Biomedical Engineering Reference
In-Depth Information
predefined pattern for optical transmission. Correlating the detected signal with the
known pattern achieves high discrimination of the particle signal from background
noise. In conventional flow cytometry, the size of the excitation area is restricted to
approximately the size of the particle. With the spatial modulation technique, a large
excitation area (ca. 0:1
1 mm) is used to increase the total flux of fluorescence
light that originates from a particle. Despite the large excitation area, the mask
pattern enables high spatial resolution which permits independent detection and
characterization of near-coincident particles, with a separation (in the flow direction)
that can approach the dimension of individual particles. In addition, the concept is
intrinsically tolerant to background fluorescence originating from constituents in
solution, the materials of the fluidic structures, or contaminants on surfaces.
To apply the spatially modulated fluorescence emission technique to particles
moving through a fluid channel, a spatially patterned mask modulates the intensity
of the fluorescent light incident on the photo detector over a large excitation area
as illustrated in Fig. 3.1 . The time dependence of the signal is defined by the spatial
structure of the stripes of the mask and the speed of the particle. The recorded signal
is analyzed by correlation techniques, and the intensity and time when the particle
traverses the detection zone are accurately calculated. With state-of-the-art real-time
correlation techniques, characterization for particle speeds up to a few meters per
second is possible. The correlation analysis not only allows for very sensitive and
reliable particle detection, but it also reveals the speed of each particle (see Fig. 3.1 )
which ultimately enables simple fluidic handling and true volumetric determination
of the analyte. The basic concept, its lab implementation, and first proof-of-concept
demonstration are described in [ 29 ]. The correlation analysis is described below
in Sect. 3.2.2 , and applications of the spatial modulation technique for detection
bioparticles are presented in Sects. 3.2.3 , 3.3 ,and 3.4 .
3.2.2
Data Evaluation and Correlation Analysis
The data analysis relies on the concept of a matched filter. A matched filter correlates
a known model signal, or template, with the stream of sensor data in order to detect
the presence of the model signal within the stream. The mathematical operation
computes the dot product of the template, T
D
.T 1 ;T 2 ; :::; T n /, with the time
series, t 1 ,t 2 , ..., at each possible position j, that is, we compute D j D P i T i :t j C i ,
for each choice of j, and then declare a detection whenever D j exceeds some
threshold chosen to balance the two types of errors, false positives and false
negatives. The template may be a theoretical pattern or, as shown in Fig. 3.2 ,
derived from previously detected signals. As a speedup, we can compute D j for
many choices of j at once using the fast Fourier transform (FFT) to compute a
convolution, rather than separately computing D j for each choice of j. The matched
filter technique, which dates back to World War II applications in radar and sonar,
is a mathematically optimal detector for well-separated signals with additive white
Gaussian noise. The technique can detect signals at remarkably low signal-to-noise
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