Enhancement of the modified p-spectrum for use in real-time QRS complex detection
Bibliographic record
Abstract
QRS complex (heart beat) detection is frequently used by physicians to detect abnormal electrical activities (such as the cardiac arrhythmia, tachycardia, and bradycardia) in the heart. Algorithms for real-time detection of cardiac arrhythmia are critical, as ambulances and critical care facilities often require heart rate data for in-situ diagnosis of a patient. In this paper, a new algorithm based on the modified p-spectrum transform for QRS complex detection is proposed. The strengths of the original transform are inherited, allowing for high accuracy detection without requiring a priori knowledge of the electrocardiograph (ECG) signal. When tested using the MIT-BIH Arrhythmia Database, the new algorithm yields identical performance characteristics and require substantially less computation time. All 48 1/2-hour ECG datasets were tested and the proposed approach outperformed by a factor of up to 3.5 at high sampling frequencies.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".