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Updated: Dec 4, 2025

Development and Functionalization of Electrolyte-Gated Graphene Field-Effect Transistor for Biomarker Detection

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Published on: February 1, 2022

Substrate-Free Multilayer Graphene Electronic Skin for Intelligent Diagnosis.

Yancong Qiao¹, Xiaoshi Li¹, Jinming Jian¹

¹Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.

ACS Applied Materials & Interfaces

|October 22, 2020

Summary

This summary is machine-generated.

This study introduces substrate-free graphene electronic skin (e-skin) offering enhanced comfort and breathability. This novel e-skin enables real-time physiological monitoring, including electrocardiogram (ECG) analysis using convolutional neural networks (CNNs).

Keywords:

flexible system laser scribing graphene neural network physiological signal monitoring substrate-free

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Area of Science:

Materials Science
Biomedical Engineering
Wearable Technology

Background:

Current wearable sensors utilize substrates, leading to discomfort, limited flexibility, and skin irritation due to inhibited sweat evaporation.
Existing substrate-based electronic skins (e-skins) present interface mismatches and reduce breathability, impacting long-term wearability and skin health.

Purpose of the Study:

To develop a novel substrate-free graphene electronic skin (SFG e-skin) with improved comfort, flexibility, and multifunctionality.
To demonstrate the SFG e-skin's capability for sensitive physiological signal detection and real-time health monitoring.

Main Methods:

Fabrication of substrate-free laser scribed graphene (SFG) electronic skin (e-skin).
Transferring SFG e-skin onto various surfaces, including human skin, using water assistance.
Designing patterned graphene electronic skin (GES) for strain sensing and developing a convolutional neural network (CNN) for automated electrocardiogram (ECG) signal analysis.

Main Results:

The SFG e-skin exhibits excellent gas permeability, low impedance, flexibility, and breathability due to its porous structure.
The GES functions effectively as a strain sensor, detecting physiological signals like respiration, human motion, and ECG with high sensitivity.
A real-time ECG monitoring system utilizing GES and a trained CNN achieved successful automatic signal analysis.

Conclusions:

Substrate-free graphene electronic skin offers a comfortable, breathable, and versatile platform for wearable sensing.
The developed GES and CNN-based system demonstrate significant potential for advanced, real-time health telemonitoring applications.