EgoHRV：用于自主神经反应与技能评估的自我中心式系统的连续心率变异性估计
EgoHRV: Continuous Heart Rate Variability Estimation from Egocentric Systems for Autonomic Response and Skill Assessment
- ETH Zürich（苏黎世联邦理工学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出EgoHRV方法，利用自我中心头戴设备的凝视摄像头结合3D骨干网络与低-高分解模块等，实现从凝视视频中连续估计HRV与HR，在HR/HRV估计中达最优准确率，集成后使EgoExo4D熟练度估计器准确率提升17.8%
AI中文摘要：
自我中心视觉系统通过可见线索捕捉人类行为，但会忽略自主神经状态的生理指标，如压力、投入度和注意力。心率变异性（HRV）是一种广泛应用的非侵入式压力下自主神经调节标志物，反映连续心跳间的微小时间差，而目前该指标无法通过自我中心平台获取，因为该平台中凝视视频的运动和噪声会掩盖这种精细时间差。本文提出EgoHRV，一种从已集成在自我中心头戴设备中的凝视摄像头估计心率变异性（HRV）及心率（HR）的方法。其流程结合3D骨干网络与新型低-高分解模块，从凝视视频中提取血容量脉冲（BVP）信号；跨域预训练对齐接触式与相机衍生信号的频域表示，使EgoHRV具备从凝视视频的细微波动中恢复HRV的时间精度。EgoHRV在自我中心视频的HR与HRV估计中达到了当前最优准确率，其感知不确定性的设计提升了下游行为建模性能；将本文的HRV估计与置信度指标集成到EgoExo4D的熟练度估计器中，准确率提升了17.8%。除技能评估外，连续HRV估计还为自我中心系统开启了压力与唤醒感知估计任务的可能性。代码：this https URL
英文摘要：
Egocentric vision systems capture human behavior from visible cues, but overlook physiological indicators of autonomic states such as stress, engagement, and attention. Heart rate variability (HRV) is a widely used noninvasive marker of autonomic regulation under stress. HRV reflects small timing differences between successive heartbeats and has so far been out of reach for egocentric platforms, where motion and noise in gaze video mask exactly this fine-grained timing. We propose EgoHRV, a method that estimates HRV as well as heart rate (HR) from the gaze cameras that are already integrated into egocentric headsets. Our pipeline combines a 3D backbone with a novel low--high decomposition module that extracts the blood volume pulse (BVP) signal from gaze video. Our cross-domain pretraining aligns the frequency-domain representations of contact-based and camera-derived signals. This alignment gives EgoHRV the temporal precision to recover HRV from the subtle fluctuations in gaze video. EgoHRV achieves state-of-the-art accuracy for HR and HRV estimation from egocentric video, and its uncertainty-aware design improves downstream behavioral modeling. Integrating our HRV estimates and confidence measures into EgoExo4D's proficiency estimator raises accuracy by 17.8%. Beyond skill, continuous HRV estimation also opens egocentric systems to stress- and arousal-aware estimation tasks. Code: https://github.com/eth-siplab/EgoHRV
