# Vectorgastrogram: dynamic trajectory and recurrence quantification analysis to assess slow wave vector movement in healthy subjects

## TL;DR

This study introduces a new method called vectorgastrogram to analyze gastric slow wave patterns in healthy individuals, offering insights into gastric activity that could aid in diagnosing gastric disorders.

## Contribution

The paper introduces a novel technique combining MVMD and vectorgastrogram to robustly identify and analyze gastric slow wave patterns.

## Key findings

- MVMD reliably detects gastric slow waves with over 91% detection rates in fasting and postprandial states.
- Postprandial ingestion increases amplitude and frequency of gastric slow waves with less than 5.3% frequency instability.
- RQA metrics indicate increased intensity and coordination of gastric slow waves after eating.

## Abstract

Functional gastric disorders entail chronic or recurrent symptoms, high prevalence and a significant financial burden. These disorders do not always involve structural abnormalities and since they cannot be diagnosed by routine procedures, electrogastrography (EGG) has been proposed as a diagnostic alternative. However, the method still has not been transferred to clinical practice due to the difficulty of identifying gastric activity because of the low-frequency interference caused by skin–electrode contact potential in obtaining spatiotemporal information by simple procedures. This work attempted to robustly identify the gastric slow wave (SW) main components by applying multivariate variational mode decomposition (MVMD) to the multichannel EGG. Another aim was to obtain the 2D SW vectorgastrogram VGGSW from 4 electrodes perpendicularly arranged in a T-shape and analyse its dynamic trajectory and recurrence quantification (RQA) to assess slow wave vector movement in healthy subjects. The results revealed that MVMD can reliably identify the gastric SW, with detection rates over 91% in fasting postprandial subjects and a frequency instability of less than 5.3%, statistically increasing its amplitude and frequency after ingestion. The VGGSW dynamic trajectory showed a statistically higher predominance of vertical displacement after ingestion. RQA metrics (recurrence ratio, average length, entropy, and trapping time) showed a postprandial statistical increase, suggesting that gastric SW became more intense and coordinated with a less complex VGGSW and higher periodicity. The results support the VGGSW as a simple technique that can provide relevant information on the “global” spatial pattern of gastric slow wave propagation that could help diagnose gastric pathologies.