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A Simple and Scalable Fabrication Method for Organic Electronic Devices on Textiles
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Bioinspired Stretchable Fiber-Based Sensor toward Intelligent Human-Machine Interactions.

Tianliang Li1, Yifei Su1, Fayin Chen1

  • 1School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China.

ACS Applied Materials & Interfaces
|May 9, 2022
PubMed
Summary
This summary is machine-generated.

A novel bionic stretchable optical strain (BSOS) sensor, inspired by a plant, offers advanced human-machine interfaces (HMI). This durable, waterproof sensor accurately measures strain and bending for applications in virtual reality, robotics, and prosthetics.

Keywords:
bionicfiber Bragg gratingflexible strain sensorhuman motion monitoringhuman−machine interactionmachine learningwearable electronics

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Area of Science:

  • Biomimetic Engineering
  • Optical Sensing
  • Human-Machine Interfaces

Background:

  • Wearable sensors for human-machine interfaces (HMI) face challenges like complexity, poor waterproofing, and electromagnetic interference.
  • Flexible electronic elements in wearable devices have limitations hindering widespread HMI applications.

Purpose of the Study:

  • To develop a bionic stretchable optical strain (BSOS) sensor inspired by Lindernia nummularifolia (LN) for intelligent HMI.
  • To overcome limitations of existing wearable sensors, enhancing performance and functionality for HMI applications.

Main Methods:

  • A bionic stretchable optical strain (BSOS) sensor was designed using an LN-shaped optical fiber and a stretchable substrate.
  • The sensor utilizes the intensity difference of two fiber Bragg gratings' (FBGs') center wavelength for temperature self-compensation.
  • Machine learning techniques were employed for gesture classification using captured muscle activity signals.

Main Results:

  • The BSOS sensor demonstrated a large tensile strain range of up to 80% with ultrasensitivity and durability (≥20,000 cycles).
  • The sensor exhibited excellent waterproofness and enabled accurate measurements of human activities.
  • The system successfully achieved HMI control for virtual reality, robot interaction, and hands-free communication.

Conclusions:

  • The developed BSOS sensor offers a promising solution for intelligent HMI, addressing limitations of current wearable technologies.
  • Its capabilities in measuring human activities and controlling devices highlight its potential in smart medical care, rehabilitation, and prosthetics.
  • The integration with machine learning enables advanced gesture recognition for prosthetic motion intention.