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Bode Plots Construction01:24

Bode Plots Construction

The Bode plot is an essential tool in control system analysis, mapping the frequency response of a system through a magnitude plot and a phase plot, both against a logarithmic frequency axis. To construct a Bode plot, consider the transfer function H(ω):

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Related Experiment Video

Updated: May 25, 2026

Measuring Changes in Brain Endothelial Barrier Integrity with Two Impedance-based Biosensors in Response to Cancer Cells and Cytokines
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Measuring Changes in Brain Endothelial Barrier Integrity with Two Impedance-based Biosensors in Response to Cancer Cells and Cytokines

Published on: September 22, 2023

An improved algorithm for quantifying real-time impedance biosensor signals.

Dean S Messing1, Andrey Ghindilis, Kevin Schwarzkopf

  • 1Sharp Laboratories of America, 5750 NW Pacific Rim Blvd, Camas, Washington 98607, USA. deanm@sharplabs.com

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 19, 2012
PubMed
Summary
This summary is machine-generated.

This study enhances an electrochemical impedance biosensor by refining its signal quantification algorithm. New constraints improve reliability and repeatability, paving the way for real-world deployment.

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Last Updated: May 25, 2026

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Published on: October 5, 2019

Area of Science:

  • Biomedical Engineering
  • Electrochemical Sensing
  • Signal Processing

Background:

  • A previously developed real-time electrochemical impedance biosensor prototype system utilized a state-space estimation algorithm for signal quantification.
  • Subsequent experiments identified algorithm failure modes that compromised quantification reliability and repeatability.

Purpose of the Study:

  • To address the identified failure modes and enhance the biosensor system's performance.
  • To improve the reliability and repeatability of signal quantification in electrochemical impedance biosensors.

Main Methods:

  • Development of a modified state-space estimation algorithm incorporating constraints.
  • Integration of a priori knowledge of expected signals derived from the biosensor signal model into the algorithm.
  • Validation of the enhanced algorithm through experimental testing.

Main Results:

  • The refined algorithm significantly improved the reliability and repeatability of signal quantification.
  • The constrained algorithm demonstrated enhanced robustness compared to the previous version.
  • The system's performance is now nearing readiness for real-world trials.

Conclusions:

  • The integration of model-based constraints into the state-space algorithm is effective in overcoming previous limitations.
  • The enhanced electrochemical impedance biosensor system shows high potential for reliable real-world applications.
  • Further development is focused on preparing the system for practical deployment and validation.