Multimodal Brain-Computer Interface Based on Artificial Intelligence for Rehabilitation of People with Motor Disorders

K. Sonkin, Yoav Zamir, J. Friedman
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Abstract

This paper describes a work in process of developing a solution for quality of life improvement for people with severe movement deficit after stroke and brain injuries. The solution is a multimodal brain-computer interface system for motor rehabilitation, which performs real-time decoding of brain and body signals using artificial intelligence methods. The project aims to develop a safe, affordable and portable system, which has the potential to become the key technology for neuro-rehabilitation of patients with severe movement disorders.
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基于人工智能的多模态脑机接口用于运动障碍患者康复
本文描述了一项正在进行的工作,为中风和脑损伤后严重运动缺陷的人提供改善生活质量的解决方案。解决方案是一个用于运动康复的多模态脑机接口系统,该系统使用人工智能方法对大脑和身体信号进行实时解码。该项目旨在开发一种安全、经济、便携的系统,该系统有可能成为严重运动障碍患者神经康复的关键技术。
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