Photoplethysmography (PPG) is a non-invasive technique that measures changes in blood flow volume through optical means. Accurate detection of peaks in the PPG waveform allows the extraction of the heart rate variability (HRV), a recognized indicator for the health of the cardiac and autonomic nervous systems. We make available a novel dataset comprising 66 minutes of PPG recordings from healthy individuals and patients with cardiopulmonary diseases, in three distinct phases of an acquisition protocol, with annotations for every systolic peak present. The dataset composition and organization are detailed in the paper that acompanies the dataset.

Paper which describes the dataset acquisition and usage: @misc{machado2023srmac, title={SRMAC -- Smoothed Recursive Moving Average Crossover for Real-Time Systolic Peak Detection in Photoplethysmography}, author={Cesar Abascal Machado and Victor O. Costa and Cesar Augusto Prior and Cesar Ramos Rodrigues}, year={2023}, eprint={2312.10013}, archivePrefix={arXiv}, primaryClass={eess.SP}} Git repository with the source code used in the implementation and test of a recursive peak detector: https://github.com/GMicro-uPPG/SRMAC_peak_detector.