An Image-Guided Robotic System for Transcranial Magnetic Stimulation: System Development and Experimental Evaluation
Yihao Liu, Jiaming Zhang, Letian Ai, Jing Tian, Shahriar Sefati, Huan, Liu, Alejandro Martin-Gomez, Amir Kheradmand, Mehran Armand

TL;DR
This paper presents an image-guided robotic system for transcranial magnetic stimulation that enhances placement accuracy and repeatability, validated through phantom and human studies showing significant improvements over manual methods.
Contribution
The work introduces a standardized planning protocol and a robotic system that significantly improves accuracy and repeatability in TMS coil placement compared to manual techniques.
Findings
Positional error halved by the robotic system
Rotational accuracy improved by up to two orders of magnitude
Repeatability increased with lower standard deviation in trials
Abstract
Transcranial magnetic stimulation (TMS) is a noninvasive medical procedure that can modulate brain activity, and it is widely used in neuroscience and neurology research. Compared to manual operators, robots may improve the outcome of TMS due to their superior accuracy and repeatability. However, there has not been a widely accepted standard protocol for performing robotic TMS using fine-segmented brain images, resulting in arbitrary planned angles with respect to the true boundaries of the modulated cortex. Given that the recent study in TMS simulation suggests a noticeable difference in outcomes when using different anatomical details, cortical shape should play a more significant role in deciding the optimal TMS coil pose. In this work, we introduce an image-guided robotic system for TMS that focuses on (1) establishing standardized planning methods and heuristics to define a…
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Taxonomy
TopicsTranscranial Magnetic Stimulation Studies · EEG and Brain-Computer Interfaces
