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This paper describes a real-time, non-invasive control system for upper limb prosthetics using motion tracking and electromyography data in a virtual reality environment. The device is particularly useful for high-level amputees because it utilizes lower limb movements to control the arm. An inexpensive, multi-channel wireless EMG acquisition module enhances intuitive control by applying machine learning methods. Experimental results show the system’s efficiency, such as the fact that up to 90.4% accuracy is reached while having less than 1 s time for responses. The method requires less learning effort and provides a simple and accessible way to train using prosthetic limbs.

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Prosthetic Arm Control and Intuitive Limb Movement Motion Tracking Using EMG

  • 会议论文

  • 发表日期：

    2026年

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  • S. Dhanasekar,
  • V. Mounish,
  • K. Rithish,
  • P. Rithiv Krishna,
  • R. Nagasubiramaniyan,
  • T. Pavithran

摘要

This paper describes a real-time, non-invasive control system for upper limb prosthetics using motion tracking and electromyography data in a virtual reality environment. The device is particularly useful for high-level amputees because it utilizes lower limb movements to control the arm. An inexpensive, multi-channel wireless EMG acquisition module enhances intuitive control by applying machine learning methods. Experimental results show the system’s efficiency, such as the fact that up to 90.4% accuracy is reached while having less than 1 s time for responses. The method requires less learning effort and provides a simple and accessible way to train using prosthetic limbs.