Physiological Signal Synthesis and Classification: Assessing Entropy Change and Other Physiological Signals

This dataset accompanies the manuscript "Physiological Signal Synthesis and Classification: Assessing Entropy Change and Other Health Metrics". It contains a single-subject physiological dataset of 1,806 samples collected across seven tasks, featuring heart rate (HR), blood pressure (BP), temperature (T), and derived entropy values (ΔS = ΔHR × ΔBP / ΔT). In addition to the original data, the dataset includes 13 synthetic data variants generated using bootstrap resampling, variational autoencoders (VAEs), and generative adversarial networks (GANs), including WGAN-GP, CycleGAN, InfoGAN, and others.

Each synthetic dataset is aligned in format and labeling with the original dataset to support reproducibility and direct classifier training. This dataset is suitable for research in synthetic data generation, biomedical machine learning, signal classification, and entropy modeling.