凝视心灵深处：面向远程光电容积描记术与健康生物标志物估计的多视角视频数据集

摘要

远程光电容积描记术（rPPG）的发展受限于现有公开数据集的关键问题：规模小、面部视频的隐私担忧以及条件多样性不足。本文介绍了一个新颖的、全面的大规模多视角视频数据集，用于rPPG及健康生物标志物估计。我们的数据集包含来自600名受试者的3600段同步视频记录，这些记录在多种条件下（静息和运动后）使用多台不同角度的消费级相机拍摄。为了实现对生理状态的多模态分析，每段视频记录均配以100Hz的PPG信号及扩展的健康指标，如心电图、动脉血压、生物标志物、体温、血氧饱和度、呼吸频率和压力水平。利用这些数据，我们训练了一个高效的rPPG模型，并在跨数据集场景中将其质量与现有方法进行了比较。我们数据集和模型的公开发布，预计将极大加速AI医疗助手研发的进程。

English

Progress in remote PhotoPlethysmoGraphy (rPPG) is limited by the critical issues of existing publicly available datasets: small size, privacy concerns with facial videos, and lack of diversity in conditions. The paper introduces a novel comprehensive large-scale multi-view video dataset for rPPG and health biomarkers estimation. Our dataset comprises 3600 synchronized video recordings from 600 subjects, captured under varied conditions (resting and post-exercise) using multiple consumer-grade cameras at different angles. To enable multimodal analysis of physiological states, each recording is paired with a 100 Hz PPG signal and extended health metrics, such as electrocardiogram, arterial blood pressure, biomarkers, temperature, oxygen saturation, respiratory rate, and stress level. Using this data, we train an efficient rPPG model and compare its quality with existing approaches in cross-dataset scenarios. The public release of our dataset and model should significantly speed up the progress in the development of AI medical assistants.

凝视心灵深处：面向远程光电容积描记术与健康生物标志物估计的多视角视频数据集

Gaze into the Heart: A Multi-View Video Dataset for rPPG and Health Biomarkers Estimation

摘要

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