MPU-rPPG Sample Dataset

Remote photoplethysmography (rPPG) is a non-contact method for monitoring physiological signals by analyzing subtle changes in skin light intensity caused by blood volume fluctuations. As rPPG moves closer to real-world deployment, comprehensive datasets are essential for the development of robust algorithms across diverse conditions and populations. Building on existing efforts, we introduce the MPU-rPPG dataset, designed to bridge current gaps and establish a new gold standard for rPPG research. This dataset captures high-fidelity physiological signals from multiple body regions (including the face and limbs) under varying light conditions and environments. It supports heart rate ranges from 50–160 bpm, accommodating both resting states and high-intensity activities, and includes a diverse set of subjects across different skin tones and demographics. The versatility of the MPU-rPPG dataset enables applications from daily health tracking to advanced early-warning systems in professional settings, such as hospitals, driver fatigue monitoring, and detection of heart rate anomalies during endurance events like marathons. By addressing these critical needs, the MPU-rPPG dataset provides a comprehensive foundation for the development of real-world rPPG systems and is committed to setting a new benchmark for future research.远程光电容积描记法（Remote photoplethysmography，rPPG）是一种非接触式生理信号监测技术，通过分析血液容量波动引发的皮肤光照强度细微变化，实现生理信号的无接触采集与监测。随着rPPG愈发贴近实际落地应用，构建覆盖多样化场景与人群的鲁棒算法亟需高质量综合数据集作为支撑。基于现有研究基础，本研究推出MPU-rPPG数据集，旨在弥补当前研究空白，为rPPG领域研究确立全新的金标准。该数据集可采集不同光照条件与环境下，多身体部位（涵盖面部与四肢）的高保真生理信号。数据集覆盖心率范围50至160次/分钟，可适配静息状态与高强度运动场景，同时纳入了不同肤色与人口统计学特征的多样化受试群体。MPU-rPPG数据集具备极强通用性，可支撑从日常健康监测，到专业场景下的先进预警系统等多类应用，例如医院场景、驾驶员疲劳监测，以及马拉松等耐力赛事中的心率异常检测。通过满足上述关键需求，MPU-rPPG数据集可为实际落地的rPPG系统研发提供全面的研究基础，并致力于为未来相关研究树立全新标杆。