Adaptive Spectrogram for Surface EEnG Analysis

Electroenterogram (EEnG) is the myoelectrical signal of the small bowel. It is the result of a permanent slow wave (low frequency component) and series of spike bursts (high frequency component) that are only present when a bowel contraction occurs. This means spectral content of EEnG changes throughout time. The definition of a t-f distribution that adapts to changes in EEnG spectrum could be very helpful to study this signal. Nine recording sessions of surface EEnG were carried out in three Beagle dogs in fast state. It was proposed an algorithm that selects the window length of spectrogram depending on the maximum frequency of interest of signal in previous window. The proposed adaptive spectrogram was applied to surface EEnG. When only slow waves are present, the adaptive spectrogram enlarges window length in order to present good frequency resolution to characterize the low frequency component of the EEnG. When spike bursts appear, windows of analysis are shorter reducing time resolution to identify individual units of slow waves accompanied by SB. The proposed adaptive spectrogram can be a helpful tool to identify surface EEnG activity in time and frequency domain. It is also likely to be adapted to study other multicomponent signals