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AI-enabled photonic smart garment for movement analysis.

Leticia Avellar1, Carlos Stefano Filho2, Gabriel Delgado3

  • 1Graduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Fernando Ferrari Avenue, Vitória, 29075-910, Brazil. leticia.avellar@ufes.br.

Scientific Reports
|March 9, 2022
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Summary

This study developed a smart garment using polymer optical fiber (POF) sensors and Artificial Intelligence (AI) for remote healthcare monitoring. The system accurately classifies daily activities and extracts movement parameters, paving the way for Healthcare 4.0.

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Area of Science:

  • Biomedical Engineering
  • Wearable Technology
  • Artificial Intelligence

Background:

  • Smart textiles offer non-invasive remote healthcare monitoring solutions.
  • Polymer optical fiber (POF) sensors are suitable for integration into smart textiles.
  • Artificial Intelligence (AI) enhances the decision-making capabilities of sensor-integrated clothing.

Purpose of the Study:

  • To develop a portable photonic smart garment with multiplexed POF sensors and AI for activity classification.
  • To evaluate the system's accuracy in recognizing six daily activities performed by multiple subjects.
  • To optimize sensor количество and assess movement parameter extraction for Healthcare 4.0 applications.

Main Methods:

  • Development of a smart garment incorporating 30 multiplexed POF sensors.
  • Application of AI algorithms, specifically a k-nearest neighbors classifier, for activity recognition.
  • Utilizing principal component analysis for sensor optimization and evaluating cadence, breathing rate, and shoulder flexion/extension.

Main Results:

  • The smart garment achieved 94.00% accuracy in classifying six daily activities across multiple subjects.
  • Sensor optimization using principal component analysis showed a slight decrease in accuracy (98.14% with 10 sensors vs. 30).
  • Accurate estimation of cadence and breathing rate with a maximum error of 2.22% compared to an inertial measurement unit.

Conclusions:

  • The developed photonic smart garment demonstrates feasibility for activity recognition and movement parameter extraction.
  • The system is optimized for sensor count and wireless communication, suitable for Healthcare 4.0.
  • This technology advances remote patient monitoring and personalized healthcare through intelligent textiles.