Time-Frequency Domain Analysis via Pulselets for Non-contact Heart Rate Estimation from Remotely Acquired Photoplethysmograms
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Bibliographic record
Abstract
A novel method for remote heart rate estimation via analysis in the time-frequency domain is proposed. A photoplethysmogram (PPG) waveform is constructed via a Bayesian minimization approach with the required posterior probability obtained through an importance-weighted Monte Carlo sampling method. A pulselet (wavelet chosen for its similarities with a finger pulse oximiter PPG waveform), is used in the continuous wavelet transform to produce a map of the wavelet energy response in the time-frequency domain. This allows the heart rate frequency to be estimated at each time step, accounting for naturally occurring changes in heart rate over time which may cause error with frequency domain based methods. The frequency corresponding to the highest wavelet response at each time step is averaged across the entire time series to estimate the average heart rate. Experimental results against a data set of 30 videos show an improvement over current state-of-the-art methods.
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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