Paper Info
Title
Chaotic behavior of gastric migrating myoelectrical complex.
Abstract
Nonlinear feedback induces oscillation, whereas dynamic equilibrium between positive and negative nonlinear feedback generates rhythm. Physiological rhythms are central to life. No absolutely stable or periodic rhythm exists in living tissues. It has been extensively reported that many rhythms in human and animal organs, such as the heart and brain, are, in fact chaotic. The aim of this paper is to investigate whether the migrating myoelectrical complex (MMC) of the stomach was chaotic. The study was performed in eight healthy female hound dogs (15-22 kg), implanted with four pairs of bipolar electrodes on the serosa of the stomach along the greater curvature. After the dogs were completely recovered from the surgery, one complete cycle of gastric MMC was recorded from the serosal electrodes. Using Takens' embedding theorem, two parameters reflecting chaotic behavior, the attractor and the Lyapunov exponent of the myoelectrical recording, were reconstructed and computed, respectively. Statistical analysis was performed to investigate the difference in the Lyapunov exponents among different phases of the MMC. The results show that the MMC of the stomach is chaotic. Different phases of the MMC are characterized with different shapes of the attractors and different values of Lyapunov exponents. The characteristic chaotic behavior of the gastric MMC may be utilized for the identification of different phases.
Year
DOI
Venue
2004
10.1109/TBME.2004.827561
IEEE transactions on bio-medical engineering
Keywords
Field
DocType
nonlinear feedback,15 to 22 kg,takens embedding theorem,bipolar electrodes,chaos,biomedical electrodes,female hound dogs,statistical analysis,attractor,medical signal processing,physiological rhythms,lyapunov exponent,stomach serosa,electromyography,chaotic behavior,gastric migrating myoelectrical complex,lyapunov methods
Stomach,Attractor,Oscillation,Nonlinear system,Control theory,Mathematical analysis,Computer science,Artificial intelligence,Chaotic,Lyapunov exponent,Computer vision,Rhythm,Statistical analysis
Journal
Volume
Issue
ISSN
51
8
0018-9294
Citations 
PageRank 
References 
2
0.77
2
Authors
3
Name
Order
Citations
PageRank
Zhishun S Wang120.77
Zhenya He220738.98
Jiande D Z Chen351.62