Injection‐on‐Skin Granular Adhesive for Interactive Human–Machine Interface

Author:

Kim Sumin12,Jang Jaepyo23,Kang Kyumin23,Jin Subin12,Choi Heewon23,Son Donghee234,Shin Mikyung125ORCID

Affiliation:

1. Department of Intelligent Precision Healthcare Convergence Sungkyunkwan University Suwon 16419 Republic of Korea

2. Center for Neuroscience Imaging Research Institute for Basic Science (IBS) Suwon 16419 Republic of Korea

3. Department of Electrical and Computer Engineering Sungkyunkwan University Suwon 16419 Republic of Korea

4. Department of Artificial Intelligence System Engineering Sungkyunkwan University Suwon 16419 Republic of Korea

5. Department of Biomedical Engineering Sungkyunkwan University Suwon 16419 Republic of Korea

Abstract

AbstractRealization of interactive human–machine interfaces (iHMI) is improved with development of soft tissue‐like strain sensors beyond hard robotic exosuits, potentially allowing cognitive behavior therapy and physical rehabilitation for patients with brain disorders. Here, this study reports on a strain‐sensitive granular adhesive inspired by the core–shell architectures of natural basil seeds for iHMI as well as human–metaverse interfacing. The granular adhesive sensor consists of easily fragmented hydropellets as a core and tissue‐adhesive catecholamine layers as a shell, satisfying great on‐skin injectability, ionic‐electrical conductivity, and sensitive resistance changes through reversible yet robust cohesion among the hydropellets. Particularly, it is found that the ionic‐electrical self‐doping of the catecholamine shell on hydrosurfaces leads to a compact ion density of the materials. Based on these physical and electrical properties of the sensor, it is demonstrated that successful iHMI integration with a robot arm in both real and virtual environments enables robotic control by finger gesture and haptic feedback. This study expresses benefits of using granular hydrogel‐based strain sensors for implementing on‐skin writable bioelectronics and their bridging into the metaverse world.

Funder

National Research Foundation of Korea

Publisher

Wiley

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3