Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Microbial Biosensors

Microbial Biosensors

Microbial biosensors are analytical devices that utilize living microbes to detect specific substances through measurable signals. These devices consist of two main components: biosensing organisms and signal-transducing elements. Biosensing organisms, such as Escherichia coli or Saccharomyces cerevisiae, are typically housed in multiwell plates connected to transducers, enabling rapid, real-time detection of target analytes.Signal Generation MechanismWhen a target analyte—such as...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A Fiber-Optical Dosimetry Sensor for Gamma-Ray Irradiation Measurement in Biological Applications.

Biosensors·2023

Same journal

Biomechanical effects of defect size and location on vertebral fracture.

Journal of medical and biological engineering·2026

Same journal

Intradiscal pressure distributions in degenerated intervertebral discs: A biomechanical investigation.

Journal of medical and biological engineering·2026

Same journal

Machine Learning Approaches for Predicting Progression to Alzheimer's Disease in Patients with Mild Cognitive Impairment.

Journal of medical and biological engineering·2025

Same journal

Preliminary Results: Comparison of Convolutional Neural Network Architectures as an Auxiliary Clinical Tool Applied to Screening Mammography in Mexican Women.

Journal of medical and biological engineering·2025

Same journal

Multi-center Integrating Radiomics, Structured Reports, and Machine Learning Algorithms for Assisted Classification of COVID-19 in Lung Computed Tomography.

Journal of medical and biological engineering·2023

Same journal

Predicting the Severity of COVID-19 from Lung CT Images Using Novel Deep Learning.

Journal of medical and biological engineering·2023

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 30, 2026

Optical Trapping of Nanoparticles

Optical Trapping of Nanoparticles

Published on: January 15, 2013

An Optical Universal Plasmon-Based Biosensor for Virus ‎‎Detection.

Adel Shaaban^1,2, Yi-Chun Du^1,3

¹Department of Biomedical Engineering, National Cheng Kung University, Tainan, 704 Taiwan.

Journal of Medical and Biological Engineering

|June 26, 2023

Summary

This summary is machine-generated.

A new theoretical framework using a reformulated Fast Fourier Transform Beam Propagation Method (FFT-BPM) enhances surface plasmonic waveguide biosensor simulations. This approach offers reliable assessments for detecting biomaterial refractive index changes.

Keywords:

Biosensor Full width at half maximum (FWHM)Plasmonic waveguide Transfer matrix method (TMM)Waveguides

More Related Videos

Optical Detection of E. coli Bacteria by Mesoporous Silicon Biosensors

Optical Detection of E. coli Bacteria by Mesoporous Silicon Biosensors

Published on: November 20, 2013

Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor

Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor

Published on: February 16, 2018

Related Experiment Videos

Last Updated: Jun 30, 2026

Optical Trapping of Nanoparticles

Optical Trapping of Nanoparticles

Published on: January 15, 2013

Optical Detection of E. coli Bacteria by Mesoporous Silicon Biosensors

Optical Detection of E. coli Bacteria by Mesoporous Silicon Biosensors

Published on: November 20, 2013

Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor

Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor

Published on: February 16, 2018

Area of Science:

Optics and Photonics
Biomedical Engineering
Materials Science

Background:

Kretschmann configuration is a subwavelength framework for detecting refractive index changes in biomaterials.
Traditional assessments often rely on plane wave excitation transfer matrix methods (TMM), which may lack accuracy for complex simulations.
A more robust theoretical framework is needed for precise evaluation of plasmonic biosensors.

Purpose of the Study:

To adapt a reformulated Fast Fourier Transform Beam Propagation Method (FFT-BPM) for theoretical assessment of surface plasmonic waveguide biosensors.
To provide a more accurate and reliable simulation framework compared to the plane wave approximation.
To evaluate the performance characteristics of the proposed biosensor design.

Main Methods:

Excitation of surface plasmon mode using a sub-wavelength narrow light beam.
Utilizing the highly confined optical energy of the plasmonic mode for sensitive detection of analyte composition variations.
Electronic detection of plasmonic guided power via an optical MOS capacitor.

Main Results:

The guided plasmonic power was used to assess sensor performance.
Key characteristics evaluated include linearity, sensitivity, figure of merit, and full width at half maximum (FWHM).

Conclusions:

The proposed sensor offers integration with angular measurement systems (e.g., goniometers) or electronic detection.
This work is valuable for researchers and developers of sensitive biosensors, particularly when complex analysis tools are undesirable.