Methods for the detection of ECG characteristic points
Bibliographic record
Abstract
The electrocardiogram (ECG) is a measurement of the electrical signals associated with the heart and is a key diagnostic tool and patient monitoring device for clinicians. This work presents and compares algorithms for per cycle temporal location of the key ECG phases using 5 methods: 2 pt and 5 pt slope, correlation, wavelet analysis and empirical mode decomposition (EMD). A new wavelet algorithm is proposed using the Daubechies DB6 wavelet and octave band decomposition followed by a series of reconstruction estimates used for temporal localization of each of the ECG phases and it is shown to detect R waves accurately (97.6% — st dev 0.048). A new EMD algorithm is proposed that uses reconstruction estimates to determine the temporal location of each of the ECG phases and it is shown to detect R waves accurately (98.5% — st dev 0.042).
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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".