摘要
针对监护对象状态难判定问题,对小波分析和神经网络相结合的方法判定、预测监护对象所处状态进行了研究,并实现自动报警,以便医护人员做出更准确的诊断决策。采用串联方法将两者相结合,用小波分析对用户的多生理参数进行预处理并提取特征值,然后将处理后的信号作为神经网络的输入向量,状态信息作为输出,实现监护对象状态判定及预测。
According to the disadvantage of use＇status decision in health monitoring system,the method of wavelet and BP neural network is put forward.Physiological parameter features are extracted using wavelet analysis which can be the inputs vector of BP neural networks,and the classification is trained and carried out by using BP neural network,so that physician can make decision more accurately.
出处
《机械设计与制造》
北大核心
2011年第3期75-77,共3页
Machinery Design & Manufacture
基金
粤港关键领域重点突破项目(20054982304)
广东省科技攻关项目(2004B10201010)
关键词
小波分析
神经网络
监护系统
状态判定
Wavelet analysis
Neural network
Monitoring system
Status decision
