title: Computer-supported analysis of continuous ambulatory manometric recordings in the human small bowel.
abstract: An algorithm has been developed for the offline analysis of prolonged manometric recordings in the upper small intestine of humans. Sample data are acquired in the human duodenum and jejunum six solid-state strain-gauge transducers mounted on a silicon catheter that is connected to a portable digital recording device. The data are sampled at 4 Hz and filtered. For accurate calculations, the filtered signals are converted to cubic B-spline functions of order four. Based on an exponential weighted moving average, a base-line is calculated from the signal. Contractions are recognised on the basis of thresholds for minimum amplitude and duration. The developed algorithm calculates properties of these contractions, such as amplitude, duration, area and a motility index. In addition, the program automatically recognises normal motor patterns of the fasted human small intestine, such as the migrating motor complex, and aids in the identification of the postprandial motor pattern. Motor patterns are defined in terms of properties such as contraction frequency and propagation. In a validation procedure using conventional manual analysis, the program correctly identifies the number of individual contractions with a 98% confidence interval and also correctly recognises 96% of phase 3 motor activity.
authors.affiliation: Center for Gastrointestinal Research, University of Leuven, Belgium.
authors.forename: A
authors.initials: A
authors.lastname: Andrioli
authors.forename: A
authors.initials: A
authors.lastname: Wilmer
authors.forename: G
authors.initials: G
authors.lastname: Coremans
authors.forename: J
authors.initials: J
authors.lastname: Vandewalle
authors.forename: J
authors.initials: J
authors.lastname: Janssens
mesh_terms: D000465:Algorithms; D000553:Ambulatory Care / Q000379:methods*; D005769:Gastrointestinal Motility; D006801:Humans; D007421:Intestine, Small / Q000502:physiology*; D008365:Manometry / Q000379:methods*; D012815:Signal Processing, Computer-Assisted