cardiovascular and cerebrovascular diseases. At present, my country's respiratory medical industry has the problems of large number of patients, lack of medical resources and uneven distribution. [0003] Breath sound signals contain rich physiological and pathological information. Clinically, different lung diseases can be diagnosed by detecting the corresponding abnormal sounds. The traditional doctor's auscultation is easily affected by external noise and the patient's heart sound, which puts forward high requiremen...

AI Technical Summary

Problems solved by technology

Up to now, breath sound recognition is still a relatively imperfect research field. The classification algorithm research in this field mainly focuses on conventional algorithms such as feed-forward neural network and support vector machine, and no new algorithms such as convolutional neural network have been introduced. plenty of room for improvement

Images