Mei Chen-PhD defense - Department of Electrical and Systems ...

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Department of Electrical and Systems Engineering




LASER DOPPLER VIBROM
ETRY MEASURES OF PHY
SIOLOGICAL FUNCTION:

EVALUATION OF BIOMET
RIC CAPABILITIES


DISSERTATION DEFENSE

b
y

Mei Chen

PhD Candidate

Department of Elec
trical and Systems Engineering

Washington University in St. Louis


Due to increasing requirements for security, the application and importance of biometrics is growing at a rapid pace. Biometr
ics is the science of
using physiological or behavioral charact
eristics to determine or verify attributes of a person, including identity. Fingerprints, iris scans, face images,
and retina scans are examples of measurements of physiological characteristics that have been proposed and are being used as
biometrics. Gait

and
signature are two primarily behavioral characteristics that have been explored for their use as biometrics. More biometric sy
stems are under
development as current biometric technologies satisfy those attributes with mixed success. In biometric recog
nition, two key properties for useful
biometrics are their ability to distinguish among individuals and their stability over time.


A novel approach of measuring carotid pulse signals via a laser Doppler vibrometer remotely is proposed. Laser Doppler Vibro
metry (LDV) is used
to sense vibration on the surface of the skin above the carotid artery. This motion is related to arterial wall movements ass
ociated with the central
blood pressure pulse. The non
-
contact basis of the LDV method has several potential be
nefits related to non
-
intrusiveness. To enhance the technical
quality of the laser signal during this developmental effort, a small patch (1 cm2) of reflective tape was affixed to the rec
ording site.


The biometric capabilities of Laser Doppler Vibrometry
(LDV) signals are evaluated. Several recognition 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 inter
-
session basis involving
testing repeated a
fter delays of 1 week to 6 months. A waveform decomposition method that utilizes principal component analysis is used to mode
l
the signal in the time domain. Authentication testing for this approach produces an equal
-
error rate (EER) of 0.5% for intra
-
sess
ion 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 to train models using data from multiple sessions. As currently impl
emented, this approach
yields an inter
-
session EER of 6.3%.


LDV biometric perfor
mance under moderate exercise is tested. A protocol is set up to produce changes in heart rate by physical exercise.
Spectrogram based approaches are applied with an EER of 3.6% for inter
-
state tests, indicating that the LDV pulse signal is stable after mo
derate
physical exercise. The performance degrades during exercise, but improves within 30 seconds as the heart rate recovers during

the rest period. The
results suggest that the variability caused by heart rate fluctuations and respiration changes decreas
es within a short time.







DATE:


Friday
,
September 11
, 2009




TIME:


12:00 p
.m.





PLACE:




Bryan Hall, Room 305




Dissertation

advisor:

Dr.
Joseph O’Sullivan

This seminar is in partial fulfillment

of

the Doctor of Philosophy

degree