Paper
5 May 2009 Laser Doppler vibrometry measures of physiological function: evaluation of biometric capabilities
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Abstract
A novel approach using mechanical physiological activity as a biometric marker is described. Laser Doppler Vibrometry is used to sense activity in the region of the carotid artery, related to arterial wall movements associated with the central blood pressure pulse. The non-contact basis of the LDV method has several potential benefits in terms of the associated non-intrusiveness. Several methods are proposed that use the temporal and/or spectral information in the signal to assess biometric performance both on an intra-session basis, and on an intersession basis involving testing repeated after delays of 1 week to 6 months. A waveform decomposition method that utilizes principal component analysis is used to model the signal in the time domain. Authentication testing for this approach produces an equal-error rate of 0.5% for intra-session testing. However, performance degrades substantially for inter-session testing, requiring a more robust approach to modeling. Improved performance is obtained using techniques based on time-frequency decomposition, incorporating a method for extracting informative components. Biometric fusion methods including data fusion and information fusion are applied in multi-session data training model. As currently implemented, this approach yields an inter-session equal-error rate of 9%.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mei Chen, Joseph A. O'Sullivan, Naveen Singla, Erik J. Sirevaag, and John W. Rohrbaugh "Laser Doppler vibrometry measures of physiological function: evaluation of biometric capabilities", Proc. SPIE 7306, Optics and Photonics in Global Homeland Security V and Biometric Technology for Human Identification VI, 730623 (5 May 2009); https://doi.org/10.1117/12.818283
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Cited by 7 scholarly publications.
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KEYWORDS
Laser Doppler velocimetry

Biometrics

Data modeling

Time-frequency analysis

Data fusion

Electrocardiography

Doppler effect

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