Performance analysis of stationary and discrete wavelet transform for action potential detection from sympathetic nerve recordings in humans

Accurate investigation of the sympathetic nervous system is important in the diagnosis and study of various autonomic and cardiovascular control and disorders. Sympathetic function associated with blood pressure regulation in humans can be evaluated by recording muscle sympathetic nerve activity (MSNA), which is characterised by synchronous neuronal discharges separated by periods of neural silence dominated by colored gaussian noise. In this paper two common methods for detecting filtered action potential in MSNA recordings is compared. These methods are based on stationary wavelet transform (SWT) and discrete wavelet transform (DWT). The performance analysis are evaluated using simulated MSNA using templates extracted from real MSNA recorded from three healthy subjects.