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Measurement of 3D Wrist Angles by Combining Textile Stretch Sensors and AI Algorithm.

Jae-Ha Kim1, Bon-Hak Koo1, Sang-Un Kim2

  • 1Department of Materials Science and Engineering, Soongsil University, Seoul 156-743, Republic of Korea.

Sensors (Basel, Switzerland)
|March 13, 2024
PubMed
Summary

New textile stretch sensors accurately measure wrist angles in three dimensions. This advancement in wearable technology offers precise data for sports analysis and rehabilitation applications.

Keywords:
AI algorithmsmulti-layer perceptronsmart wearable sensorstextile stretch sensorswrist angle

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Area of Science:

  • Biomedical Engineering
  • Materials Science
  • Wearable Technology

Background:

  • The wrist joint's complexity necessitates accurate angle measurement for applications in sports and rehabilitation.
  • Existing methods for measuring wrist angles may lack the flexibility or cost-effectiveness for widespread use.
  • Textile stretch sensors offer a promising alternative due to their lightweight, cost-effective, and reproducible nature.

Purpose of the Study:

  • To develop and validate textile stretch sensors for precise, three-dimensional wrist angle measurement.
  • To investigate the efficacy of a deep learning approach in enhancing sensor accuracy.
  • To demonstrate the practical application of these sensors in an arm sleeve for real-time motion analysis.

Main Methods:

  • Fabrication of textile stretch sensors by immersing an E-band in a carbon nanotube solution.
  • Attachment of three sensors to an arm sleeve to capture wrist movements across all three axes.
  • Application of the Multi-Layer Perceptron (MLP) deep learning technique to process sensor data.
  • Development of a novel algorithm to utilize sensor coupling for 3D angle calculation.

Main Results:

  • Textile stretch sensors successfully measured wrist angles in three dimensions when integrated into an arm sleeve.
  • The Multi-Layer Perceptron (MLP) technique significantly improved sensor precision.
  • The developed algorithm, leveraging sensor coupling, achieved an error angle of less than 4.5°.
  • This accuracy surpasses that of other available soft sensors for wrist angle measurement.

Conclusions:

  • Textile stretch sensors, enhanced by deep learning, provide a highly accurate and practical solution for 3D wrist angle measurement.
  • The developed system demonstrates significant potential for enhancing sports performance analysis and physical rehabilitation.
  • This research highlights the feasibility of integrating advanced wearable sensing technology into everyday clothing.