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Difference from Background: Limit of Detection

Difference from Background: Limit of Detection

The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...

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Related Experiment Video

Updated: May 1, 2026

Attaching Biological Probes to Silica Optical Biosensors Using Silane Coupling Agents

Attaching Biological Probes to Silica Optical Biosensors Using Silane Coupling Agents

Published on: May 1, 2012

Optimizing detection limits in whispering gallery mode biosensing.

Matthew R Foreman, Wei-Liang Jin, Frank Vollmer

|March 26, 2014

Summary

This summary is machine-generated.

This study analyzes biosensor detection limits using the Cramér-Rao lower bound, considering various noise types. Slightly under-coupled cavities offer superior sensitivity for biosensing applications.

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Last Updated: May 1, 2026

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Area of Science:

Photonics
Biosensing
Theoretical Physics

Background:

Whispering gallery mode (WGM) biosensors offer high sensitivity.
Understanding detection limits is crucial for biosensor development.
Technical noise sources can limit biosensor performance.

Purpose of the Study:

To theoretically analyze detection limits in swept-frequency WGM biosensing.
To derive measurement acuity factors considering different noise profiles.
To compare sensitivity of resonance shift and broadening modalities.

Main Methods:

Application of the Cramér-Rao lower bound (CRLB).
Derivation of acuity factors for uncoloured and 1/f Gaussian noise.
Consideration of frequency fluctuations (laser jitter, thermorefractive noise).
Use of the asymptotic Fisher information matrix for arbitrary coloured noise.

Main Results:

Acuity factors were derived for various noise conditions.
Detection sensitivity was quantified for resonance shift and broadening.
Slightly under-coupled cavities were identified as optimal.
Under-coupled cavities outperform critically and over-coupled ones.

Conclusions:

Theoretical framework established for WGM biosensor detection limits.
Noise characterization is essential for optimizing biosensor performance.
Cavity coupling significantly impacts biosensing sensitivity, with under-coupling being advantageous.