Biomedical Engineering Reference
In-Depth Information
Fig. 3.3
Analysis of spatial modulation signal: (a) the time series above shows 5 ms of fluores-
cence intensity data. A particle is passing by the mask and its fluorescence signal is detected.
While the absolute fluorescence intensity is not higher than the background, a clear pattern can be
discerned. Therefore a typical threshold algorithm would fail to detect this particle. (b) Smoothened
FFT of Figure
3.3
a: The periodic signal from a particle passing a striped mask appears between
17 kHz and 40 kHz, depending upon the speed of the particle. Thus even a signal with low SNR still
results in a strong peak in the frequency domain. Additionally an envelope peak for the detection
duration of the particle occurs at a lower frequency. In Figure 3.3a, a particle is detected for
approximately 1 ms, resulting in an envelope peak at 1 kHz in the FFT spectrum
noise from the sensor and electronics (Fig.
3.3
) actually has power level decreasing
quite markedly with frequency. In this case, spatial modulation offers a great
advantage: by varying the width of the stripes in the mask, we can place the signal in
a higher frequency region and thereby improve the effective SNR by 10
or more.
The advantage is greatest for periodic signals of known frequency and long duration.
3.2.2.2
Varying Speeds of Particles
Our simple, low-cost, compact flow cytometer design moves complexity from
hardware to software by allowing the speed of particles to vary within the channel
and compensating for this variability computationally. The software computes the
