一种提取动作电位的自适应阈值算法

Adaptive Threshold Method for Spike Detection

阈值检测法是目前最广泛的动作电位提取的方法之一,自适应阈值算法比定阈值算法更为灵活,更能准确有效地检测出动作电位信号。该文设计了自适应阈值检测算法,它比目前自动设定阈值的方法计算量小,更容易实现,能够根据接收到的神经信号的数据,不断地计算﹑调整阈值,同时根据此阈值准确、实时地提取动作电位信号。该文把此种算法进行了Matlab仿真和FPGA电路实现。实验证明,该文中的自适应阈值法,方法简单、易于在电路上进行实现,能够灵活地调整阈值。同时,对神经信号发生器产生的动作电位信号,此算法把100%的动作电位和极少部分噪声截取出来,滤除了绝大部分的噪声信号。

Threshold method was currently one of the most widely spike detection methods. The adaptive threshold method was more flexible and more accurate than fixed threshold method. Therefore,this paper designs an adaptive threshold method which can be implemented more easily. It need much less computational complexity than traditional adaptive threshold method. It can continuously calculate the threshold by the received neuronal data. Then we can simultaneously detect spikes according to the threshold Value. At the same time,the method was tested by the MAT- LAB simulation and FPGA circuit. Experiments results show that,the adaptive threshold method can automatically ad- just the threshold by the neural signal data. Meanwhile,this method was very simple and it can be implemented easily. The method can detect 100% spikes and minimal noise from signals that a neural signal generator produces. It filters most noise signals.