用AI驱动可穿戴系统，实现个性化健康管理。
Artificial Intelligence-driven Intelligent Wearable Systems: A full-stack Integration from Material Design to Personalized Interaction
- 构建人机共生健康智能框架，融合多模态传感与边缘云协同计算。
- 通过强化学习和数字孪生实现动态干预，支持个体差异自适应。
- 适合医疗健康、可穿戴设备研发人员关注，推动主动预防型医疗。
智能可穿戴系统是精准医疗的前沿，对提升人机交互至关重要。传统设备受限于经验性材料设计和基础信号处理。为此，我们提出人机共生健康智能（HSHI）框架，整合多模态传感器网络、边缘-云协同计算，以及数据与知识混合建模。该框架能动态适应个体间与个体内的差异，将健康管理从被动监测转向主动协同演化。HSHI通过AI优化材料与微结构，实现多模态信号鲁棒解析，并融合群体洞察与个性化调整的双重机制。结合强化学习闭环优化与数字孪生，支持定制化干预与反馈。总体而言，HSHI标志着医疗范式转变，迈向以预防、适应性及技术-健康和谐关系为核心的新模式。
原文摘要 · Abstract (English)
Intelligent wearable systems are at the forefront of precision medicine and play a crucial role in enhancing human-machine interaction. Traditional devices often encounter limitations due to their dependence on empirical material design and basic signal processing techniques. To overcome these issues, we introduce the concept of Human-Symbiotic Health Intelligence (HSHI), which is a framework that integrates multi-modal sensor networks with edge-cloud collaborative computing and a hybrid approach to data and knowledge modeling. HSHI is designed to adapt dynamically to both inter-individual and intra-individual variability, transitioning health management from passive monitoring to an active collaborative evolution. The framework incorporates AI-driven optimization of materials and micro-structures, provides robust interpretation of multi-modal signals, and utilizes a dual mechanism that merges population-level insights with personalized adaptations. Moreover, the integration of closed-loop optimization through reinforcement learning and digital twins facilitates customized interventions and feedback. In general, HSHI represents a significant shift in healthcare, moving towards a model that emphasizes prevention, adaptability, and a harmonious relationship between technology and health management.
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