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在机器人辅助的多模态刺激训练过程中对相互作用的脑网络进行识别。

The identification of interacting brain networks during robot-assisted training with multimodal stimulation.

作者信息

Wang Duojin, Huang Yanping, Liang Sailan, Meng Qingyun, Yu Hongliu

机构信息

Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, People's Republic of China.

Shanghai Engineering Research Center of Assistive Devices, 516 Jungong Road, Shanghai 200093, People's Republic of China.

出版信息

J Neural Eng. 2023 Jan 18;20(1). doi: 10.1088/1741-2552/acae05.

Abstract

Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far, various robotic devices have been developed for automatic training of central nervous system following injury. Multimodal stimulation such as visual and auditory stimulus and even virtual reality technology were usually introduced in these robotic devices to improve the effect of rehabilitation training. This may need to be explained from a neurological perspective, but there are few relevant studies.In this study, ten participants performed right arm rehabilitation training tasks using an upper limb rehabilitation robotic device. The tasks were completed under four different feedback conditions including multiple combinations of visual and auditory components: auditory feedback; visual feedback; visual and auditory feedback (VAF); non-feedback. The functional near-infrared spectroscopy devices record blood oxygen signals in bilateral motor, visual and auditory areas. Using hemoglobin concentration as an indicator of cortical activation, the effective connectivity of these regions was then calculated through Granger causality.We found that overall stronger activation and effective connectivity between related brain regions were associated with VAF. When participants completed the training task without VAF, the trends in activation and connectivity were diminished.This study revealed cerebral cortex activation and interacting networks of brain regions in robot-assisted rehabilitation training with multimodal stimulation, which is expected to provide indicators for further evaluation of the effect of rehabilitation training, and promote further exploration of the interaction network in the brain during a variety of external stimuli, and to explore the best sensory combination.

摘要

机器人辅助康复训练是辅助康复治疗的一种有效方式。到目前为止,已经开发出了各种机器人设备用于中枢神经系统损伤后的自动训练。这些机器人设备通常会引入视觉和听觉刺激等多模态刺激,甚至虚拟现实技术,以提高康复训练的效果。这可能需要从神经学角度进行解释,但相关研究较少。在本研究中,十名参与者使用上肢康复机器人设备执行右臂康复训练任务。这些任务在四种不同的反馈条件下完成,包括视觉和听觉成分的多种组合:听觉反馈;视觉反馈;视觉和听觉反馈(VAF);无反馈。功能近红外光谱设备记录双侧运动、视觉和听觉区域的血氧信号。以血红蛋白浓度作为皮质激活的指标,然后通过格兰杰因果关系计算这些区域的有效连接性。我们发现,总体而言,相关脑区之间更强的激活和有效连接性与视觉和听觉反馈有关。当参与者在没有视觉和听觉反馈的情况下完成训练任务时,激活和连接性的趋势会减弱。本研究揭示了在多模态刺激的机器人辅助康复训练中大脑皮质的激活以及脑区的相互作用网络,这有望为进一步评估康复训练效果提供指标,并促进对大脑在各种外部刺激下相互作用网络的进一步探索,以及探索最佳的感觉组合。

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