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Related Experiment Video

Updated: Jul 20, 2025

Bioinspired Soft Robot with Incorporated Microelectrodes

Bioinspired Soft Robot with Incorporated Microelectrodes

Published on: February 28, 2020

Deep-Learning Enabled Active Biomimetic Multifunctional Hydrogel Electronic Skin.

Kai Tao^1,2, Jiahao Yu^1,2, Jiyuan Zhang^1,2

¹Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.

|July 31, 2023

Summary

This summary is machine-generated.

This study introduces biomimetic electronic skin (BHES) that mimics human skin's epidermis and dermis. The advanced hydrogel-based skin accurately identifies materials and textures, enabling new human-machine interfaces.

Keywords:

Deep learning E-Skin Human machine interface Hydrogel Triboelectric nanogenerator

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Last Updated: Jul 20, 2025

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Four-Dimensional Printing of Stimuli-Responsive Hydrogel-Based Soft Robots

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Published on: January 13, 2023

Area of Science:

Materials Science
Biomedical Engineering
Robotics

Background:

Human skin's epidermis and dermis perform critical sensory functions for physical interaction.
Recreating these functions in artificial skin is essential for advanced robotics and human-machine interfaces.
Existing electronic skin technologies often lack the sensitivity, multifunctionality, or biomimicry required for sophisticated applications.

Purpose of the Study:

To develop a biomimetic, ultrasensitive, and multifunctional hydrogel-based electronic skin (BHES).
To mimic the epidermis for material identification via contact electrification.
To replicate dermal mechanoreceptors for texture and pressure sensing.

Main Methods:

Epidermis mimicry using poly(ethylene terephthalate) with nanoscale wrinkles for contact electrification.
Mechanoreceptor mimicry using interdigital silver electrodes with stick-slip sensing for texture identification.
Dermis mimicry with patterned microcone hydrogel for high-sensitivity pressure sensing.

Main Results:

The BHES achieved high sensitivity (17.32 mV/Pa) and a wide pressure range (20-5000 Pa) with fast response (10 ms) and recovery (17 ms).
Deep learning integration enabled high accuracy in material (95.00%) and texture (97.20%) identification.
A wearable drone control system demonstrated the BHES's potential for soft robots and digital twin interfaces.

Conclusions:

The proposed BHES successfully replicates key functions of human epidermis and dermis.
This technology offers significant potential for advanced soft robotics, self-powered human-machine interaction, and digital twin applications.
The BHES demonstrates a novel approach to creating sophisticated, responsive artificial skin.