Surface plasmon resonance biosensors measure the thickness or molecular con
centration of a biolayer by analyzing small changes in measured reflection
spectra. In this paper, we describe linear spectral analysis techniques des
igned to produce measurements with the maximum possible signal-to-noise rat
io. We show how, under appropriate assumptions, an optimal analysis method
may be derived for measuring any system parameter, and how measurements of
multiple parameters may be made independent in exchange for an decrease in
signal to noise ratio. Compared to two conventional data analysis technique
s (quadratic fit and centroid methods) using simulated data, the linear tec
hniques show a 30% increase in signal to noise ratio. In application to act
ual thiol binding data, the linear method yields a signal to noise ratio 46
% greater than that of the centroid method and 65% greater than that of the
quadratic fit method. This level of noise reduction was achieved by using
the ability of the linear methods to reject noise caused by light source br
ightness variations. (C) 1999 Elsevier Science S.A. All rights reserved.