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Related Experiment Video

Updated: Feb 10, 2026

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Biometric Authentication Using the PPG: A Long-Term Feasibility Study.

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  • 1Aragón Institute of Engineering Research (I3A), University of Zaragoza, 50018 Zaragoza, Spain. jslarraz@unizar.es.

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|May 13, 2018
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Summary

Photoplethysmogram (PPG) signals show potential for long-term biometric authentication. While stable error rates are achievable, performance degrades in real-world conditions and over time, impacting reliability.

Keywords:
Manhattan distanceauthenticationbiometricslong-termmulti-cycle templatephotoplethysmogram (PPG)

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Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Biometrics

Background:

  • Photoplethysmogram (PPG) signals measure peripheral blood flow changes.
  • PPG's utility in biometric authentication remains inconclusive despite recent research.
  • Long-term feasibility of PPG for biometrics requires further investigation.

Purpose of the Study:

  • To analyze the long-term feasibility of using PPG signals for biometric authentication.
  • To evaluate the stability of performance metrics like False Match Rate (FMR) and False Non-Match Rate (FNMR).
  • To assess the impact of varying recording conditions and time intervals on biometric performance.

Main Methods:

  • Utilized time-domain and Karhunen-Loève transform feature extractors.
  • Employed Manhattan and Euclidean distances for matching metrics.
  • Tested performance across four PPG databases: PRRB, MIMIC-II, Berry, and Nonin.

Main Results:

  • Demonstrated constant FMR and FNMR values over time for a selected threshold, crucial for authentication.
  • Achieved Equal Error Rate (EER) from 1.0% (controlled) to 8% (real-world) within the same session.
  • Observed significant performance degradation, with EER reaching 23.2% for signals recorded on different days.

Conclusions:

  • PPG signals offer a stable basis for biometric authentication under consistent conditions.
  • Real-world application and long-term use are challenged by performance variability and degradation over time.
  • Further research is needed to mitigate performance drops in diverse and longitudinal scenarios.