Model predictive control of the cardiac amplitude of alternans PDE
Bibliographic record
Abstract
Sudden cardiac death resulting from ventricular arrhythmia is one of the leading causes of mortality in the United States. The beat-to-beat oscillations in the action potential duration (APD) of paced cardiac cells, defined as cardiac alternans, has been identified as a potential precursor to ventricular arrhythmia. Therefore, the annihilation of these alternans is a promising antiarrhythmic strategy. In this work, the small amplitude of alternans partial differential equation (PDE) for a one dimensional cable of cardiac cells is stabilized through model predictive control (MPC). In our proposed control strategy, both boundary and spatially distributed actuators are utilized in suppressing the alternans along the cable. The low-order MPC formulation is developed for the finite-dimensional, discrete state space representation of the PDE. Furthermore, input and state constraints are addressed explicitly in the MPC formulation. The input constraints may arise due to actuator limitations, while state constraints are naturally present in cardiac systems. By satisfying these constraints, we can ensure that the controller action will not induce conduction block in the cardiac cells. Simulation results are presented to demonstrate the successful annihilation of alternans using the proposed control algorithm.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".