帕金森病人苍白球神经元放电的自适应阈值检测

Adaptive Threshold Detecting Neural Spikes of the Globus Pallidus for Parkinson's Patients

自动选取合适的阈值以适应不同信噪比的信号,达到检测神经元放电的目的。依据微电极记录的信号,采用闭环方式自动递归调整阈值,逐次检测神经元放电。对合成的模拟神经放电信号及临床手术中微电极记录的112个病人的神经元放电信号处理,检测出了不同信噪比信号中的神经元放电脉冲,这些放电脉冲反映了神经核团的电生理特征。根据检测的神经元放电,可以对不同神经核团放电特征进行客观定量的分析,准确识别手术中微电极所在的神经核团,对于指导靶点定位具有重要的意义。

To select exact threshold automatically for accurate spikes detection under various signal to noise ratio（SNR） conditions.Based on the neuron discharge signals recorded by microelectrodes,close loop adaptive threshold algorithm was used to regulate the threshold for automatic spike detection,and neural spikes were detected gradually.The results showed that spikes were detected effectively in both simulated data according to actual extracellular recordings and clinic data under various SNR levels.These neural spikes reflect nucleus physiological characteristic.Based on spike detection,the discharge characteristic of different neurons could be analyzed objectively and quantitatively,thus the nucleus could be identified exactly.The proposed method is of great importance for targets localization during surgery.