BCI-FES With Multimodal Feedback for Motor Recovery Poststroke.

BCI-FES With Multimodal Feedback for Motor Recovery Poststroke.
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具有多模式反馈的BCI-FES用于中风后的运动恢复。

DOI:
10.3389/fnhum.2022.725715
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发表时间:
2022
影响因子:
2.9
通讯作者:
--
中科院分区:
医学3区
文献类型:
--
作者:

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越来越多的研究团队正在研究脑机接口(BCI)介导的干预措施对促进中风后运动恢复的有效性。越来越多的证据表明,在各种BCI设计中,最有效的是那些根据运动意图对上肢(UE)肌肉进行功能性电刺激(FES)的设计。更具体地说,BCI-FES干预利用隔离运动信号的算法-从大脑皮层运动区记录的用户生成的意图移动神经活动-来驱动单个肌肉或肌肉协同作用的电刺激。BCI-FES干预旨在通过促进和/或诱导适当控制回路中的长期运动学习相关神经可塑性变化来恢复受损肢体的感觉运动功能。我们开发了一种非侵入性的、基于脑电图(EEG)的BCI-FES系统,该系统提供对目标远端肌肉的闭环神经活动触发的电刺激,同时为用户提供多模态感觉反馈。该BCI-FES系统由三个组件组成:(1)EEG采集和信号处理,以从大脑皮层运动区提取实时意志和任务相关的神经命令信号,(2)视运动皮层神经命令信号而定的受损手部肌肉的FES,以及(3)与行为任务的执行相关的多模态感觉反馈,包括视觉信息,通过完整的感觉运动回路和舌头的电触觉刺激来激活躯体感觉传入。在这份报告中,我们描述了我们的BCI-FES系统的设备参数和干预方案,结合标准的物理康复方法,已被证明在治疗中风幸存者的UE运动障碍方面是有效的,无论损伤程度和慢性程度如何。
An increasing number of research teams are investigating the efficacy of brain-computer interface (BCI)-mediated interventions for promoting motor recovery following stroke. A growing body of evidence suggests that of the various BCI designs, most effective are those that deliver functional electrical stimulation (FES) of upper extremity (UE) muscles contingent on movement intent. More specifically, BCI-FES interventions utilize algorithms that isolate motor signals—user-generated intent-to-move neural activity recorded from cerebral cortical motor areas—to drive electrical stimulation of individual muscles or muscle synergies. BCI-FES interventions aim to recover sensorimotor function of an impaired extremity by facilitating and/or inducing long-term motor learning-related neuroplastic changes in appropriate control circuitry. We developed a non-invasive, electroencephalogram (EEG)-based BCI-FES system that delivers closed-loop neural activity-triggered electrical stimulation of targeted distal muscles while providing the user with multimodal sensory feedback. This BCI-FES system consists of three components: (1) EEG acquisition and signal processing to extract real-time volitional and task-dependent neural command signals from cerebral cortical motor areas, (2) FES of muscles of the impaired hand contingent on the motor cortical neural command signals, and (3) multimodal sensory feedback associated with performance of the behavioral task, including visual information, linked activation of somatosensory afferents through intact sensorimotor circuits, and electro-tactile stimulation of the tongue. In this report, we describe device parameters and intervention protocols of our BCI-FES system which, combined with standard physical rehabilitation approaches, has proven efficacious in treating UE motor impairment in stroke survivors, regardless of level of impairment and chronicity.
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