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Sensor Fusion of Motion-Based Sign Language Interpretation with Deep Learning.

Boon Giin Lee1, Teak-Wei Chong2, Wan-Young Chung3

  • 1School of Computer Science, The University of Nottingham Ningbo China, Ningbo 315100, China.

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|November 5, 2020
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Summary

This study introduces a smart wearable system for American Sign Language (ASL) interpretation using inertial measurement units (IMUs). The system achieves 99.81% accuracy for dynamic gestures, overcoming limitations of computer vision methods.

Keywords:
deep learninghuman-computer interactionmotion sensorsensor fusionsign language recognitionwearable computing

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Area of Science:

  • Engineering
  • Computer Science
  • Human-Computer Interaction

Background:

  • Sign language is crucial for hearing-impaired individuals, but societal knowledge is limited, creating communication barriers.
  • Existing computer vision (CV) methods for sign language recognition face limitations due to visual angle dependency and environmental factors.
  • CV-based systems often require expert teams and expensive hardware, increasing real-world application costs.

Purpose of the Study:

  • To design and implement a smart wearable American Sign Language (ASL) interpretation system.
  • To overcome the limitations of CV-based approaches by utilizing sensor fusion and deep learning.
  • To provide a cost-effective and accessible solution for facilitating communication for the hearing-impaired community.

Main Methods:

  • Developed a deep learning model incorporating sensor fusion of six inertial measurement units (IMUs).
  • Attached IMUs to fingertips and the back of the hand to capture gesture data.
  • The system is designed to be independent of the field of view, unlike CV methods.

Main Results:

  • Achieved an average recognition rate of 99.81% for dynamic ASL gestures.
  • The wearable system demonstrated high accuracy and robustness in recognizing sign language.
  • The proposed method is not restricted by visual angle or environmental conditions.

Conclusions:

  • The developed wearable ASL interpretation system offers a highly accurate and reliable solution.
  • Integration with Information and Communication Technology (ICT) and Internet of Things (IoT) can further enhance its utility.
  • This technology has the potential to significantly improve communication and quality of life for the hearing-impaired.