A System and Method for Online High-Resolution Mapping of Gastric Slow-Wave Activity

Abstract

High-resolution (HR) mapping employs multielectrode arrays to achieve spatially detailed analyses of propagating bioelectrical events. A major current limitation is that spatial analyses must currently be performed "off-line" (after experiments), compromising timely recording feedback and restricting experimental interventions. These problems motivated development of a system and method for "online" HR mapping. HR gastric recordings were acquired and streamed to a novel software client. Algorithms were devised to filter data, identify slow-wave events, eliminate corrupt channels, and cluster activation events. A graphical user interface animated data and plotted electrograms and maps. Results were compared against off-line methods. The online system analyzed 256-channel serosal recordings with no unexpected system terminations with a mean delay 18 s. Activation time marking sensitivity was 0.92; positive predictive value was 0.93. Abnormal slow-wave patterns including conduction blocks, ectopic pacemaking, and colliding wave fronts were reliably identified. Compared to traditional analysis methods, online mapping had comparable results with equivalent coverage of 90% of electrodes, average RMS errors of less than 1 s, and CC of activation maps of 0.99. Accurate slow-wave mapping was achieved in near real-time, enabling monitoring of recording quality and experimental interventions targeted to dysrhythmic onset. This work also advances the translation of HR mapping toward real-time clinical application.