AI 中文总结
本综述提出以人为中心的具身智能（HCEI）概念，引入感知-认知-执行-增强（PCAA）框架，整合多领域进展以指导软质可穿戴机器人向个性化、可预测的以人为中心方向发展。
AI 中文摘要
软质可穿戴机器人已从概念验证设备快速发展为用于康复、职业辅助和人类增强的有前景平台。随着该领域成熟，其核心挑战已超越开发更柔软的材料和更强大的执行器，延伸至将传感、智能和人类适应整合到用户可长时间舒适穿戴、信任并从中受益的系统中。这一转变催生了以人为中心的具身智能（Human-Centric Embodied Intelligence, HCEI）概念，其中智能源于耦合的人机系统，通过形态、多模态传感、自适应认知、柔顺执行及穿戴者自身生理与行为适应的交互而产生。为梳理这一视角，本综述引入感知-认知-执行-增强（Perception-Cognition-Actuation-Augmentation, PCAA）框架，将感知与认知定位为设计的主要驱动因素，推动开发超越传统的执行器优先范式。利用该框架，本综述整合了软材料、可穿戴传感、人工智能、执行、人机交互、数字孪生、临床转化、制造、监管及伦理等领域的进展，强调这些相互依赖的组件如何共同塑造长期个性化与实际部署。通过提供统一的概念框架与设计视角，本综述旨在指导未来研究、促进跨学科合作，并加速下一代软质可穿戴机器人向个性化、可预测且以人为中心的可穿戴智能的转化。
英文摘要
Soft wearable robots have evolved rapidly from proof-of-concept devices into promising platforms for rehabilitation, occupational assistance, and human augmentation. As the field matures, its central challenge extends beyond the development of softer materials and more capable actuators to the integration of sensing, intelligence, and human adaptation into systems that users can wear comfortably, trust, and benefit from over extended periods. This transition motivates the concept of Human-Centric Embodied Intelligence (HCEI), in which intelligence emerges from the coupled human-robot system through the interaction of morphology, multimodal sensing, adaptive cognition, compliant actuation, and the wearer's own physiological and behavioral adaptation. To organize this perspective, this review introduces the Perception-Cognition-Actuation-Augmentation (PCAA) framework, which positions perception and cognition as the primary drivers of design, shifting development beyond the conventional actuator-first paradigm. Using this framework, the review synthesizes advances in soft materials, wearable sensing, artificial intelligence, actuation, human-robot interaction, digital twins, clinical translation, manufacturing, regulation, and ethics, highlighting how these interdependent components collectively shape long-term personalization and real-world deployment. By providing a unified conceptual framework and design perspective, this review aims to guide future research, foster interdisciplinary collaboration, and accelerate the translation of next-generation soft wearable robots toward personalized, predictive, and human-centric wearable intelligence.
CommentsReview article; 48 pages, 6 figures, 4 tables, and 2 supplementary tables
