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This paper reports on an in-depth study of electrocardiogram (ECG) biometricsin everyday life. We collected ECG data from 20 people over a week, using anon-medical chest tracker. We evaluated user identification accuracy in severalscenarios and observed equal error rates of 9.15% to 21.91%, heavily dependingon 1) the number of days used for training, and 2) the number of heartbeatsused per identification decision. We conclude that ECG biometrics can work inthe wild but are less robust than expected based on the literature,highlighting that previous lab studies obtained highly optimistic results withregard to real life deployments. We explain this with noise due to changingbody postures and states as well as interrupted measures. We conclude withimplications for future research and the design of ECG biometrics systems forreal world deployments, including critical reflections on privacy.

Heartbeats in the Wild: A Field Study Exploring ECG Biometrics in Everyday Life