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

脑-机接口 运动表象 虚拟现实 阿凡达 具身认知 计算机科学 人机交互 个性化 沉浸式(数学) 接口(物质) 康复 虚拟机 脑电图 心理学 人工智能 神经科学 气泡 最大气泡压力法 并行计算 数学 万维网 纯数学 操作系统
作者
Kishor Lakshminarayanan,Rakshit Shah,Vadivelan Ramu,Deepa Madathil,Yifei Yao,Inga Wang,Brahim Brahmi,Mohammad Habibur Rahman
出处
期刊:Journal of Visualized Experiments [MyJOVE]
卷期号: (207)
标识
DOI:10.3791/66859
摘要

This study introduces an innovative framework for neurological rehabilitation by integrating brain-computer interfaces (BCI) and virtual reality (VR) technologies with the customization of three-dimensional (3D) avatars. Traditional approaches to rehabilitation often fail to fully engage patients, primarily due to their inability to provide a deeply immersive and interactive experience. This research endeavors to fill this gap by utilizing motor imagery (MI) techniques, where participants visualize physical movements without actual execution. This method capitalizes on the brain's neural mechanisms, activating areas involved in movement execution when imagining movements, thereby facilitating the recovery process. The integration of VR's immersive capabilities with the precision of electroencephalography (EEG) to capture and interpret brain activity associated with imagined movements forms the core of this system. Digital Twins in the form of personalized 3D avatars are employed to significantly enhance the sense of immersion within the virtual environment. This heightened sense of embodiment is crucial for effective rehabilitation, aiming to bolster the connection between the patient and their virtual counterpart. By doing so, the system not only aims to improve motor imagery performance but also seeks to provide a more engaging and efficacious rehabilitation experience. Through the real-time application of BCI, the system allows for the direct translation of imagined movements into virtual actions performed by the 3D avatar, offering immediate feedback to the user. This feedback loop is essential for reinforcing the neural pathways involved in motor control and recovery. The ultimate goal of the developed system is to significantly enhance the effectiveness of motor imagery exercises by making them more interactive and responsive to the user's cognitive processes, thereby paving a new path in the field of neurological rehabilitation.
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