Development Of Multifunctional Cardiopulmonary Sound Detection Device

Heart-related diseases are major diseases that seriously threaten the health and safety of people around the world.Auscultation technology is one of the simplest and most direct effective methods for clinical diagnosis of heart disease.It has the advantage that ECG and ultrasound can't replace it.The stethoscope is a common diagnostic method for doctors because of its simple operation and low price.The biggest advantage of heart sound auscultation is that some heart sounds can be heard from the heart sounds before pathological changes occur.However,the traditional auscultation requires high requirements for the surrounding environment and the doctor's experience at the time of diagnosis,and it is unable to achieve the function of replay and comparison of patients' pathological signals,thus hindering the in-depth application of auscultation technology in medicine.At present,although many researchers have conducted research on digital auscultation technology,the technology is still not mature,and there is no integrated product in the market.Therefore,this paper proposes to developing a portable and versatile digital auscultation device.In this paper,based on the mechanism of heart sound signal generation and the heart activity process corresponding to heart sound signal,a multi-functional cardiopulmonary sound detection device and application system were developed,and the synchronous detection of ECG signals was realized at the same time.The main work includes building hardware platform,designing software and realizing the segmentation algorithm of heart sound signal.The hardware part is mainly for the selection of key components of the system and circuit design.In this paper,a piezoelectric thin film sensor with precise electrons is used to collect the heart sound signal.The detection of ECG signals is based on Analog front end of Texas Instruments,CPU is the STM32F103RCT6;software part mainly realizes the bottom driver software design and PC software design,the bottom driver software design mainly completes the driving of each hardware sub-module,signal sampling andpacket transmission and transmission;PC The software design realizes the functions of receiving,storing,playing back,recording and so on.The algorithm part mainly completes the filtering processing of the heart sound signal,segmenting the heart sound signal and calculating the characteristic parameters,and completing some abnormal heart sounds and normal.The classification of heart sounds;the correct detection rate of the starting and stopping points of S1 and S2 of normal heart sounds can reach 97.69%,and the correct detection rate of abnormal heart sounds is basically above 87.9%.In this paper,a total of clinical data of 100 cases were collected and their classifications were studied in depth.The designed software was used to analyze the heart sound signal in the time domain and the frequency domain,and the feature points of the heart sound signals were automatically and manually completed.This paper also combines the development of telemedicine in recent years,realizes the wireless data transmission function,and realizes the software management and analysis of the software to the patient.In addition,this paper completed the hardware system function test and system verification.After testing,the power supply voltage error of each module of the hardware system is less than 5%,the power consumption test error is less than 3%,and the test result meets the hardware design requirements.In addition,the heart sound signals of 30 normal subjects and patients with cardiovascular diseases were compared for a total of 120 cardiac cycles,it was found that there were significant differences in the duration of S1,S2,and ventricular diastolic phase between the two groups of normal heart sound signal abnormal heart sound signals.It provides a valid reference for the clinical diagnosis of heart disease.At the same time,at the end of the paper,the shortcomings and improvement directions of the system and the future prospects of automatic disease diagnosis for auscultation technology are pointed out.