An electronic auscultation system with intelligent array sensors

Abstract

The invention discloses an intelligent array sensor electronic auscultation system, including a sound collection and signal processing system distributed by array sensors for collecting heart and lung sounds; Heart and lung sound intelligent detection system with cloud" server function; and remote cloud server system with deep learning model training and big data computing capabilities. The present invention can synchronously collect heart and lung sounds from various parts of the body; has the function of active noise reduction, and the signal quality is higher than that of traditional electronic stethoscopes; the auscultation head with a resonant cavity structure is used to pick up sound, so that the auscultation effect can be optimized and the signal of heart and lung sounds can be improved. The noise ratio is improved; the sound source positioning algorithm is used to realize the real-time display of the three-dimensional cardiopulmonary status; the "artificial intelligence + big data" method is adopted, so that as the number of people using the system increases and the number of samples collected increases, the self-learning function of the system model will increase. Make the cardiopulmonary state classification model more and more accurate.

Description

technical field [0001] The invention belongs to the fields of smart medical treatment and mobile health equipment, and in particular relates to an intelligent electronic auscultation system with an intelligent array sensor. Background technique [0002] The "New Coronary Pneumonia" that broke out in early 2020 has posed a huge threat to the health of the people and has also had a huge impact on the development of the national economy. If patients can stay at home, they can make a preliminary judgment on their physical health (especially cardiopulmonary function) through smart auscultation equipment at the early stage of illness, and doctors can review and confirm the judgment results of smart auscultation equipment in a contactless and remote manner. , to assess the patient's physical condition, so as to carry out targeted treatment. In this way, the waste of medical resources will be greatly avoided, and the risk of cross-infection caused by patients traveling, visiting ho...

AI Technical Summary

Problems solved by technology

[0005] For the following defects of the traditional stethoscope: 1) It is complicated to use, requires professionals to operate, and requires multiple points for time-sharing and repeated measurements; 2) It is greatly affected by external environmental noise, and it is difficult to hear weak cardiopulmonary murmurs; 3) Traditional stethoscopes The resonant chamber of the stethoscope is designed to meet the sensitivity of the human cochlea, not the sensitivity of the microphone, which distorts the collected heart and lung sounds; 4) The judgment of the auscultation result depends on the doctor's auscultation experience, which often leads to misdiagnosis and missed diagnosis; 5 ) cannot be used remotely, and doctors and patients need direct contact, which is prone to cross-infection of viruses; 6) It is impossible to intuitively see the position of heart and lung sounds in a three-dimensional graphical manner; 7) It is impossible to remotely store auscultation information, and there is no effective The diagnosis and treatment information management method applied to smart medical treatment. The present invention proposes an intelligent electronic auscultation system with intelligent array sensors, which specifically includes three subsystems: a sound collection and signal processing system distributed by array sensors for collecting patient heart and lung sounds ;As a system control center, it has artificial intelligence pattern recognition, heart and lung sounds Figure three Cardiopulmonary sound intelligent detection system with three-dimensional graphical display and linking remote "cloud" server functions; and remote "cloud" server system with deep learning model training and big data computing capabilities

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