信息通信技术与政策2024,Vol.50Issue(5) :41-46.DOI:10.12267/j.issn.2096-5931.2024.05.006

基于混合模态的脑机接口技术应用:神经康复新方向

Application of brain-computer interface based on hybrid modalities:a new direction in neural rehabilitation

董越 刘可 王涛
信息通信技术与政策2024,Vol.50Issue(5) :41-46.DOI:10.12267/j.issn.2096-5931.2024.05.006

基于混合模态的脑机接口技术应用:神经康复新方向

Application of brain-computer interface based on hybrid modalities:a new direction in neural rehabilitation

董越 1刘可 1王涛1
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作者信息

  • 1. 苏州念及智能科技有限公司,苏州 215000
  • 折叠

摘要

随着人口老龄化和慢性病患者增加,康复医疗领域面临着巨大挑战和机遇.非侵入式脑机接口技术作为一种创新的诊疗手段,为脑卒中等中枢神经受损导致运动失能的患病人群带来了新的希望.与传统康复训练相比,单一模态脑机接口技术具有激活感觉运动皮质、从大脑层面协助病人康复的优势,但单一模态各范式具有各自的局限性.混合模态是近年的研究热点,以两种范式相结合的方式来提升整体系统的可靠性和准确性.基于此,提出了一种新的运动-视觉混合模态脑机接口技术,该系统在在线实验中的平均分类准确率为86.67%,能够同时诱发运动皮层和视觉皮层的响应,有望成为主动康复、神经重塑的新范式.

Abstract

As the aging population and the number of patients with chronic diseases increase,the field of rehabilitation medicine faces both significant challenges and opportunities.Non-invasive brain computer interface(BCI)technology,as an innovative diagnostic and therapeutic tool,brings new hope to patients with motor disabilities caused by central nervous system damage such as stroke.Compared to traditional rehabilitation training,single-modal BCI technology has the advantage of activating sensory-motor cortex and assisting patients'rehabilitation from a brain-level perspective,but each single-modal paradigm has its limitations.Hybrid modalities have been a recent research focus,aiming to improve the overall system's reliability and accuracy by combining two modalities.Based on this,a novel motor-visual hybrid modality BCI technology is proposed,with an average classification accuracy of 86.67%in online experiments.It can simultaneously evoke responses from the motor cortex and visual cortex,and is expected to become a new paradigm for active rehabilitation and neural reshaping.

关键词

非侵入式脑机接口/康复医疗/视觉诱发电位/运动想象/混合模态

Key words

non-invasive BCI/neural rehabilitation/visual evoked potentials/motor imagery/hybrid modalities

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出版年

2024
信息通信技术与政策
信息产业部电信传输研究所

信息通信技术与政策

影响因子:0.363
ISSN:2096-5931
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