Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China.
Shanghai Engineering Research Center of Assistive Devices, Shanghai, China.
Brain Connect. 2024 Oct;14(8):401-417. doi: 10.1089/brain.2024.0005. Epub 2024 Aug 1.
With an aging population, the prevalence of neurological disorders is increasing, leading to a rise in lower limb movement disorders and, in turn, a growing need for rehabilitation training. Previous neuroimaging studies have shown a growing scientific interest in the study of brain mechanisms in robot-assisted lower limb rehabilitation (RALLR). This review aimed to determine differences in neural activity patterns during different RALLR tasks and the impact on neurofunctional plasticity. Sixty-five articles in the field of RALLR were selected and tested using three brain function detection technologies. Most studies have focused on changes in activity in various regions of the cerebral cortex during different lower limb rehabilitation tasks but have also increasingly focused on functional changes in other cortical and deep subcortical structures. Our analysis also revealed a neglect of certain task types. We identify and discuss future research directions that may contribute to a clear understanding of neural functional plasticity under different RALLR tasks. Impact Statement The evaluation of robot-assisted lower limb rehabilitation based on brain function detection technology can assess the neurological changes of patients in the rehabilitation process by monitoring brain activities and can also provide more accurate guidance for robot-assisted lower limb rehabilitation. By monitoring the patient's brain activity, the robot can adjust according to the real-time status of the patient to achieve more effective rehabilitation training. This has potential impact on improving the rehabilitation effect and speeding up the rehabilitation process of patients.
随着人口老龄化,神经紊乱的患病率不断增加,导致下肢运动障碍的发病率上升,进而对康复训练的需求也日益增长。先前的神经影像学研究表明,机器人辅助下肢康复(RALLR)领域的大脑机制研究越来越受到科学界的关注。本综述旨在确定不同 RALLR 任务中的神经活动模式差异及其对神经功能可塑性的影响。选择了 65 篇 RALLR 领域的文章,并使用三种大脑功能检测技术进行了测试。大多数研究都集中在不同下肢康复任务中大脑皮层不同区域的活动变化上,但也越来越关注其他皮层和深部皮质下结构的功能变化。我们的分析还揭示了对某些任务类型的忽视。我们确定并讨论了未来的研究方向,这可能有助于清楚地了解不同 RALLR 任务下的神经功能可塑性。影响声明基于脑功能检测技术的机器人辅助下肢康复评估可以通过监测大脑活动来评估患者康复过程中的神经变化,也可以为机器人辅助下肢康复提供更准确的指导。通过监测患者的大脑活动,机器人可以根据患者的实时状态进行调整,以实现更有效的康复训练。这对提高患者的康复效果和加快康复进程具有潜在影响。