Design of a Hamming-distance classifier for ECG biometrics
Why this work is in the frame
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Bibliographic record
Abstract
In existing ECG-based biometric recognition systems, the feature extraction and matching are performed in Euclidean spaces. However, there are many scenarios (e.g., biometric template encryption for privacy protection, or low-complexity classification in an identification mode of operation) in which it is useful to binarize the feature vectors. The main contribution of this paper is a Hamming-distance classifier for ECG biometrics based on SPEC-Hashing. The proposed system was evaluated over a database of ECG signals from 52 different subjects that were collected at the Biometrics Security Laboratory of the University of Toronto. The EER of the Hamming-distance classifier was found to be 5.5% for closed-set matching and 14.82% for open set matching.
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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 | 0.001 |
| 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 it