首个基于事件相机的生理数据集，用于非接触式脉搏波检测
EMPD: An Event-based Multimodal Physiological Dataset for Remote Pulse Wave Detection
- 用激光增强皮肤微振动，通过事件相机捕捉高精度生理信号
- 包含193条来自83人的数据，心率范围40-110 BPM，含运动前后状态
- 适合做神经形态生理监测算法研究，尤其关注时间精度的场景
基于传统帧式相机的远程光电容积脉搏波图（rPPG）常受运动伪影和时间分辨率限制。为解决这些问题，本文提出首个专为事件相机设计的非接触生理感知基准数据集EMPD。该数据集采用激光辅助采集系统，将桡动脉引起的微弱皮肤振动调制为可被类脑传感器检测的显著信号。硬件平台集成高分辨率事件相机捕捉微运动与强度瞬变、工业级RGB相机提供传统rPPG基准，以及临床级血氧仪记录真实脉搏波形。EMPD包含193条有效记录，覆盖83名受试者在静息与运动后状态下的心率范围（40–110 BPM）。通过提供毫秒级同步的多模态数据，该数据集为发展鲁棒的神经形态生理监测算法提供了关键资源。数据集已公开：https://doi.org/10.5281/zenodo.18765701
原文摘要 · Abstract (English)
Remote photoplethysmography (rPPG) based on traditional frame-based cameras often struggles with motion artifacts and limited temporal resolution. To address these limitations, we introduce EMPD (Event-based Multimodal Physiological Dataset), the first benchmark dataset specifically designed for non-contact physiological sensing via event cameras. The dataset leverages a laser-assisted acquisition system where a high-coherence laser modulates subtle skin vibrations from the radial artery into significant signals detectable by a neuromorphic sensor. The hardware platform integrates a high-resolution event camera to capture micro-motions and intensity transients, an industrial RGB camera to provide traditional rPPG benchmarks, and a clinical-grade pulse oximeter to record ground truth PPG waveforms. EMPD contains 193 valid records collected from 83 subjects, covering a wide heart rate range (40-110 BPM) under both resting and post-exercise conditions. By providing precisely synchronized multimodal data with microsecond-level temporal precision, EMPD serves as a crucial resource for developing robust algorithms in the field of neuromorphic physiological monitoring. The dataset is publicly available at: https://doi.org/10.5281/zenodo.18765701
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