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Related Experiment Video

Updated: Nov 1, 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

Trajectory Generation of FBG-Sensorized Needles for Insertions into Multi-Layer Tissue.

Dimitri A Lezcano¹, Iulian I Iordachita¹, Jin Seob Kim¹

¹Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.

Proceedings of IEEE Sensors. IEEE International Conference on Sensors

|June 21, 2021

Summary

This summary is machine-generated.

This study introduces a new method for flexible needle trajectory generation, enabling complex curvatures in multi-layer tissue. The approach combines sensor data with elastic rod mechanics for accurate shape prediction.

Keywords:

FBG flexible needle mathematical model needle motion planning tissue inhomogeneity

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Last Updated: Nov 1, 2025

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Area of Science:

Robotics
Medical Device Engineering
Biomedical Engineering

Background:

Accurate prediction of flexible needle shape is crucial for minimally invasive surgery.
Existing models struggle with complex needle curvatures, especially in multi-layer tissues.

Purpose of the Study:

To develop and evaluate a novel method for flexible needle trajectory generation.
To enable accurate prediction of complex needle shapes in multi-layer tissue environments.

Main Methods:

A new model combining fiber Bragg grating (FBG) sensor measurements with inextensible elastic rod mechanics for shape-sensing.
Evaluation of the method in both single- and double-layer isotropic tissue models.

Main Results:

The proposed method successfully generates trajectories for flexible needles with complex curvatures.
Demonstrated validity in predicting needle shape within different tissue layers.

Conclusions:

The developed method offers a significant advancement in flexible needle trajectory generation.
This approach accounts for complex curvatures, improving prediction accuracy in challenging tissue environments.