中国康复理论与实践 ›› 2023, Vol. 29 ›› Issue (1): 71-76.doi: 10.3969/j.issn.1006-9771.2023.01.010

• 应用研究 • 上一篇    下一篇

基于运动表象的脑机接口训练对亚急性期脑卒中患者手功能康复的效果

刘明月, 李哲(), 曹永生, 郝道剑, 宋薛艺   

  1. 郑州大学第五附属医院康复医学科,河南郑州市 450000
  • 收稿日期:2022-07-08 修回日期:2022-11-02 出版日期:2023-01-25 发布日期:2023-02-17
  • 通讯作者: 李哲(1974-),男,博士,主任医师,主要研究方向:神经康复,E-mail: Lizhe.1974@163.com。
  • 作者简介:刘明月(1994-),男,汉族,河南周口市人,硕士研究生,主要研究方向:脑机接口技术。
  • 基金资助:
    河南省医学科技攻关计划省部共建项目(SBGJ202002092)

Effect of brain-computer interface training based on motor imagery on hand function for subacute stroke patients

LIU Mingyue, LI Zhe(), CAO Yongsheng, HAO Daojian, SONG Xueyi   

  1. Department of Rehabilitation Medicine, Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, China
  • Received:2022-07-08 Revised:2022-11-02 Online:2023-01-25 Published:2023-02-17
  • Contact: LI Zhe, E-mail: Lizhe.1974@163.com
  • Supported by:
    Henan Province Medical Science and Technology Research Program of Provincial and Ministry Co-construction(SBGJ202002092)

摘要:

目的 观察并探讨基于运动表象的脑机接口(BCI)训练对亚急性期脑卒中偏瘫患者手功能康复的疗效。

方法 2020年6月至2021年12月,郑州大学第五附属医院康复医学科亚急性期脑卒中偏瘫患者40例随机数字表法分为对照组(n = 20)和试验组(n = 20)。两组均予药物治疗和常规综合康复,对照组采用手部康复机器人训练,试验组采用基于运动表象的BCI训练,共4周。治疗前后,采用Fugl-Meyer评定量表上肢部分(FMA-UE)、改良Barthel指数、改良Ashworth量表进行评定,表面肌电图检测患侧指浅屈肌、指伸肌和拇短展肌在最大等长收缩状态下的积分肌电值(iEMG)。

结果 对照组脱落2例,试验组脱落1例。治疗后,两组各项指标均改善(t > 2.322, Z > 2.631, P < 0.05);除FMA-UE腕评分外,其他指标试验组优于对照组(t > 2.227, Z > 2.078, P < 0.05)。

结论 基于运动表象的BCI训练能有效改善亚急性期脑卒中偏瘫患者的手功能和日常生活活动能力。

关键词: 脑卒中, 运动表象, 脑机接口, 手功能

Abstract:

Objective To observe the effect of brain-computer interface (BCI) training based on motor imagery on hand function in hemiplegic patients with subacute stroke.

Methods From June, 2020 to December, 2021, 40 patients with hemiplegia in subacute stroke from Department of Rehabilitation Medicine, Fifth Affiliated Hospital of Zhengzhou University were divided into control group (n = 20) and experimental group (n = 20) using random number table. Both groups accepted medication and routine comprehensive rehabilitation, while the control group accepted hand rehabilitation robot training, and the experimental group accepted the robot training using motor imagery-based BCI, for four weeks. They were assessed with Fugl-Meyer Assessment-Upper Extremities (FMA-UE), modified Barthel Index, modified Ashworth scale, and measured integrated electromyogram of the superficial finger flexors, finger extensors and short thumb extensors of the affected forearm during maximum isometric voluntary contraction with surface electromyography.

Results Two patients in the control group and one in the experimental group dropped off. All the indexes improved in both groups after treatment (t > 2.322, Z > 2.631, P < 0.05), and they were better in the experimental group than in the control group (t > 2.227, Z > 2.078, P < 0.05), except the FMA-UE score of wrist.

Conclusion Motor imagery-based BCI training is more effective on hand function and activities of daily living in hemiplegic patients with subacute stroke.

Key words: stroke, motor imagery, brain-computer interface, hand function

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