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Updated: Aug 12, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
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Electromyogram-Based Lip-Reading via Unobtrusive Dry Electrodes and Machine Learning Methods.

Penghao Dong1, Yuanqing Song2, Shangyouqiao Yu1

  • 1Department of Mechanical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA.

Small (Weinheim an Der Bergstrasse, Germany)
|January 27, 2023
PubMed
Summary

This study introduces a novel, unobtrusive lip-reading system using skin-like sensors and machine learning to convert lip movements into speech. The technology offers robust performance in various conditions, enabling new human-machine interactions and assistive communication.

Keywords:
dry electrodeselectromyogramlip-readingmachine learningnanomaterials

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Area of Science:

  • Biomedical Engineering
  • Human-Computer Interaction
  • Machine Learning

Background:

  • Existing lip-reading systems are often bulky, obtrusive, and lack robustness, limiting their practical application.
  • A natural and unobtrusive method for converting lip movements to speech is needed for wider adoption.

Purpose of the Study:

  • To design and develop a hardware-software architecture for capturing, analyzing, and interpreting lip movements for speech conversion.
  • To create a robust and unobtrusive lip-reading system suitable for diverse environments and silent speech.
  • To demonstrate the system's potential in augmented reality and healthcare.

Main Methods:

  • Development of self-adhesive, skin-conformable, semi-transparent dry electrodes for electromyogram (EMG) signal acquisition.
  • Implementation of a hardware-software architecture to capture and analyze lip movements and associated EMG signals.
  • Utilization of machine learning algorithms to decode EMG signals and convert them into spoken words.

Main Results:

  • The developed system effectively recognizes different and similar visemes.
  • The system demonstrates robustness in noisy and dark environments.
  • Skin-like sensors ensure high-fidelity EMG signal capture with minimal interference.

Conclusions:

  • The novel lip-reading system offers a natural and unobtrusive solution for speech communication and human-machine interaction.
  • The technology shows significant potential for applications in augmented reality and medical services.
  • This advancement paves the way for more immersive interactions and improved assistive technologies.