<p>The evolution of rehabilitation aids from passive mechanical devices to intelligent systems is reshaping human motor function recovery. However, traditional orthoses often lack adaptability and comfort, highlighting the need for advanced material solutions. This review systematically explores the role of Shape Memory Textile Composites (SMTCs) in limb orthotics, bridging material science with clinical rehabilitation. We first analyze biomechanical regulation strategies for distinct limb deformities to establish design requirements. Subsequently, we discuss how SMTCs leverage advanced resin matrices and intelligent textile structures to resolve the inherent conflict between mechanical support and physiological compliance, emphasizing their environmental adaptability and active responsiveness. Furthermore, we propose a closed loop rehabilitation paradigm that integrates multi source sensing with artificial intelligence algorithms. The study concludes that fusing SMTCs with intelligent systems facilitates a transition from passive support to active neural remodeling, offering a critical pathway for next generation precision rehabilitation ecosystems.</p> Graphical Abstract <p></p>

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Shape memory smart textile composites open a new era of human limb function rehabilitation: principles, design and applications

  • Jichen Li,
  • Jia-Horng Lin,
  • Yexiong Qi,
  • Huan Guo,
  • Ching-Wen Lou

摘要

The evolution of rehabilitation aids from passive mechanical devices to intelligent systems is reshaping human motor function recovery. However, traditional orthoses often lack adaptability and comfort, highlighting the need for advanced material solutions. This review systematically explores the role of Shape Memory Textile Composites (SMTCs) in limb orthotics, bridging material science with clinical rehabilitation. We first analyze biomechanical regulation strategies for distinct limb deformities to establish design requirements. Subsequently, we discuss how SMTCs leverage advanced resin matrices and intelligent textile structures to resolve the inherent conflict between mechanical support and physiological compliance, emphasizing their environmental adaptability and active responsiveness. Furthermore, we propose a closed loop rehabilitation paradigm that integrates multi source sensing with artificial intelligence algorithms. The study concludes that fusing SMTCs with intelligent systems facilitates a transition from passive support to active neural remodeling, offering a critical pathway for next generation precision rehabilitation ecosystems.

Graphical Abstract