<br>高性能水凝胶传感器实现多模式、精确的人机交互系统，实现主动康复,Advanced Materials

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高性能水凝胶传感器实现多模式、精确的人机交互系统，实现主动康复
Advanced Materials ( IF 27.4 ) Pub Date : 2023-12-14 , DOI: 10.1002/adma.202309868
Hao Wang ₁ , Qiongling Ding ₁ , Yibing Luo ₁ , Zixuan Wu ₁ , Jiahao Yu ₂ , Huizhi Chen _{3,

4} , Yubin Zhou _{3,

4} , He Zhang ₅ , Kai Tao ₂ , Xiaoliang Chen ₆ , Jun Fu ₇ , Jin Wu _{1,

5,

8}

Affiliation

State Key Laboratory of Optoelectronic Materials and Technologies and the Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, 510275, China.
Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, Northwestern Polytechnical University, Xi'an, 710072, China.
Guangdong Provincial Key Laboratory of Research and Development of Natural Drugs and School of Pharmacy, Guangdong Medical University, Dongguan, 523808, P. R. China.
The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, 523808, P. R. China.
Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing, National Engineering Research Center of Novel Equipment for Polymer Processing, Key Laboratory of Polymer Processing Engineering (SCUT) Ministry of Education, South China University of Technology, Guangzhou, 510641, P. R. China.
Micro- and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China.
School of Materials Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, China.
State Key Laboratory of Polymer Materials Engineering, Sichuan University, Chengdu, 610065, People's Republic of China.

人机交互（HMI）技术在康复医学中显示出重要的应用前景，但由于识别精度和佩戴舒适度不理想而受到很大限制。这项工作开发了一种完全灵活、舒适且功能化的多模式 HMI 界面，由基于水凝胶的传感器和自行设计的柔性印刷电路板组成。由于水凝胶的成分调节和结构设计，可以准确稳定地收集肌电图（EMG）和肌力图（FMG）信号，以便随后在人工智能（AI）的帮助下进行解码。与传统的多通道肌电信号相比，基于肌电和FMG信号组合的多模态人机交互方法通过增加交互信号的信息熵，显着提高了人机交互的效率。仅两个通道不同手势的交互信号解码准确率达到91.28%。由此产生的人工智能主动康复系统可以控制气动机器人手套，帮助中风患者根据识别的人体运动意图完成运动。此外，该HMI界面进一步推广并应用于其他遥感平台，如机械手、智能汽车和无人机，为未来智能机器人系统的设计铺平了道路。

"点击查看英文标题和摘要"

High-Performance Hydrogel Sensors Enabled Multimodal and Accurate Human–Machine Interaction System for Active Rehabilitation

Human–machine interaction (HMI) technology shows an important application prospect in rehabilitation medicine, but it is greatly limited by the unsatisfactory recognition accuracy and wearing comfort. Here, this work develops a fully flexible, conformable, and functionalized multimodal HMI interface consisting of hydrogel-based sensors and a self-designed flexible printed circuit board. Thanks to the component regulation and structural design of the hydrogel, both electromyogram (EMG) and forcemyography (FMG) signals can be collected accurately and stably, so that they are later decoded with the assistance of artificial intelligence (AI). Compared with traditional multichannel EMG signals, the multimodal human–machine interaction method based on the combination of EMG and FMG signals significantly improves the efficiency of human–machine interaction by increasing the information entropy of the interaction signals. The decoding accuracy of the interaction signals from only two channels for different gestures reaches 91.28%. The resulting AI-powered active rehabilitation system can control a pneumatic robotic glove to assist stroke patients in completing movements according to the recognized human motion intention. Moreover, this HMI interface is further generalized and applied to other remote sensing platforms, such as manipulators, intelligent cars, and drones, paving the way for the design of future intelligent robot systems.

更新日期：2023-12-14

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