Robot-assisted Transcranial Magnetic Stimulation (Robo-TMS): A Review

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 33; p. 1
• Main Authors: Bai, Wenzhi, Weightman, Andrew, O'Connor, Rory J, Ding, Zhengtao, Zhang, Mingming, Xie, Sheng Quan, Li, Zhenhong
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2025
• Subjects: Accuracy; Algorithms; Calibration; Coils; Collision avoidance; Equipment Design; Humans; Image-Guided Robotic Systems; Magnetic fields; Manipulators; Medical Robots; Neuronavigation; Neuronavigation - methods; Non-invasive Brain Stimulation; Optical Tracking Systems; Registration; Reviews; Robotics - instrumentation; Robotics - methods; Robots; Service robots; Transcranial magnetic stimulation; Transcranial Magnetic Stimulation - instrumentation; Transcranial Magnetic Stimulation - methods
• ISSN: 1534-4320; 1558-0210; 1558-0210
• DOI: 10.1109/TNSRE.2025.3585651

Transcranial magnetic stimulation (TMS) is a non-invasive and safe brain stimulation procedure with growing applications in clinical treatments and neuroscience research. However, achieving precise stimulation over prolonged sessions poses significant challenges. By integrating advanced robotics with conventional TMS, robot-assisted TMS (Robo-TMS) has emerged as a promising solution to enhance efficacy and streamline procedures. Despite growing interest, a comprehensive review from an engineering perspective has been notably absent. This paper systematically examines four critical aspects of Robo-TMS: hardware and integration; calibration and registration; neuronavigation systems; and control systems. We review state-of-the-art technologies in each area, identify current limitations, and propose future research directions. Our findings suggest that broader clinical adoption of Robo-TMS is currently limited by unverified clinical applicability, high operational complexity, and substantial implementation costs. Emerging technologies-including marker-less tracking, non-rigid registration, learning-based electric field (E-field) modelling, individualised magnetic resonance imaging (MRI) generation, robot-assisted multi-locus TMS (Robo-mTMS), and automated calibration and registration-present promising pathways to address these challenges.