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

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Authors: Yutao Song, Yixiao Li, Yi Wang, Chan Ye, Chenxin Zhu, Rong Yang
Cited by: 11
References: 151

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.

Fields of Study & Subjects

Advanced Sensor and Energy Harvesting Materials Hand Gesture Recognition Systems Emotion and Mood Recognition

Publication details

Journal / source
Advanced Functional Materials
Publisher
Wiley
Volume
36
Issue
36
Publication date
30 January 2026
Language
EN