用机器人提升脑刺激精度，解决传统TMS操作难、不精准的痛点。
Robot-assisted Transcranial Magnetic Stimulation (Robo-TMS): A Review
- 将机器人与TMS结合，实现高精度、长时间稳定刺激。
- 现有系统存在临床效果未验证、操作复杂、成本高等问题。
- 适合神经工程、康复医疗及脑机接口研究者参考。
经颅磁刺激（TMS）是一种非侵入性且安全的大脑刺激技术，在临床治疗和神经科学研究中应用日益广泛。然而，长时间精准刺激面临重大挑战。通过将先进机器人技术与传统TMS相结合，机器人辅助经颅磁刺激（Robo-TMS）成为提升疗效和简化流程的有前景方案。尽管兴趣增长，但缺乏从工程角度的全面综述。本文系统分析了Robo-TMS的四个关键方面：硬件与集成、校准与配准、神经导航系统和控制系统。回顾各领域前沿技术，识别当前局限，并提出未来研究方向。研究发现，Robo-TMS更广泛临床应用受限于未经验证的临床适用性、高操作复杂度和高昂实施成本。新兴技术如无标记追踪、非刚性配准、基于学习的电场（E-field）建模、个性化MRI生成、机器人辅助多部位刺激（Robo-mTMS）以及自动化校准与配准，为突破这些瓶颈提供了潜在路径。
原文摘要 · Abstract (English)
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.
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