Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/5746
Title: | Acquisition and Time Delay Estimates of Canine Gastric Nerve Signals |
Authors: | Yu, Jiann-Liuh James |
Advisor: | Sinha, N.K. Daniel, E.E. |
Department: | Electrical and Computer Engineering |
Keywords: | Electrical and Computer Engineering;Electrical and Computer Engineering |
Publication Date: | Feb-1986 |
Abstract: | <p>Approaches to the investigation of myogenic and hormonal controls in the mediation of gut motility are well understood, however methods to analyze neural control remain to be developed. I have developed a cannula system with nerve cuff electrodes, subserosal bipolar electrodes, and extraluminal strain gauges to simultaneously monitor the vagal nerve, myoelectric (ECA), and contractile activities in chronic dogs. The cuff electrodes were used to both stimulate and record nerve signals. Five healthy dogs were implanted with such cannula on the gastric area, with the cuff electrodes placed on the branches of the anterior nerve of Latarjet. The condition of the cuff electrodes were monitored by impedance measurements, while that of the nerves under the cuff electrode were studied by electron microscopy (EM). Three Time Delay Estimation (TDE) algorithms: General Cross Correlation (GCC), Smooth Coherence Of Transform (SCOT), and Maximum Likelihood (ML) methods were simulated with three types of signals as inputs: Band limited Gaussian White Noise (GWN), Sine wave (SINE), and Impulses of random intervals (IMP). Results of the analysis of the recorded neural signals show that the three algorithms can be used to study the sensory and motor patterns of the compound nerve signals with the SCOT and ML methods being superior than the GCC method. The results from the EM studies suggested that the cuff electrode caused loss of the myelinated axons and the larger diameter unmyelinated axons. Based on the results of this study, relevant physiological interpretations were also discussed.</p> |
URI: | http://hdl.handle.net/11375/5746 |
Identifier: | opendissertations/1091 2610 1314741 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
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fulltext.pdf | 4.43 MB | Adobe PDF | View/Open |
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