Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 25, 2025

Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets
06:12

Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets

Published on: March 17, 2023

1.4K

Integrated LSPR Biosensing Signal Processing Strategy and Visualization Implementation.

Mixing Zhou1, Zhaoxin Geng1,2

  • 1School of Information Engineering, Minzu University of China, Beijing 100081, China.

Micromachines
|May 25, 2024
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Solution-Processed ReS<sub>2</sub>/FAPbI<sub>3</sub>/p-Si Dual Type-II van der Waals Heterojunctions for Ultrahigh Modulation Depth and Humidity-Resistant Terahertz Modulators.

ACS applied materials & interfaces·2026
Same author

A Route to the Colorimetric Detection of Alpha-Fetoprotein Based on a Smartphone.

Micromachines·2024
Same author

A Flexible Terahertz Metamaterial Biosensor for Cancer Cell Growth and Migration Detection.

Micromachines·2022
Same author

Route to Cost-Effective Fabrication of Wafer-Scale Nanostructure through Self-Priming Nanoimprint.

Micromachines·2021
Same author

A Potential Plasmonic Biosensor Based Asymmetric Metal Ring Cavity with Extremely Narrow Linewidth and High Sensitivity.

Sensors (Basel, Switzerland)·2021
Same author

Label-Free Exosome Detection Based on a Low-Cost Plasmonic Biosensor Array Integrated with Microfluidics.

Langmuir : the ACS journal of surfaces and colloids·2019
Same journal

Correction: Kang et al. Fluid Flow to Electricity: Capturing Flow-Induced Vibrations with Micro-Electromechanical-System-Based Piezoelectric Energy Harvester. <i>Micromachines</i> 2024, <i>15</i>, 581.

Micromachines·2026
Same journal

Femtosecond Laser Texturing of Wood Coatings with Bio-Based Epoxy and Wax Additives for Enhanced Hydrophobicity.

Micromachines·2026
Same journal

Engineering of Optoelectronic Devices for Renewable Energy Applications.

Micromachines·2026
Same journal

Phase Transformation and Electrochemical Behavior of Hexagonal TiO<sub>2</sub> Nanotubes Under Different Annealing Temperatures and Heating Rates.

Micromachines·2026
Same journal

Process Optimization and Predictive Modeling of Femtosecond Laser Precision Milling for Commercial PMMA Slices.

Micromachines·2026
Same journal

A Hybrid Preprocessing Multi-Objective Surrogate Model for Thermal MEMS Actuators.

Micromachines·2026
See all related articles

A new software tool enhances localized surface plasmon resonance (LSPR) biosensing by providing universal signal processing and self-verification. This innovation boosts precision and cost-effectiveness for disease marker identification in nanophotonics.

Area of Science:

  • Nanophotonics
  • Biochemical Sensing
  • Biosensor Technology

Background:

  • Localized Surface Plasmon Resonance (LSPR) biosensor chips are valuable for disease marker identification in labs.
  • Clinical application of LSPR biosensors is limited due to a lack of universal signal processing tools.
  • Enhanced precision and self-verification are needed for LSPR biochemical sensors.

Purpose of the Study:

  • To introduce a novel visual LSPR sensor software for real-time spectral processing.
  • To enable optimization of signal processing and incorporate self-verification in LSPR biosensing.
  • To address the need for a universal, precise, and cost-effective solution in nanophotonic sensing.

Main Methods:

  • The software processes real-time transmission or reflection spectra from LSPR biosensors.
Keywords:
LSPR biosensorfigure of meritintegrated softwaresensitivityspectral analysis

More Related Videos

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions
09:09

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Published on: November 23, 2015

8.6K
Surface Enhanced Raman Spectroscopy Detection of Biomolecules Using EBL Fabricated Nanostructured Substrates
11:44

Surface Enhanced Raman Spectroscopy Detection of Biomolecules Using EBL Fabricated Nanostructured Substrates

Published on: March 20, 2015

20.3K

Related Experiment Videos

Last Updated: Jun 25, 2025

Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets
06:12

Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets

Published on: March 17, 2023

1.4K
A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions
09:09

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Published on: November 23, 2015

8.6K
Surface Enhanced Raman Spectroscopy Detection of Biomolecules Using EBL Fabricated Nanostructured Substrates
11:44

Surface Enhanced Raman Spectroscopy Detection of Biomolecules Using EBL Fabricated Nanostructured Substrates

Published on: March 20, 2015

20.3K
  • It captures structural changes at the nanostructure interface and computes key parameters like resonance wavelength shift and sensitivity.
  • Users can customize processing algorithms and benefit from robust result validation.

    • Main Results:

    • The software computes resonance wavelength shift, full width at half maximum, sensitivity, and quality factor.
    • It offers tailored processing algorithms for diverse data capture sessions.
    • The system navigates nanostructure morphology complexities and validates results effectively.

    Conclusions:

    • The visual LSPR sensor software represents a significant advancement in nanophotonics and high-throughput LSPR biosensing.
    • It enhances reliability, efficiency, and cost-effectiveness in biochemical detection.
    • This user-centric innovation simplifies complexity for researchers and practitioners in nanophotonic sensing technology.