Motor Imagery Performance Through Embodied Digital Twins in a Virtual Reality-Enabled Brain-Computer Interface Environment

作者： Kishor Lakshminarayanan1, Rakshit Shah2, Vadivelan Ramu1, Deepa Madathil3, Yifei Yao4, Inga Wang5, Brahim Brahmi6, Mohammad Habibur Rahman7 1Department of Sensors and Biomedical Tech, School of Electronics Engineering,Vellore Institute of Technology, 2Department of Orthopaedic Surgery,University of Arizona, 3Jindal Institute of Behavioural Sciences,O. P. Jindal Global University, 4Soft Tissue Biomechanics Laboratory, Med-X Research Institute, School of Biomedical Engineering,Shanghai Jiao Tong University, 5Department of Occupational Science & Technology,University of Wisconsin-Milwaukee, 6Electrical Engineering,Collège Ahuntsic, 7Department of Mechanical Engineering, BioRobotics Lab,University of Wisconsin-Milwaukee

简介：

Overview

This study explores the integration of EEG, motor imagery, and virtual reality technologies to improve upper limb function in individuals with neurological injuries. Personalized digital avatars enhance immersion and body ownership during rehabilitation.

Key Study Components

Area of Science

• Neuro rehabilitation
• Brain-computer interfaces
• Virtual reality technologies

Background

• Upper limb function rehabilitation is crucial for individuals with neurological disorders.
• Virtual reality environments provide realistic simulations tailored to individual needs.
• Hybrid systems combining VR with robotic arms and haptic feedback are emerging.
• Intersubject variability poses challenges for brain-computer interface effectiveness.

Purpose of Study

• To enhance the effectiveness of motor skills rehabilitation.
• To understand the integration of various technologies in rehabilitation.
• To address the customization needs of brain-computer interfaces.

Methods Used

• EEG monitoring of brain activity during motor imagery.
• Use of virtual reality environments for rehabilitation exercises.
• Personalized digital avatars to enhance user experience.
• Assessment of intersubject variability in brain signals.

Main Results

• Improved motor skills observed in participants using VR technology.
• Personalized avatars increased immersion and engagement.
• Challenges in BCI customization highlighted the need for tailored approaches.
• Hybrid systems showed promise in enhancing rehabilitation outcomes.

Conclusions

• Combining EEG, motor imagery, and VR can significantly aid rehabilitation.
• Personalization is key to effective brain-computer interface systems.
• Further research is needed to address intersubject variability.

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