论文标题
野外心跳：一项现场研究，探索日常生活中的心电图生物识别技术
Heartbeats in the Wild: A Field Study Exploring ECG Biometrics in Everyday Life
论文作者
论文摘要
本文报告了对日常生活中心电图（ECG）生物识别技术的深入研究。我们使用非医疗胸部跟踪器收集了一周内20人的ECG数据。我们在几种情况下评估了用户识别精度，并观察到相等的错误率为9.15％至21.91％，这取决于1）训练的天数，以及2）每个识别决定使用的心跳数量。我们得出的结论是，心电图生物识别技术可以在野外起作用，但根据文献的稳健性不如预期，这强调了以前的实验室研究在现实生活部署方面获得了高度乐观的结果。由于身体姿势和状态不断变化以及措施中断，我们用噪音来解释这一点。我们最终对未来研究的影响以及对现实世界部署的心电图生物识别系统的设计，包括对隐私的批判性思考。
This paper reports on an in-depth study of electrocardiogram (ECG) biometrics in everyday life. We collected ECG data from 20 people over a week, using a non-medical chest tracker. We evaluated user identification accuracy in several scenarios and observed equal error rates of 9.15% to 21.91%, heavily depending on 1) the number of days used for training, and 2) the number of heartbeats used per identification decision. We conclude that ECG biometrics can work in the wild but are less robust than expected based on the literature, highlighting that previous lab studies obtained highly optimistic results with regard to real life deployments. We explain this with noise due to changing body postures and states as well as interrupted measures. We conclude with implications for future research and the design of ECG biometrics systems for real world deployments, including critical reflections on privacy.
