中国现代神经疾病杂志 ›› 2025, Vol. 25 ›› Issue (8): 705-716. doi: 10.3969/j.issn.1672-6731.2025.08.005

• 脑血管病康复 • 上一篇    下一篇

2 基于静息态fMRI智能下肢康复机器人改善皮质下卒中患者运动功能的脑功能机制研究

郭丽, 赵紫璇, 杨栩, 尹勇*()   

  1. 650021 昆明,云南大学附属医院康复医学科(现在云南中医药大学第二附属医院康复治疗中心,邮政编码:650041)
  • 收稿日期:2025-06-30 出版日期:2025-08-25 发布日期:2025-09-06
  • 通讯作者: 尹勇
  • 基金资助:
    国家自然科学基金资助项目(81960422); 云南省教育厅科学研究基金项目(2023J0042)

Research on brain functional mechanism underlying improvement of motor functionby intelligent lower limb rehabilitation robot based on resting - state fMRI in subcortical stroke

Li GUO, Zi-xuan ZHAO, Xu YANG, Yong YIN*()   

  1. Department of Rehabilitation Medicine, The Affiliated Hospital of Yunnan University, Kunming 650021, Yunnan, China
  • Received:2025-06-30 Online:2025-08-25 Published:2025-09-06
  • Contact: Yong YIN
  • Supported by:
    the National Natural Science Foundation of China(81960422); Scientific Research Foundation of Yunnan Provincial Education Department(2023J0042)

摘要:

目的: 通过基于静息态fMRI的脑功能活动及功能连接,探讨智能下肢康复机器人促进亚急性期皮质下卒中患者运动功能恢复的治疗机制。方法: 选择2022年1月至2023年8月云南大学附属医院收治的24例亚急性期皮质下卒中患者,随机分为机器人组(常规运动康复训练+ 机器人康复治疗,12例)和常规组(常规运动康复训练,12例)。基于rs-fMRI计算脑区静态低频振幅(sALFF)、动态低频振幅、静态局部一致性(sReHo)和动态局部一致性,探讨两组康复治疗后大脑功能活动变化;采用基于种子点的动态功能连接(dFC)和静态功能连接(sFC)分析两组康复治疗后种子点与其他脑区的功能连接变化;分别以美国国立卫生研究院卒中量表(NIHSS)、Fugl-Meyer下肢评价量表(FMA-LE)和改良Barthel指数(mBI)评估神经功能缺损程度、下肢运动功能及日常生活活动能力。结果: 机器人组和常规组康复治疗前后NIHSS评分(F = 17.806,P = 0.000)、FMA -LE评分(F = 51.911,P = 0.000)和mBI评分(F =130.224,P = 0.000)差异具有统计学意义,两组治疗后NIHSS评分均低于治疗前(t = - 2.785,P = 0.004;t =- 3.183,P = 0.011),FMA-LE评分(t = 7.225,P = 0.000;t = 2.964,P = 0.007)及mBI评分(t = 9.717,P = 0.000;t = 6.442,P = 0.000)高于治疗前。机器人组治疗后右侧枕叶皮质腹内侧和左侧枕叶皮质外侧sALFF值降低、右侧楔前叶sReHo值增加(均体素水平P<0.005,团块水平P<0.05);右侧枕叶皮质腹内侧与右侧小脑Ⅷ叶dFC值和左侧枕叶皮质腹内侧sFC值降低,而与右侧顶下小叶sFC值增加,左侧枕叶皮质外侧与右侧小脑Ⅶ叶和右侧顶下小叶sFC值增加(均体素水平P<0.005,团块水平P<0.05)。常规组治疗后左侧岛叶和左侧扣带回sALFF值增加(均体素水平P<0.005,团块水平P<0.05);左侧扣带回与左侧额上回dFC值增加,而与右侧枕叶皮质外侧和右侧梭状回sFC值降低(均体素水平P<0.005,团块水平P<0.05)。康复治疗前后机器人组左侧枕叶皮质外侧sALFF值差值与mBI评分差值呈负相关(r = - 0.609,P = 0.036)。结论: 智能下肢康复机器人可以通过增加楔前叶神经活动同步性,优化运动控制策略,调节枕叶与小脑以及枕叶与顶下小叶间功能连接,增强感觉-运动整合,促进皮质下卒中患者下肢运动功能恢复。

关键词: 卒中, 大脑皮质, 磁共振成像, 康复, 外骨骼康复器

Abstract:

Objective: To investigate the treatment mechanism of the intelligent lower limb rehabilitation robot to promote the recovery of motor function in patients with subacute subcortical stroke, based on resting-state fMRI (rs-fMRI) in terms of functional activity and functional connectivity. Methods: Twenty - four patients with subacute subcortical stroke were admitted to The Affiliated Hospital of Yunnan University between January 2022 and August 2023. They were randomly assigned to either robot group (conventional rehabilitation treatment combined with robot rehabilitation treatment, n = 12) or conventional group (conventional rehabilitation treatment, n = 12). Based on the rs-fMRI data, static amplitude of low - frequency fluctuation (sALFF), dynamic amplitude of low - frequency fluctuation (dALFF), static regional homogeneity (sReHo) and dynamic regional homogeneity (dReHo) were calculated to analyze changes in brain functional activity in 2 groups after treatment. The seed-based dynamic functional connectivity (dFC) and static functional connectivity (sFC) analysis methods were used to explore the distribution of changes in functional connectivity between brain regions exhibiting altered functional activity after treatment and other brain regions across the 2 groups. Neurological deficits, lower limb motor function and activities of daily living were assessed using the National Institutes of Health Stroke Scale (NIHSS), the Fugl - Meyer Assessment Scale for Lower Extremity (FMA - LE) and the modified Barthel Index (mBI), respectively. Results: The differences in NIHSS score (F = 17.806, P = 0.000), FMA -LE score (F = 51.911, P = 0.000) and mBI score (F = 130.224, P = 0.000) between robot group and conventional group before and after treatment were statistically significant. After treatment, the NIHSS score in robot group (t = - 2.785, P = 0.004) and conventional group (t = - 3.183, P = 0.011) were lower than those before treatment, while FMA-LE score (t = 7.225, P = 0.000; t = 2.964, P = 0.007) and mBI score (t = 9.717, P = 0.000; t = 6.442, P = 0.000) in robot group and conventional group were higher than those before treatment. After treatment, the robot group exhibited decreased sALFF in the right medioventral occipital cortex and left lateral occipital cortex and increased sReHo in the right precuneus (voxel level threshold of P < 0.005 and cluster level threshold of P < 0.05, for all). Decreased dFC in the right medioventral occipital cortex with right lobule Ⅷ of the cerebellar hemisphere, and decreased sFC with the left medioventral occipital cortex, while increased sFC with the right inferior parietal lobule (voxel level threshold of P < 0.005 and cluster level threshold of P < 0.05, for all). Increased sFC in the left lateral occipital cortex with right lobule Ⅶ of the cerebellar hemisphere and right inferior parietal lobule (voxel level threshold of P < 0.005 and cluster level threshold of P < 0.05, for all). The conventional group showed increased sALFF in the left insula and left cingulate gyrus (voxel level threshold of P < 0.005 and cluster level threshold of P < 0.05, for all). Increased dFC in the left cingulate gyrus with left superior frontal and decreased sFC with the right lateral occipital cortex and right fusiform gyrus (voxel level threshold of P < 0.005 and cluster level threshold of P < 0.05, for all). The difference in sALFF of the left lateral occipital cortex in robot group was negatively correlated with the difference in mBI score (r = - 0.609, P = 0.036). Conclusions: The intelligent lower limb rehabilitation robot may facilitate the recovery of motor function in patients with subcortical stroke by improving the synchronization of neural activity in the right precuneus, to optimize motor control strategies and by modulating the functional connectivity between the occipital lobule and cerebellum, and between the occipital lobule and parietal lobule to enhance sensorimotor integration.

Key words: Stroke, Cerebral cortex, Magnetic resonance imaging, Rehabilitation, Exoskeleton device