Blood Pressure Level and Heart Rate Detection from Photoplethysmography Signals Using DT–CWT
Why this work is in the frame
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Bibliographic record
Abstract
In this study, it was aimed to estimate systolic and diastolic blood pressures and heart rate using Photoplethysmography (PPG) signals. The PPG signals data used in the study were obtained from an open database containing signals and information of 219 people. With the help of the Dual Tree Complex Wavelet Transform (DT-CWT) method, The properties such as the average power, absolute value mean, kurtosis, skewness and standard deviation of the coefficients of each frequency subbands were obtained. Regression analysis was performed on the extracted PPG signals using Linear Regression (DR), Random Forest (RF) and Support Vector Machines (SVM) algorithms in the Weka program, and blood pressure levels and heart rates were estimated. As a result of the regression analysis, it was seen that blood pressure and heart rate estimations with a higher correlation coefficient and a lower average margin of error, heart rate and diastolic blood pressure analysis with the RF algorithm using the DT-CWT method, and systolic blood pressure analysis with the SVM algorithm would be more accurate.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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