banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
On noise processes and limits of performance in biosensors
Rent this article for


Image of FIG. 1.
FIG. 1.

Markov model for probabilistic motion in the reaction chamber. Each coordinate corresponds to a state of the process into which target analytes can move or from which they can leave. represents the location of the analyte particle at time , and defines the coordinates of the state in the system.

Image of FIG. 2.
FIG. 2.

Markov model for probabilistic capture in the reaction chamber. Only when the target analytes get into intimate proximity of the capturing probes (state 1) there is a probability of capturing denote by .

Image of FIG. 3.
FIG. 3.

Modification of association transition probability , due to probe saturation.

Image of FIG. 4.
FIG. 4.

Block diagram of different stages of a general biosensor platform. Various noise processes originating from different sources may corrupt the signal; however, all of these noise sources can be referred to as the number of analytes in the sample.

Image of FIG. 5.
FIG. 5.

Impedimetric biosensor where binding of analytes alters the impedance (or admittance ) between the fingers of an interdigitated electrode structure. The change in overall impedance corresponds to the amount of captured analytes.

Image of FIG. 6.
FIG. 6.

Detection circuitry for the impedimetric biosensor.

Image of FIG. 7.
FIG. 7.

Performance result of the impedimetric biosensor. In (a) the biosensor output signal is plotted vs the target analyte concentration. In (b) the SNR of the system is plotted and the DR is calculated for the of .

Image of FIG. 8.
FIG. 8.

Fluorescence-based biosensor where binding of labeled analytes is detected after the incubation phase. The emitted light from the fluorescent labels is detected by the photodiode connected to a charge integrating transimpedance amplifier (CTIA).

Image of FIG. 9.
FIG. 9.

Simulation result of fluorescence-based biosensor. In (a) the biosensor output signal is plotted vs the target analyte concentration. In (b) the SNR of the system is plotted and the DR is shown for the of . In (c) the SNR of the system is shown where the integration time (i.e., transduction gain) is increased by one order of magnitude while the photodetector dark-current noise power is decreased ten times.

Image of FIG. 10.
FIG. 10.

Noise figure (NF) of the biosensor platforms, where (a) is for the microfabricated impedimetric biosensor, (b) is for the fluorescence-based biosensor, and (c) is for the modified (low-noise) fluorescence-based biosensor.


Generic image for table
Table I.

Signal-to-noise ratio (SNR) and noise figure (NF) of biosensor systems when (a) only the target analyte is in the system, (b) the target analyte and the interfering species coexist in the system, and (c) when the system in addition has noisy amplification stages.

Generic image for table
Table II.

Characteristics of the impedimetric biosensor.

Generic image for table
Table III.

Characteristics of the fluorescence-based biosensor.


Article metrics loading...


Full text loading...

This is a required field
Please enter a valid email address
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: On noise processes and limits of performance in biosensors