ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2015
Detection of the Recovery Phase of in vivo gastric slow wave recordings.
Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Gastric slow-wave morphology in health and disease.Digestive diseases and sciences · 2026Article
- Improved Visualization of Gastrointestinal Slow Wave Propagation Using a Novel Wavefront-Orientation Interpolation Technique.IEEE transactions on bio-medical engineering · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Gastric motility is coordinated by bio-electrical events known as slow waves. Abnormalities in slow waves are linked to major functional and motility disorders. In recent years, the use of high-resolution (HR) recordings have provided a unique view of spatiotemporal activation profiles of normal and dysrhythmic slow wave activity. To date, in vivo studies of gastric slow wave activity have primarily focused on the activation phase of the slow wave event. In this study, the recovery phase of slow waves was investigated through the use of HR recording techniques. The recovery phase of the slow wave event was detected through the use of the signal derivative, computed via a wavelet transform. The activation to recovery interval (ARi) metric was computed as a difference between the recovery time and activation time. The detection method was validated with synthetic slow wave signals of varying morphologies with the addition of synthetic ventilator and high frequency noise. The methods was then applied to HR experimental porcine gastric slow wave recordings. Ventilator noise more than 10% of the slow wave amplitude affected the estimation of the ARi metric. Signal to noise ratio below 3 dB affected the ARi metric, but with minor deviation in accuracy. Experimental ARi values ranged from 3.7-4.7 s from three data sets, with significant differences across them.
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Registered trials
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