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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".