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

Honorable Mention
Motor Impairment Assistive Input TechnologiesBiosensors & Physiological MonitoringContext-Aware ComputingPhysicians, Nurses & CliniciansAthletes & Fitness EnthusiastsElderly Care Workers

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.

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https://hci.top/en/papers/chi/32555/2020

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DOI: https://doi.org/10.1145/3313831.3376536
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Source
CHI
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Year
2020
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Award
Honorable Mention
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Authors
2 authors
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Subtopics
Motor Impairment Assistive Input Technologies, Biosensors & Physiological Monitoring, Context-Aware Computing
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Professions
Physicians, Nurses & Clinicians, Athletes & Fitness Enthusiasts, Elderly Care Workers
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Content Status
Abstract only
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Related Papers
1 related papers