An automated artifact detection and rejection system for body surface gastric mapping.

ABSTRACT:

Background

Body surface gastric mapping (BSGM) is a new clinical tool for gastric motility diagnostics, providing high-resolution data on gastric myoelectrical activity. Artifact contamination was a key challenge to reliable test interpretation in traditional electrogastrography. This study aimed to introduce and validate an automated artifact detection and rejection system for clinical BSGM applications.

Methods

Ten patients with chronic gastric symptoms generated a variety of artifacts according to a standardized protocol (176 recordings) using a commercial BSGM system (Alimetry, New Zealand). An automated artifact detection and rejection algorithm was developed, and its performance was compared with a reference standard comprising consensus labeling by 3 analysis experts,

SUBMITTER: Calder S 

PROVIDER: S-EPMC9786272 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature