Biomedical Engineering Reference
In-Depth Information
where
K
is Boltzmann's constant,
T
is the absolute temperature,
R
is the conductor resist-
ance, and
f
is the measurement bandwidth. The internal photodetector resistance and
load resistance are the major sources of thermal noise.
Applying noise analysis to biological systems tends to be more difficult due to their
inherent structural complexity, dynamic nature, and inhomogeneous properties. It is well
accepted that thermal noise, present in all physical systems, is the limiting factor in detec-
tion of weak signals. In biomaterials, thermal noise is a key contributor to the overall sys-
tem noise. When a proton channel within a cell membrane is in thermal equilibrium, it is
considered equivalent to a simple resistor (77). Although it has been reported that shot
noise also exists in biological systems, the mechanisms of generating such noise in biosys-
tems are far different from that of silicon-based devices. Shot noise in biological processes
is modeled as fluctuations of a variable (i.e., ion current), due to its discrete nature. When
significant energy flows into or out of a system (i.e., in cases where it is not in thermal
equilibrium with its environment), motion of the charged particle introduces shot noise
(78).
It has been widely observed that the electrical responses from both vertebrate and inver-
tebrate photoreceptors are accompanied by significant noise (79; 80). Signals carried by
light are noisy because there are variations in the rate at which photons are emitted. The
resultant fluctuations within biological phototransduction processes are recognized as
noise sources. There are three major noise categories under consideration herein (80; 81):
(1) photon-induced fluctuation. The observed signal, under the conditions of steady illu-
mination, is the superposition of all signals produced by every incident photon. Variation
in the rate of incoming photons and in their rate of absorption will produce noise. (2)
Discrete noise in darkness. In complete darkness, there is a low rate of events leading to
thermal isomerization. These events set the limits of performance in the detection of dim
flashes. (3) Continuous noise in darkness. It appears that thermal isomerizations of
rhodopsin and fluctuations in biochemical intermediates are the dominant fluctuations in
photoreceptors that have been exposed to darkness for prolonged periods of time (i.e.,
fully dark adapted). In the presence of moderate illumination levels, the dominant noise
source arises from photon fluctuations.
17.4.1.2 Signal-to-Noise Analysis in Bacteriorhodopsin Photoreceptor
In terms of the component parameters that comprise the photoreceptor, an analysis of the
SNR is important to optimize its performance. High SNR can be achieved by improving
photoreceptor fabrication, as well as front-end amplifier design. A general noise equiva-
lent circuit of a bR photoreceptor is shown in Figure 17.10. Five noise sources contribute
to the output signal: photoreceptor shot noise
V
iph
, photoreceptor thermal noise
V
Rm
,
amplifier current noise
V
in
, amplifier voltage noise
V
en
, and feedback thermal noise
V
Rf
.
I
ph
C
f
C
I
e
n
R
f
R
I
+
R
s
+
−
R
m
C
m
+
i
n
−
E
ph
(
t
)
FIGURE 17.10
Schematic representation of the simplified equivalent bR circuit used for noise analysis. This equivalent RC cir-
cuit shows one pixel with its amplifier and includes the different noise sources.
