中圖分類號: TP399 文獻(xiàn)標(biāo)識碼: A DOI:10.16157/j.issn.0258-7998.200960 中文引用格式: 牟俊杰,,姚剛,孫濤. 基于CNN-LSTM神經(jīng)網(wǎng)絡(luò)的聲紋識別系統(tǒng)設(shè)計(jì)[J].電子技術(shù)應(yīng)用,,2021,,47(3):75-78. 英文引用格式: Mu Junjie,Yao Gang,,Sun Tao. Design of vocieprint recognition system based on CNN-LSTM neural network[J]. Application of Electronic Technique,,2021,,47(3):75-78.
Design of vocieprint recognition system based on CNN-LSTM neural network
Abstract: 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.
Key words : CNN,;LSTM;features extraction,;MFCC,;cardiovascular disease;vocieprint recognition
在人口老齡化日益嚴(yán)重的當(dāng)下,,心血管疾病不斷威脅老年人健康,,引發(fā)社會(huì)廣泛關(guān)注。由于醫(yī)療知識欠缺,、行動(dòng)不便等原因,,部分老年人就醫(yī)不及時(shí),錯(cuò)過了搶救的黃金時(shí)間,,留下永遠(yuǎn)的遺憾,。開發(fā)心血管疾病方面的智能預(yù)警系統(tǒng),滿足龐大的老年人群體需求迫在眉睫[3],。在醫(yī)療實(shí)踐中,,對心血管疾病的診斷常常以心率、心肺音數(shù)據(jù)為重要支撐,,國內(nèi)外以DSP[4],、長短時(shí)記憶(Long Short Time Memory,LSTM)[5],、卷積神經(jīng)網(wǎng)絡(luò)[6](Convolutional Neural Network,,CNN)等方法算法為手段對心血管疾病的信號診斷進(jìn)行了相當(dāng)多的分析,但基本均停留在理論層面,,距離軟硬件結(jié)合的實(shí)際應(yīng)用尚有差距,。各種醫(yī)療設(shè)備的聚焦點(diǎn)主要是信號的準(zhǔn)確采集、分離[7-8],,基于醫(yī)療倫理等原因,,對智能診斷設(shè)備的研制尚處于知識儲(chǔ)備期,,有巨大的空白亟需填補(bǔ)。本文設(shè)計(jì)了基于CNN-LSTM的心血管疾病預(yù)警系統(tǒng),,利用物聯(lián)網(wǎng)技術(shù)采集心率和心肺音等健康指標(biāo)數(shù)據(jù),,對老人的健康狀況進(jìn)行實(shí)時(shí)監(jiān)測、預(yù)警,,采用基于CNN-LSTM模型的智能算法對心肺音信號進(jìn)行智能分析預(yù)警,。系統(tǒng)著重考慮了適用性、穩(wěn)定性和成本,,具有較高的實(shí)用價(jià)值和完整的結(jié)構(gòu)框架,,是利用智慧醫(yī)療從應(yīng)用層面解決心血管疾病問題的一次重要探索。