This repository relates to the following topic:
Evaluating Machine Learning Models for Blood Pressure Estimation from PPG Data Beyond Intensive Care
For running the notebooks:
pipenv install
pipenv shell
pipenv run jupyter notebook
The notebooks in features process raw PPG data and estimate blood pressure for 3 different datasets:
HYPE: extract_features_and_predict_bp_from_ppg_hype.ipynb
EVAL: extract_features_and_predict_bp_from_ppg_eval.ipynb
LIANG: extract_features_and_predict_bp_from_ppg_liang.ipynb
For further analysis, you can use the notebooks under analysis.
EVAL: https://www.kaggle.com/mkachuee/noninvasivebp (original)
However, I processed it and used the following file as the input to the notebook: https://doi.org/10.6084/m9.figshare.12649691
HYPE: Available to the scientific community through a data agreement. Please fill in the following form: https://forms.gle/M8DDtuMeWGfT3k4y5