Data Augmentation for Generating Synthetic Electrogastrogram Time Series

TL;DR

This paper introduces a new method for generating customizable synthetic electrogastrogram (EGG) data to enhance dataset diversity for signal processing and AI training, with potential applications to other biosignals.

Contribution

A novel, customizable approach for synthetic EGG data generation that preserves key features and can be adapted for other biosignals, improving data availability for research.

Findings

Synthetic EGG data can distinguish postprandial and fasting states in over 70% of cases.

Generated features mimic real EGG signals and trends related to simulator sickness.

The method is freely available and adaptable for various biosignal synthesis.

Abstract

To address an emerging need for large number of diverse datasets for rigor evaluation of signal processing techniques, we developed and evaluated a new method for generating synthetic electrogastrogram time series. We used electrogastrography (EGG) data from an open database to set model parameters and statistical tests to evaluate synthesized data. Additionally, we illustrated method customization for generating artificial EGG time series alterations caused by the simulator sickness. Proposed data augmentation method generates synthetic EGG data with specified duration, sampling frequency, recording state (postprandial or fasting state), overall noise and breathing artifact injection, and pauses in the gastric rhythm (arrhythmia occurrence) with statistically significant difference between postprandial and fasting states in > 70% cases while not accounting for individual differences. Features obtained from the synthetic EGG signal resembling simulator sickness occurrence displayed expected trends. The code for generation of synthetic EGG time series is not only freely available and can be further customized to assess signal processing algorithms but also may be used to increase data diversity for training artificial intelligence (AI) algorithms. The proposed approach is customized for EGG data synthesis but can be easily utilized for other biosignals with similar nature such as electroencephalogram.