Multimodal Remote Cardiac Cycle-Level Variability Dataset (MRC²VD)

The dataset includes synchronized recordings of electroencephalogram (EEG), electrocardiogram (ECG), photoplethysmogram (PPG), ballistocardiogram (BCG), respiratory data from chest pressure sensors, and video data. By capturing high-resolution temporal dynamics across these modalities, the dataset enables detailed analysis of cycle-level fluctuations in cardiac signals, such as beat-to-beat variations in ECG, PPG, and BCG waveforms. This comprehensive resource provides a foundation for advancing methodologies in heart rate (HR) and heart rate variability (HRV) characterization, as well as for exploring the interdependencies between different physiological signals. Potential applications span biomedical engineering, psychophysiology, and health monitoring, with specific relevance to non-invasive cardiac health assessment, stress detection, and sleep pattern analysis. The dataset’s emphasis on cycle-level variability offers new insights into the physiological mechanisms underlying cardiac signal dynamics, bridging gaps between signal processing and clinical diagnostics.This dataset contains original facial videos that may be identifiable. Access is restricted to researchers who agree to the Data Usage Agreement prohibiting re-identification and redistribution.