Detection of single action potential in multi-unit postganglionic sympathetic nerve recordings in humans: A matched wavelet approach

Sympathetic nerve activity associated with blood pressure regulation can be recorded directly using microneurography. Action potentials (APs) in the sympathetic nerve signal are dominated by colored gaussian noise. This paper proposes a novel method for detecting APs from muscle sympathetic nerve activity (MSNA) in multi-unit postganglionic recordings. The new method is based on designing a new mother wavelet matched to an actual AP template extracted from a real raw MSNA signal. To detect action potentials, the new matched wavelet was applied to the MSNA signal using a continuous wavelet transform following a thresholding procedure and detecting local maxima to estimate AP arrival times. The performance of the proposed method was evaluated using real MSNA recorded from six healthy participants and compared with two previous wavelet-based methods using a simulated MSNA signal.