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Updated: Apr 13, 2026

Surgical Technique for Spinal Cord Delivery of Therapies: Demonstration of Procedure in Gottingen Minipigs

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Published on: December 7, 2012

Simulation-based Flexible Needle Control with Single-core FBG Feedback for Spinal Injections.

Yanzhou Wang¹, Yangsheng Xu², Jiarong Kang²

¹Department of Mechanical Engineering and Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, Maryland, USA.

IEEE Transactions on Medical Robotics and Bionics

|August 12, 2024

Summary

This summary is machine-generated.

This study introduces a novel framework for robot-assisted spinal injections, enabling precise needle control without continuous imaging. The system reconstructs needle shape and generates control inputs using real-time simulation and fiber optic sensors.

Keywords:

Medical robots Motion control Surgical robots

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Area of Science:

Robotics
Medical Devices
Biomedical Engineering

Background:

Robot-assisted spinal injections offer precision but often rely on continuous imaging.
Lack of imaging feedback poses challenges for complex needle steering and control.

Purpose of the Study:

To develop a general framework for simultaneous needle shape reconstruction and control input generation for robot-assisted spinal injections.
To enable accurate needle guidance without relying on continuous imaging feedback.

Main Methods:

A real-time needle-tissue interaction simulation generated system input-output mapping.
Single-core Fiber Bragg Grating (FBG) sensors provided local needle shape feedback within the simulation.
FBG wavelength shifts due to temperature were mitigated by exploiting fiber arrangement redundancy.

Main Results:

Targeting experiments on lumbar phantoms and ex vivo porcine tissue demonstrated low tip errors.
In-plane tip errors were achieved, along with total tip errors of and .

Conclusions:

The proposed control strategy and workflow are self-contained and independent of imaging guidance modality.
This approach is generalizable to other needle-based interventions requiring closed-loop control without reliable medical imaging.