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Related Experiment Video

Updated: Jul 29, 2025

Fabrication of Fine Electrodes on the Tip of Hypodermic Needle Using Photoresist Spray Coating and Flexible Photomask for Biomedical Applications

Fabrication of Fine Electrodes on the Tip of Hypodermic Needle Using Photoresist Spray Coating and Flexible Photomask for Biomedical Applications

Published on: November 28, 2017

Needle-Based Electrical Impedance Imaging Technology for Needle Navigation.

Jan Liu¹, Ömer Atmaca^1,2, Peter Paul Pott¹

¹Institute of Medical Device Technology, University of Stuttgart, 70569 Stuttgart, Germany.

Bioengineering (Basel, Switzerland)

|May 27, 2023

Summary

This study introduces a novel needle-based electrical impedance imaging system for guiding medical procedures. The system shows promise as an alternative to ultrasound, classifying tissues with 70.56% accuracy.

Keywords:

bioimpedance electrical impedance imaging impedance measurements needle navigation tissue classification

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Last Updated: Jul 29, 2025

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Published on: April 21, 2013

Area of Science:

Biomedical Engineering
Medical Imaging
Electrical Impedance Tomography

Background:

Needle insertion procedures like biopsies and treatments require accurate guidance.
Current ultrasound imaging has limitations in spatial resolution and interpretation.
A new needle-based electrical impedance imaging system is proposed as an alternative.

Purpose of the Study:

To develop and evaluate a needle-based electrical impedance imaging system for tissue classification.
To assess the feasibility of this system as an alternative to conventional imaging techniques.
To visualize tissue types in 3D using impedance measurements.

Main Methods:

A modified needle with 12 electrodes was used for impedance measurements.
Finite Element Method (FEM) simulations determined needle sensitivity volumes.
A k-Nearest Neighbors (k-NN) algorithm classified tissue phantoms.
A MATLAB Graphical User Interface (GUI) provided control and visualization.

Main Results:

The system achieved an average tissue classification success rate of 70.56%.
Fat tissue phantom classification was highly successful (100% accuracy).
Layered tissue structures presented lower classification success rates.
Average latency between measurement and 3D visualization was 112.1 ms.

Conclusions:

Needle-based electrical impedance imaging is a feasible alternative to conventional methods.
The developed system can classify tissues and provide 3D visualization.
Further hardware, algorithm, and usability improvements are needed for clinical application.