摘要
为实现对心血管疾病的预警,及早发现以心率、心肺音恶性变化为代表的危险前兆,设计基于CNN-LSTM神经网络的声纹识别系统。利用物联网技术融合心率传感芯片、单片机、电子听诊器等设备,对心率进行实时监测、辅助预警;根据梅尔道普频率系数对心肺音信号进行特征提取,构建基于CNN-LSTM算法的心肺音智能识别模型,对部分心肺音进行智能检测诊断,实验结果显示损失值为0.082,准确率达0.908。开拓了人工智能技术在心血管疾病预警方面的应用空间,前瞻性强、结构框架完整,可有效避免医疗资源浪费,前置对心血管疾病的应对措施,市场应用前景广阔,对于推动智慧医疗有重大作用。
For warning of cardiovascular disease,in order to early detect the change of heart and lung voice representing the signs of danger,the vocieprint recognition system based on CNN-LSTM is designed.Using the Internet of Things technology coalescing the heart rate sensor chip,single-chip computer,electronic stethoscope,such as equipments,it can monitor the heart rate in real-time,early warn.And the cardiopulmonary sound recognition model based on the CNN-LSTM algorithm is trained,results show that the loss value is 0.082,accuracy rate of 0.908.The system is forward-looking and has a complete structural framework,which can effectively avoid the waste of medical resources,preposite the countermeasures for cardiovascular diseases.It has a broad application prospect in the market,and plays a significant role in promoting smart medical treatment.
作者
牟俊杰
姚刚
孙涛
Mu Junjie;Yao Gang;Sun Tao(Coastal Defense College,Naval Aviation University,Yantai 264001,China)
出处
《电子技术应用》
2021年第3期75-78,共4页
Application of Electronic Technique
