Abstract
Background The motor-assisted robotic stereotaxy system presents a compact and light-weight robotic system for stereotactic neurosurgery. Our system is designed to position probes in the human brain for various applications, for example, deep brain stimulation. It features five fully automated axes. High positioning accuracy is of utmost importance in robotic neurosurgery. Methods First, the key parameters of the robot's kinematics are determined using an optical tracking system. Next, the positioning errors at the center of the arc-which is equivalent to the target position in stereotactic interventions-are investigated using a set of perpendicular cameras. A modeless robot calibration method is introduced and evaluated. To conclude, the application accuracy of the robot is studied in a phantom trial. Results We identified the bending of the arc under load as the robot's main error source.Acalibration algorithmwas implemented to compensate for the deflection of the robot's arc. Themean error after the calibrationwas 0.26 mm, the 68.27th percentile was 0.32 mm, and the 95.45th was 0.50 mm. Conclusion The kinematic properties of the robot were measured, and based on the results an appropriate calibration methodwas derived.With mean errors smaller than currently used mechanical systems, our results show that the robot's accuracy is appropriate for stereotactic interventions.
| Original language | English |
|---|---|
| Journal | International Journal of Computer Assisted Radiology and Surgery |
| Volume | 7 |
| Issue number | 6 |
| Pages (from-to) | 911-920 |
| Number of pages | 10 |
| ISSN | 1861-6410 |
| DOIs | |
| Publication status | Published - 01.01.2012 |
Funding
Acknowledgments The authors would like to thank C. Dold and U. Albicker from inomed Medizintechnik GmbH for their collaboration in this project. This work is financially supported by the European Union and the State of Schleswig-Holstein (Centre of Excellence for Technology and Engineering in Medicine (TANDEM): grant no. 122-09-024).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 9 Industry, Innovation, and Infrastructure
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