Evidence map›Paper›PMID 26737682›Full record

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.

Niranchan Paskaranandavadivel, Xingzheng Pan, Peng Du, Gregory O'Grady, Leo K Cheng

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Gastric slow-wave morphology in health and disease.Digestive diseases and sciences · 2026
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Niranchan Paskaranandavadivel
Xingzheng Pan
Peng Du
Gregory O'Grady
Leo K Cheng

Funding

Realistic models of gastrointestinal bioelectromagnetismR01DK064775 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CHENG, LEO · 2004 to 2014
$2.6M
NIDDK NIH HHS R01 DK064775NIDDK NIH HHS R01 DK64775
6 · The paper itself

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.

Indexed as

AnimalsElectrodesElectromyographyElectrophysiological PhenomenaMuscle, SmoothSignal-To-Noise RatioStomachSwine

Identifiers

PMID26737682
PMCPMC4938633

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.