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February 2, 2026Advanced Functional Materials0 citations

Artificial Intelligence Powered Smart Multimodal Hand‐Wearable Systems for Healthcare and Human–Machine Interaction

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YSYutao SongYLYixiao LiYWYi Wang

Key Points

  • This review aims to explore how multimodal hand-wearable systems integrate AI for enhanced healthcare and human-machine interaction.
  • Review of advances in sensing materials and mechanisms
  • Examination of human-sensor interfaces
  • Discussion on AI-driven multimodal data fusion
  • Analysis of system integration in wearable technologies
  • Identified key materials and technologies enhancing multimodal functionality
  • Outlined potential frameworks for practical applications
  • Highlighted the role of AI in improving signal processing and decision-making

Abstract

ABSTRACT Hand‐wearable systems stand at the frontier of wearable electronics, leveraging the hand's intricate dexterity and rich physiological information for noninvasive, biocompatible healthcare monitoring and human–machine interaction (HMI). However, single‐modality constraints have highlighted the necessity for multimodal approaches. Through the convergence of advanced materials, multimodal sensing mechanisms, and artificial intelligence (AI), hand‐wearable systems are transforming into intelligent platforms capable of advanced signal processing, autonomous decision‐making, and adaptive interaction. This review systematically examines advancements in sensing materials, human–sensor interfaces, multimodal sensing mechanisms, system integration, and AI‐driven multimodal data fusion. A central focus is placed on the design and implementation of multimodal system architectures in healthcare monitoring and HMI. By synthesizing these advances and presenting a proposed framework, this review provides a comprehensive perspective to guide future research and accelerate the transition from laboratory prototypes to practical applications.

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Cite This Study

Song et al. (2026) studied this question.

synapsesocial.com/papers/6980fe68c1c9540dea810783https://doi.org/10.1002/adfm.202532014
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