凝視心臟：用於rPPG與健康生物標記估計的多視角影片資料集

摘要

遠程光電容積描記法（rPPG）的進展受到現有公開數據集關鍵問題的限制：規模小、面部視頻的隱私問題以及條件缺乏多樣性。本文介紹了一個新穎的、全面的、大規模的多視角視頻數據集，用於rPPG和健康生物標誌物的估計。我們的數據集包含來自600名受試者的3600段同步視頻記錄，這些記錄是在不同條件下（靜息和運動後）使用多個消費級相機從不同角度捕捉的。為了實現生理狀態的多模態分析，每段記錄都配備了100 Hz的PPG信號以及擴展的健康指標，如心電圖、動脈血壓、生物標誌物、溫度、血氧飽和度、呼吸頻率和壓力水平。利用這些數據，我們訓練了一個高效的rPPG模型，並在跨數據集場景中與現有方法進行質量比較。我們數據集和模型的公開發布應能顯著加快AI醫療助手開發的進程。

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.

凝視心臟：用於rPPG與健康生物標記估計的多視角影片資料集

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

摘要

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