【摘要】 诱发电位 (EP)信号的检测与分析技术是临床医学诊断神经系统损伤及病变的一种重要手段。本研究提出一种预处理EP潜伏期变化动态检测方法 ,即利用独立分量分析方法 (ICA)对含有α稳定分布噪声的EP信号做预处理 ,再利用DLMS、DLMP算法动态检测EP潜伏期变化 ,形成了p -DLMS和p -DLMP算法。仿真结果及实验数据分析表明 ,p -DLMS和p -DLMP收敛速度分别高于DLMS和DLMP算法 ;在混合信噪比较低的情况下 ,p -DLMS和p -DLMP算法可以自适应地检测出潜伏期变化 ,且比DLMS和DLMP算法具有较好的估计精度和收敛速度 ;对不同的α的值 (0 <α 2 ) ,p -DLMS算法和p -DLMP算法性能基本不变。更多还原

【Abstract】 The detection and analysis of evoked potentials (EPs) is an important means in clinical diagnosis for the injury and disease of central nervous system. This paper proposed a method of preprocessing the EP signals contaminated by α stable noises with Infomax and comparing the latency change detection results between the normal DLMS, DLMP and the Infomax preprocess based methods (p-DLMS,p-DLMP). It is clear from computer simulations that p-DLMS and p-DLMP algorithms detect the latency changes more effectively and accurately than DLMS and DLMP,even when the mixed SNR is as low as -20dB. Further more, the performance of p-DLMS and p-DLMP algorithms are unchanged with different α(0<α≤2) values.更多还原