High-resolution in vivo monophasic gastric slow waves to quantify activation and recovery profiles

Translation of an existing implantable cardiac monitoring device for measurement of gastric electrical slow-wave activity

BACKGROUND

Despite evidence that slow-wave dysrhythmia in the stomach is associated with clinical conditions such as gastroparesis and functional dyspepsia, there is still no widely available device for long-term monitoring of gastric electrical signals. Actionable biomarkers of gastrointestinal health are critically needed, and an implantable slow-wave monitoring device could aid in the establishment of causal relationships between symptoms and gastric electrophysiology. Recent developments in the area of wireless implantable gastric monitors demonstrate potential, but additional work and validation are required before this potential can be realized.

METHODS

We hypothesized that translating an existing implantable cardiac monitoring device, the Reveal LINQ™ (Medtronic), would present a more immediate solution. Following ethical approval and laparotomy in anesthetized pigs (n = 7), a Reveal LINQ was placed on the serosal surface of the stomach, immediately adjacent to a validated flexible-printed-circuit (FPC) electrical mapping array. Data were recorded for periods of 7.5 min, and the resultant signal characteristics from the FPC array and Reveal LINQ were compared.

KEY RESULTS

The Reveal LINQ device recorded slow waves in 6/7 subjects with a comparable period (p = 0.69), signal-to-noise ratio (p = 0.58), and downstroke width (p = 0.98) to the FPC, but with reduced amplitude (p = 0.024). Qualitatively, the Reveal LINQ slow-wave signal lacked the prolonged repolarization phase present in the FPC signals.

CONCLUSIONS & INFERENCES

These findings suggest that existing cardiac monitors may offer an efficient solution for the long-term monitoring of slow waves. Translation toward implantation now awaits.

A novel framework for the removal of pacing artifacts from bio-electrical recordings

BACKGROUND

Electroceuticals provide clinical solutions for a range of disorders including Parkinson's disease, cardiac arrythmias and are emerging as a potential treatment option for gastrointestinal disorders. However, pre-clinical investigations are challenged by the large stimulation artifacts registered in bio-electrical recordings.

METHOD

A generalized framework capable of isolating and suppressing stimulation artifacts with minimal intervention was developed. Stimulation artifacts with different pulse-parameters in synthetic and experimental cardiac and gastrointestinal signals were detected using a Hampel filter and reconstructed using 3 methods: i) autoregression, ii) weighted mean, and iii) linear interpolation.

RESULTS

Synthetic stimulation artifacts with amplitudes of 2 mV and 4 mV and pulse-widths of 50 ms, 100 ms, and 200 ms were successfully isolated and the artifact window size remained uninfluenced by the pulse-amplitude, but was influenced by pulse-width (e.g., the autoregression method resulted in an identical Root Mean Square Error (RMSE) of 1.64 mV for artifacts with 200 ms pulse-width and both 2 mV and 4 mV amplitudes). The performance of autoregression (RMSE = 1.45 ± 0.16 mV) and linear interpolation (RMSE = 1.22 ± 0.14 mV) methods were comparable and better than weighted mean (RMSE = 5.54 ± 0.56 mV) for synthetic data. However, for experimental recordings, artifact removal by autoregression was superior to both linear interpolation and weighted mean approaches in gastric, small intestinal and cardiac recordings.

CONCLUSIONS

A novel signal processing framework enabled efficient analysis of bio-electrical recordings with stimulation artifacts. This will allow the bio-electrical events induced by stimulation protocols to be efficiently and systematically evaluated, resulting in improved stimulation therapies.