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Characterizing an electronic–robotic targeting platform for precise and fast brain stimulation with multi-locus transcranial magnetic stimulation

Renan H. Matsuda, Victor H. Souza, Thais C. Marchetti, Ana M. Soto, Olli‐Pekka Kahilakoski, Mikael Laine, Heikki Sinisalo, Dubravko Kičić, Pantelis Lioumis, Risto J. Ilmoniemi, Oswaldo Baffa

Year
2024
Citations
5
Access
Open access

Abstract

1. Abstract Background Multi-locus TMS (mTMS) enables precise electronic control of brain stimulation targeting, eliminating the need for physical coil movement. However, with a small number of coils, the stimulation area is constrained, and manually handling the coil array is cumbersome. Combining electronic mTMS targeting with robotics will enable automated, user-independent, and precise brain stimulation protocols. Objective Characterizing an open-source electronic–robotic mTMS platform for rapid and accurate brain stimulation targeting. Methods We developed an automated robotic mTMS positioning platform. The accuracy of the system was quantified with a TMS characterizer that measures the TMS-induced electric field on a spherical cortex model. We used a 5-coil mTMS device equipped with a set of five coils coupled to a collaborative robot. The induced electric-field distortion generated by robot coupling was evaluated for each coil. We compared the accuracy of robotic–electronic targeting by repositioning the mTMS coil set with the robotic and the conventional manual positioning. Results Our collaborative robot-based system offers submillimeter precision and autonomy in positioning mTMS coil sets. The electronic–robotic mTMS platform was approximately 1.8 mm and 1.0° more accurate than the conventional manual positioning. Integrating robotics and mTMS automates brain stimulation procedures, resulting in minimal reliance on user expertise and subjective analysis. Conclusion Our open-source platform combining rapid mTMS targeting with robotic precision enhances the safety and reproducibility of brain stimulation techniques, enabling more efficient and reliable outcomes than previous techniques.

Keywords

Electromagnetic coilTranscranial magnetic stimulationRoboticsRobotArtificial intelligenceComputer scienceBrain stimulationStimulationEngineeringNeuroscience

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