Real-time gastric motility monitoring using transcutaneous intraluminal impedance measurements (TIIM)
Bibliographic record
Abstract
The stomach plays a critical role in digestion, processing ingested food mechanically and breaking it up into particles, which can be effectively and efficiently processed by the intestines. When the motility of the stomach is compromised, digestion is adversely affected. This can lead to a variety of disorders. Current diagnostic techniques for gastric motility disorders are seriously lacking, and are based more on eliminating other possibilities rather than on specific tests. Presently, gastric motility can be assessed by monitoring gastric emptying, food transit, intragastric pressures, etc. The associated tests are usually stationary and of relatively short duration. The present study proposes a new method of measuring gastric motility, utilizing the attenuation of an oscillator-induced electrical signal across the gastric tissue, which is modulated by gastric contractions. The induced high-frequency oscillator signal is generated within the stomach, and is picked up transluminally by cutaneous electrodes positioned on the abdominal area connected to a custom-designed data acquisition instrument. The proposed method was implemented in two different designs: first a transoral catheter was modified to emit the signal inside the stomach; and second, a gastric retentive pill was designed to emit the signal. Both implementations were applied in vivo on two mongrel dogs (25.50 kg and 25.75 kg). Gastric contractions were registered and quantitatively compared to recordings from force transducers sutured onto the serosa of the stomach. Gastric motility indices were calculated for each minute, with transluminal impedance measurements and the measurements from the force transducers showing statistically significant (p < 0.05) Pearson correlation coefficients (0.65 ± 0.08 for the catheter-based design and 0.77 ± 0.03 for the gastric retentive pill design). These results show that transcutaneous intraluminal impedance measurement has the potential with further research and development to become a useful diagnostic technique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".