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

TL;DR

This review discusses the integration of robotics with transcranial magnetic stimulation (TMS), highlighting current technologies, limitations, and future directions to improve precision, efficiency, and clinical adoption.

Contribution

It provides a comprehensive engineering perspective on Robo-TMS, reviewing state-of-the-art systems, identifying challenges, and proposing future research avenues.

Findings

Broader clinical adoption is limited by unverified applicability and high costs.

Emerging technologies like marker-less tracking and learning-based modeling offer promising solutions.

Automation and individualized approaches can enhance Robo-TMS effectiveness.

Abstract

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.