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Hand Prosthesis with Soft Robotics Technology and Artificial Intelligence for Fine Motor Control.

Marco Chaucala-Gualotuña1, Danni De la Cruz-Guevara2,3, Johanna Tobar-Quevedo1

  • 1Department of Energy and Mechanics Sciences, Universidad de las Fuerzas Armadas ESPE, Sangolquí 171103, Ecuador.

Sensors (Basel, Switzerland)
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Summary

This study introduces a novel soft robotic hand prosthesis that mimics natural muscle and tendon actions for improved grasping. This accessible myoelectric prosthetic offers functional fine motor assistance for everyday tasks.

Keywords:
fine motor controlintelligent sensorsprosthesissoft robotic

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Area of Science:

  • Biomedical Engineering
  • Robotics
  • Neuroprosthetics

Background:

  • Developing prosthetic hands with fine motor skills for daily assistance is challenging.
  • Existing prostheses often rely on complex sensors and lack adaptability.
  • Biomimetic design principles are crucial for intuitive prosthetic control.

Purpose of the Study:

  • To develop a soft robotic hand prosthesis prototype.
  • To achieve biomimetic motion and adaptable grasping without force sensors.
  • To utilize myoelectric signals for real-time prosthetic control.

Main Methods:

  • Designed a soft robotic hand with internal vacuum reinforcement and textured fingertips.
  • Employed myoelectric signals (EMG) from a wearable armband for control.
  • Utilized a lightweight dense neural network on a low-power microcontroller for signal processing.
  • Implemented tendon-driven actuation for smooth, compliant movements.

Main Results:

  • The prosthesis successfully reproduced open-hand and tripod pinch movements.
  • Real-time EMG signal classification enabled responsive control.
  • Functional tests showed response times between 0.49 and 2.00 seconds.
  • Achieved approximately 80% grasping effectiveness with everyday objects.

Conclusions:

  • The soft robotic hand prosthesis offers an accessible and functional solution for fine motor assistance.
  • The design shows potential for low-cost, resource-constrained myoelectric prosthetic systems.
  • This biomimetic approach advances the field of neuroprosthetics and assistive robotics.