Autoregressive spectral analysis of electroenterogram (EEnG) for basic electric rhythm identification

The aim of the present study is to identify the slow wave (SW) of the myoelectric activity of the small bowel (electroenterogram) recorded at the abdominal surface. For this purpose autoregressive spectral estimation (AR) was used. Internal and external recordings were acquired simultaneously from three Beagle dogs (in nine recording sessions). Three methods for obtaining the optimal order of AR model were applied to one-minute-length: abdominal myoelectric signal: Final prediction error (FPE), Akaike information criterion (AIC) and minimum description length (MDL). The optimal order was of 10, with a frequency resolution Δf= 0,025 Hz. The frequency of the maximum peaks of the signal spectrum can be found around 0,3 Hz. AR spectral analysis shows that the SW can be detected on the abdominal recordings of the small bowel myoelectrical activity without breathing interference.