Validation of non-invasive body-surface gastric mapping for detecting electrophysiological biomarkers by simultaneous high-resolution serosal mapping in a porcine model
S. Calder, L. K. Cheng, C. Andrews, N. Paskaranandavadivel, S. Waite, S. Alighaleh, J. Erickson, A. Gharibans, G. O'Grady, P. Du
Abstract
Gastric disorders are increasingly prevalent, but reliable clinical tools to objectively assess gastric function are lacking. Body-surface gastric mapping (BSGM) is a non-invasive method for the detection of gastric electrophysiological biomarkers including slow wave direction, which have correlated with symptoms in patients with gastroparesis and functional dyspepsia. However, no studies have validated the relationship between gastric slow waves and body surface activation profiles. This study aimed to comprehensively evaluate the relationship between gastric slow waves and body-surface recordings. High-resolution electrode arrays were placed to simultaneously capture slow waves from the gastric serosa (32x6 electrodes at 4 mm resolution) and abdominal surface (8x8 at 20 mm inter-electrode spacing) in a porcine model. BSGM signals were extracted based on a combination of wavelet and phase information analyses. A total of 1185 individual cycles of slow waves assessed, out of which 897 (76%) were normal antegrade waves, occurring in 10/14 (71%) subjects studied. BSGM accurately detected the underlying slow wave in terms of frequency (r = 0.99, p = 0.43) as well as the direction of propagation (p = 0.41, F-measure: 0.92). In addition, the cycle-by-cycle match between BSGM and transitions of gastric slow waves in terms either or both temporal and spatial abnormalities was demonstrated. These results validate BSGM as a suitable method for non-invasively and accurately detecting gastric slow wave activation profiles from the body surface. Single sentence summarySimultaneous recordings of the stomach using serosal and body-surface electrode arrays demonstrated reliable detection of frequency and classification of propagation.
02 /Specification & Classification
Click any tag to browse matching papers- Assay
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- A case for slow-wave morphology as a functional biomarker of gastric disease
Jarrah M. Dowrick, Jonathan C. Erickson, … Timothy R. Angeli·bioRxiv·May 21, 2025
- Comparison of dry and wet electrodes for detecting gastrointestinal activity patterns from body surface electrical recordings
J. C. Erickson, E. Stepanyan, E. Hassid·bioRxiv·Apr 23, 2022
- Skin-conformal electronics for wearable electrogastrography monitoring
Liuxi Xing, Yulu Cai, … Jinxing Li·IEEE Journal on Flexible ElectronicsPeer-reviewed·Oct 20, 2025
- Gastric Neurons in the Nucleus Tractus Solitarius are Selective to the Orientation of Gastric Electrical Stimulation
Jiayue Cao, Xiaokai Wang, … Zhongming Liu·Journal of Neural EngineeringPeer-reviewed·Oct 1, 2021
- Towards Passive Dietary Monitoring: Dilated CNN-Based Meal Detection Using Ambulatory High-Resolution Electrogastrography
Belinda Chen, Sandya Subramanian·bioRxiv·Jun 17, 2026
- Surface-based Characterization of Gastric Anatomy and Motility using Magnetic Resonance Imaging and Neural Ordinary Differential Equation