ABSTRACT

The digestive system allows the transformation of food in nutrients and provides the calories and the fundamental elements for life to the organism. Moreover, it is responsible for the disposal of waste products in an appropriate manner. In this context, the intestinal motility is very important for the segmentation of the chyme and intestinal transit and it is determined by the myoelectrical activity of the intestinal muscular layers; such activity is also called electroenterogram (EEnG). The myoelectrical signal is the result of a low frequency component that is always present in physiological conditions slow wave (SW) or rhythm electrical basic (BER) and a high frequency component called spike bursts which is associated with intestinal contractions. The analysis of the EEnG is a key step to monitor the intestinal activity. The study of intestinal slow wave not only provides information about the basic rhythm of bowel contractions, but also may help to diagnose some gastrointestinal pathologies. In order to approach this tool to clinical applications, the recording of EEnG signal should be non invasive.
The aim of this Ph.D Thesis is to detect the intestinal pacemaker activity and characterize the basic electric rhythm on external EEnG, comparing and studying their relationship with the internal EEnG.
The analyzed signals were obtained simultaneously on abdominal surface and on intestinal serosa from Beagle dogs in fast state. Autoregressive (AR), autoregressive moving average (ARMA), Prony and multiple signal classification (MUSIC) estimation was used to determinate the power spectral distributions which is associated with slow wave activity of both internal and external records. On the other hand, to study the relationship between the spectrum of the signal recorded on the abdominal surface and internal signals, the coherence functions were estimated using ARM and MUSIC models.
We studied the optimal order for each parametric estimators. However, this order changes for differents signal segment, subjects and channels. It was set an appropriate order for every spectral estimator, thus, the dominant frequency of the power spectral distributions provided by these estimators agree with the repetition frequency of the intestinal slow wave not only in internal but also in external recordings. Hence, it is possible to detect non-invasively the basic electric rhythm of the intestine. On the other hand, it was shown that the slow wave frequency can change throughout recordings sessions in fast state. This evolution can behave in three different ways: type I with no significant changes in the BER frequency; type II when BER frequency follows a similar pattern to the intestinal motility index (IMI) although with a time-delay; and finally type III that is similar to type II, but the changes of the BER frequency are synchronized with the IMI.
The coherence function between internal and external signals, presented the maximum coherence value in the frequency which corresponds to the intestinal BER. The values obtained show a linear relationship between the spectra of internal and external signals. Specifically, the results indicate that the intestinal activity recorded on the abdominal surface corresponds to the region of middle jejunum. This agrees with the results obtained by the spectral analysis.
This work proves that it is possible to detect non-invasively the intestinal pacemaker activity and to monitor the frequency of the bowel basic electrical rhythm from abdominal surface recording of the EEnG. In addition, the proposed methodology permits to estimate the region of the small bowel which has been non-invasively recorded.