EEG Brainwave Controlled Robotic Arm for Neurorehabilitation Training

Authors

  • Wenyi Chen School of Engineering, Shantou University
  • Ruike Wang School of Biomedical Engineering, Northeastern University, Shenyang
  • Bohan Yan School of Biomedical Engineering, Northeastern University, Shenyang
  • Yuxuan Li School of Biomedical Engineering, Northeastern University, Shenyang

DOI:

https://doi.org/10.61603/ceas.v1i2.18

Keywords:

neurorehabilitation, robotic arm, EEG, brainwaves, AI

Abstract

This study presents an EEG-based control method using AI for a robotic arm neurorehabilitation system. The system employs advanced EEG technology to capture and interpret brainwaves, utilizing AI algorithms for analysis and translation. This enables users to control the robotic arm via neural signals during neurorehabilitation training. Real-time feedback and adaptive AI ensure a personalized, interactive experience, and adjust the program based on user progress. This approach aims to enhance neurorehabilitation outcomes by promoting neuroplasticity and motor skill recovery in individuals with neurological disorders or injuries. The study’s results highlight AI’s positive impact on the system, suggesting EEG-based AI control could play a pivotal role in neurorehabilitation.

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Published

2023-12-22

Issue

Section

Articles

How to Cite

EEG Brainwave Controlled Robotic Arm for Neurorehabilitation Training. (2023). Cambridge Explorations in Arts and Sciences, 1(2). https://doi.org/10.61603/ceas.v1i2.18