Key result
The bipolar velocity estimation algorithm rapidly estimated gastric slow wave wavefront velocities with 19.2 direction error and 2.0 mm/s speed error compared to standard methods in pig models.
Why the study?
Capturing gastric slow wave wavefront velocity using high-resolution in vivo recordings typically requires a standard marking-and-grouping approach with manual review, motivating a more efficient estimation method.
The BVE algorithm enables efficient estimation of gastric slow wave wavefront velocities in high-resolution recordings with minimal errors.
Supports efficient gastric mapping in preclinical models; leaves open human validation and clinical translation.
Objective: Gastric bio-electrical slow waves are, in part, responsible for coordinating motility. High-resolution (HR) in vivo recordings can be used to capture the wavefront velocity of the propagating slow waves. A standard marking-and-grouping approach is typically employed along with manual review. Here, a bipolar velocity estimation (BVE) method was developed, which utilized local directional information to estimate the wavefront velocity in an efficient manner. Methods: With this approach, unipolar in vivo HR recordings were used to construct bipolar recordings in different directions. Then, the local directionality of the slow wave was extracted by calculating time delay information. The accuracy of the method was verified using synthetic data and then validated with in vivo HR pig experimental recordings. Results: Against ventilator noise amplitude of 0% - 70% of the average slow wave amplitude, the direction and speed error increased from 4.4 and 0.9 mm/s to 8.6 and 1.4 mm/s. For signals added with high-frequency noise with signal-to-noise ratios of 60 dB - 12 dB, the error increased from 8.0 and 1.0 mm/s to 9.8 and 1.2 mm/s. For experimental signals, the BVE algorithm resulted in 19.2 1.7 of direction error and 2.0 0.2 mm/s of speed error, when compared to the standard marking-and-grouping method. Conclusion: Gastric slow wave wavefront velocities were estimated rapidly using the BVE algorithm with minimal errors. Significance: The BVE algorithm enables the ability to estimate wavefront velocities in HR recordings in an efficient manner.
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A 2021 study studied Gastric slow wave motility. Bipolar velocity estimation (BVE) method vs. Standard marking-and-grouping method was evaluated on Direction and speed error of wavefront velocity estimation. The bipolar velocity estimation algorithm rapidly estimated gastric slow wave wavefront velocities with 19.2 direction error and 2.0 mm/s speed error compared to standard methods in pig models.
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