Objective: This article presents the development and validation of a new robotic system for Transcranial Magnetic Stimulation (TMS), characterized by a new control approach, and an ad-hoc calibration methodology, specifically devised for the TMS application. Methods: The robotic TMS platform is composed of a 7 dof manipulator, controlled by an impedance control, and a camera-based neuronavigation system. The proposed calibration method was optimized on the workspace useful for the specific TMS application (spherical shell around the subject's head), and tested on three different hand-eye and robot-world calibration algorithms. The platform functionality was tested on six healthy subjects during a real TMS procedure, over the left primary motor cortex. Results: employing our method significantly decreases (p< 0.001) the calibration error by 34% for the position and 19% for the orientation. The robotic TMS platform achieved greater orientation accuracy than the expert operators, significantly reducing orientation errors by 46% (p< 0.001). No significant differences were found in the position errors and in the amplitude of the motor evoked potentials (MEPs) between the robot-aided TMS and the expert operators. Conclusion: The proposed calibration represents a valid method to significantly reduce the calibration errors in robot-aided TMS applications. Results showed the efficacy of the proposed platform (including the control algorithm) in administering a real TMS procedure, achieving better coil positioning than expert operators, and similar results in terms of MEPs. Significance: This article spotlights how to improve the performance of a robotic TMS platform, providing a reproducible and low-cost alternative to the few devices commercially available.

Development and Validation of a Novel Calibration Methodology and Control Approach for Robot-Aided Transcranial Magnetic Stimulation (TMS)

D'Alonzo M.;Pinardi M.;Di Pino G;Formica D.
2021-01-01

Abstract

Objective: This article presents the development and validation of a new robotic system for Transcranial Magnetic Stimulation (TMS), characterized by a new control approach, and an ad-hoc calibration methodology, specifically devised for the TMS application. Methods: The robotic TMS platform is composed of a 7 dof manipulator, controlled by an impedance control, and a camera-based neuronavigation system. The proposed calibration method was optimized on the workspace useful for the specific TMS application (spherical shell around the subject's head), and tested on three different hand-eye and robot-world calibration algorithms. The platform functionality was tested on six healthy subjects during a real TMS procedure, over the left primary motor cortex. Results: employing our method significantly decreases (p< 0.001) the calibration error by 34% for the position and 19% for the orientation. The robotic TMS platform achieved greater orientation accuracy than the expert operators, significantly reducing orientation errors by 46% (p< 0.001). No significant differences were found in the position errors and in the amplitude of the motor evoked potentials (MEPs) between the robot-aided TMS and the expert operators. Conclusion: The proposed calibration represents a valid method to significantly reduce the calibration errors in robot-aided TMS applications. Results showed the efficacy of the proposed platform (including the control algorithm) in administering a real TMS procedure, achieving better coil positioning than expert operators, and similar results in terms of MEPs. Significance: This article spotlights how to improve the performance of a robotic TMS platform, providing a reproducible and low-cost alternative to the few devices commercially available.
2021
calibration methodology
hand-eye and robot-world calibration
impedance control
neuronavigation
Robotic TMS
Calibration
Evoked Potentials, Motor
Humans
Neuronavigation
Robotics
Transcranial Magnetic Stimulation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/65242
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