Spike detection in human muscle sympathetic nerve activity using a matched wavelet approach
Spike detection in human muscle sympathetic nerve activity using a matched wavelet approach
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DOI：
10.1016/j.jneumeth.2010.08.035
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发表时间：
2010-11-30
影响因子：
3
通讯作者：
Shoemaker, J. Kevin
中科院分区：
文献类型：
--
作者：
Salmanpour, Aryan;Brown, Lyndon J.;Shoemaker, J. Kevin
与血压调节相关的交感神经记录可以直接使用微神经造影记录。该信号的一般特征是在相当大的高斯噪声背景下，由静默期分离的尖峰（动作电位）的自发爆发活动。在电极测量期间，原始肌肉交感神经活动（MSNA）信号被放大、带通滤波、整流和集成，该集成过程去除信息本文提出了一种从原始MSNA信号中检测动作电位的新方法，以研究神经节后神经放电特性。该方法基于母小波的设计，母小波与从真实原始MSNA信号中提取的实际平均动作电位模板相匹配，利用连续小波变换将新的匹配小波应用于MSNA信号中检测动作电位使用(1)从7名健康参与者记录的真实MSNA和(2)模拟MSNA对所提出的方法与之前两种基于小波的方法的性能进行了评估。结果表明，新的匹配小波比之前使用非匹配小波检测MSNA信号中的动作电位的基于小波的方法表现得更好(C) 2010 Elsevier BV版权所有
Sympathetic nerve recordings associated with blood pressure regulation can be recorded directly using microneurography A general characteristic of this signal is spontaneous burst activity of spikes (action potentials) separated by silent periods against a background of considerable Gaussian noise During measurement with electrodes the raw muscle sympathetic nerve activity (MSNA) signal is amplified band-pass filtered rectified and integrated This integration process removes information regarding action potential content and their discharge properties This paper proposes a new method for detecting action potentials from the raw MSNA signal to enable investigation of post-ganglionic neural discharge propertiesThe new method is based on the design of a mother wavelet that is matched to an actual mean action potential template extracted from a real raw MSNA signal To detect action potentials the new matched wavelet is applied to the MSNA signal using a continuous wavelet transform following a thresholding procedure and finding of a local maxima that indicates the location of action potentials The performance of the proposed method versus two previous wavelet-based approaches was evaluated using (1) real MSNA recorded from seven healthy participants and (2) simulated MSNA The results show that the new matched wavelet performs better than the previous wavelet-based methods that use a non-matched wavelet in detecting action potentials in the MSNA signal (C) 2010 Elsevier B V All rights reserved