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Updated: Feb 14, 2026
07:20
Stimulation Location Determination using a 3D Digitizer with High-Definition Transcranial Direct Current Stimulation
Published on: December 20, 2019
7.4K
Towards direct head navigation for robot-guided transcranial magnetic stimulation using 3D laserscans: Idea, setup
Lars Richter1, Ralf Bruder, Alexander Schlaefer
1Institute for Robotics and Cognitive Systems, University of Lübeck, 23538, Germany. richter@rob.uni-luebeck.de
Summary
This study introduces a novel 3D laser scanning method for precise direct head navigation in robotized transcranial magnetic stimulation (TMS) systems. Results demonstrate high accuracy, paving the way for improved robotic-guided TMS therapies.
Area of Science:
- Robotics
- Medical Imaging
- Neurosurgery
Background:
- Direct tracking offers superior robustness compared to marker-based methods.
- Accurate patient head positioning is critical for robotized transcranial magnetic stimulation (TMS) systems.
- 3D laser scanning provides dense surface point data for direct object tracking.
Purpose of the Study:
- To develop and evaluate a novel 3D laser scanning method for direct head navigation in robotized TMS.
- To assess the accuracy of the proposed system for precise coil placement on the patient's head.
Main Methods:
- Utilized a 3D laser scanner to acquire surface point data of the patient's head.
- Implemented a novel direct head navigation method within an industrial robot-controlled TMS system.
- Performed robot hand-eye calibration and compared scanned head data to reference images using Iterative Closest Point (ICP) algorithm.
Main Results:
- Achieved translational error < 2mm in robot hand-eye calibration.
- Demonstrated rotational error of 0.75° and scaling error < 0.001.
- Showcased sub-millimeter accuracy (< 0.2mm) in scanned head to reference image comparison via ICP.
Conclusions:
- Direct head navigation using 3D laser scanning is feasible for robotized TMS systems.
- The developed method shows high precision for robotic-guided coil placement.
- Future work should focus on optimizing computation time for real-time application.
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