Prototype algorithm for automated determination of gastric slow wave characteristics

An algorithm for determining the frequency and propagation time of the gastric slow wave has been designed for integration into a demand gastric pacing system. The algorithm analyses the serosal activity in both the time and frequency domains, and the results are compared to produce a conclusion only when the values are within 5% of each other. Thus, the probability of inappropriate intervention is reduced, at the expense of unidentified segments. The system is verified by comparing the conclusions produced by the algorithm with conclusions from hand analysis of seven canine and one human serosal recordings. The algorithm correctly identifies the slow-wave frequency in the distal portion of the stomach for 90% of the segments, while producing no incorrect results. Slow-wave propagation times in the antrum are correctly identified for 84% of the segments, with no incorrect identifications.

[1]  R. H. Smallwood,et al.  Analysis of gastric electrical signals from surface electrodes using phaselock techniques: Part 1—System design , 1978, Medical and Biological Engineering and Computing.

[2]  J. L. Grashuis,et al.  What is measured in electrogastrography? , 1980, Digestive Diseases and Sciences.

[3]  N. V. Thakor,et al.  Optimal QRS detector , 1983, Medical and Biological Engineering and Computing.

[4]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[5]  Richard W. McCallum,et al.  Electrogastrography: Principles and Applications , 1994 .

[6]  D. A. Linkens,et al.  Estimation of frequencies of gastrointestinal electrical rhythms using autoregressive modelling , 2006, Medical and Biological Engineering and Computing.

[7]  N. Senninger,et al.  [Electric stimulation of the human stomach]. , 1998, Zeitschrift fur Gastroenterologie.

[8]  J. Cullen,et al.  The future of intestinal pacing. , 1994, Gastroenterology clinics of North America.

[9]  Cullen Jj,et al.  The future of intestinal pacing. , 1994 .

[10]  D A Linkens,et al.  Interactive graphics analysis of gastrointestinal electrical signals. , 1974, IEEE transactions on bio-medical engineering.

[11]  R A Ross,et al.  Gastric pacing improves emptying and symptoms in patients with gastroparesis. , 1998, Gastroenterology.

[12]  K. Kelly,et al.  Pacing the canine stomach with electric stimulation. , 1972, The American journal of physiology.

[13]  J. L. Grashuis,et al.  Running spectrum analysis as an aid in the representation and interpretation of electrogastrographic signals , 2006, Medical and Biological Engineering and Computing.

[14]  C. Zheng,et al.  QRS detection by wavelet transform , 1993, Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Societ.

[15]  R. H. Smallwood,et al.  Intestinal smooth muscle electrical potentials recorded from surface electrodes , 2006, Medical and biological engineering.

[16]  Y. J. Kingma,et al.  Study of transcutaneous and intraluminal measurement of gastric electrical activity in humans , 1987, Medical and Biological Engineering and Computing.

[17]  O. Pahlm,et al.  Software QRS detection in ambulatory monitoring — a review , 1984, Medical and Biological Engineering and Computing.