脑电信号数据压缩及棘波识别的小波神经网络方法  

A Wavelet Neural Network Algorithm of EEG Signals Data Compression and Spikes Recognition

作　　者：张永胜[1] 刘爱萍 郁可[3] 

机构地区：[1]武汉工业大学计算机科学系,武汉430070 [2]洛阳工业高专计算机系,洛阳471003 [3]武汉工业大学光纤中心,武汉430070

出　　处：《生物医学工程学杂志》1999年第2期172-176,共5页Journal of Biomedical Engineering

摘　　要：在对小波神经网络及其算法研究的基础上，提出了一种对脑电信号压缩表达和痫样脑电棘波识别的新方法。实验结果显示，小波网络在大量压缩数据的同时，能够较好的恢复原有信号。另外，在脑电信号的时频谱等高线图上，得到了易于自动识别的棘波和棘慢复合波特征，说明此方法在电生理信号处理和时频分析方面有着光明的应用前景。A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike slow rhythm are auto detected from the time frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time frequency analyzing.

关 键 词：脑电图 小波神经网络 数据压缩 癫痫 棘波识别 

分 类 号：R741.044[医药卫生—神经病学与精神病学] R742.104[医药卫生—临床医学]