Applying a brain-computer interface to support motor imagery practice in people with stroke for upper limb recovery: a feasibility study.
Applying a brain-computer interface to support motor imagery practice in people with stroke for upper limb recovery: a feasibility study.
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DOI：
10.1186/1743-0003-7-60
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发表时间：
2010-12-14
影响因子：
5.1
通讯作者：
Crosbie J
中科院分区：
文献类型：
--
作者：
Prasad G;Herman P;Coyle D;McDonough S;Crosbie J
现在有足够的证据表明，使用包括运动想象(MI)练习和以目标为导向的康复任务的物理练习(PP)相结合的康复方案可以增强中风患者瘫痪肢体的功能恢复。然而，在没有任何在线测量的情况下，很难在MI期间确认患者的参与度。幸运的是，基于脑电的脑机接口(BCI)可以为BCI用户提供MI活动的在线测量作为神经反馈，帮助他们更好地专注于MI任务。然而，BCI新手用户的初始表现可能相当一般，可能会导致挫折感。本文报告了一项先导性研究，在该研究中，脑机接口系统被用来在协议的MI部分向中风参与者提供基于计算机游戏的神经反馈。参与者包括五名慢性偏瘫中风患者。参与者接受为期6周的每周2天的最多12次30分钟的MI练习课程(与相同持续时间的PP课程一起)。根据MI任务分类准确率(CA)评价BCI神经反馈性能。在评估上肢功能恢复时，采用了包括动作研究臂测试(ARAT)和握力(GS)在内的一系列结果测量。此外，由于中风患者经常经历身体疲劳，这可能会影响协议的有效性，因此定期评估他们的疲劳和情绪水平。在所有参与者中，至少在一项结果测量中观察到积极的改善，同时改善接近ARAT的最小临床重要差异(MCID)。在有限的12次训练中，新手MI以偏侧化事件相关去同步(ERD)和事件相关同步(ERS)效应形式诱发的感觉运动节奏(SMR)调制模式的在线CA在60%-75%的中等范围内。从第一次会议到最后一次会议，ERD/ERS的变化只对两名参与者具有统计学意义。总体而言，关键的观察是，适度的BCI分类表现并没有阻碍积极的康复趋势，正如本研究中采用的康复结果衡量标准所量化的那样。因此，可以得出结论，脑机接口支持的心肌梗死是一种可行的干预措施，作为卒中后康复方案的一部分，结合了康复任务的PP和MI实践。尽管这些发现很有希望，但最终结论的范围受到样本量小和缺乏对照组的限制。
There is now sufficient evidence that using a rehabilitation protocol involving motor imagery (MI) practice in conjunction with physical practice (PP) of goal-directed rehabilitation tasks leads to enhanced functional recovery of paralyzed limbs among stroke sufferers. It is however difficult to confirm patient engagement during an MI in the absence of any on-line measure. Fortunately an EEG-based brain-computer interface (BCI) can provide an on-line measure of MI activity as a neurofeedback for the BCI user to help him/her focus better on the MI task. However initial performance of novice BCI users may be quite moderate and may cause frustration. This paper reports a pilot study in which a BCI system is used to provide a computer game-based neurofeedback to stroke participants during the MI part of a protocol. The participants included five chronic hemiplegic stroke sufferers. Participants received up to twelve 30-minute MI practice sessions (in conjunction with PP sessions of the same duration) on 2 days a week for 6 weeks. The BCI neurofeedback performance was evaluated based on the MI task classification accuracy (CA) rate. A set of outcome measures including action research arm test (ARAT) and grip strength (GS), was made use of in assessing the upper limb functional recovery. In addition, since stroke sufferers often experience physical tiredness, which may influence the protocol effectiveness, their fatigue and mood levels were assessed regularly. Positive improvement in at least one of the outcome measures was observed in all the participants, while improvements approached a minimal clinically important difference (MCID) for the ARAT. The on-line CA of MI induced sensorimotor rhythm (SMR) modulation patterns in the form of lateralized event-related desynchronization (ERD) and event-related synchronization (ERS) effects, for novice participants was in a moderate range of 60-75% within the limited 12 training sessions. The ERD/ERS change from the first to the last session was statistically significant for only two participants. Overall the crucial observation is that the moderate BCI classification performance did not impede the positive rehabilitation trends as quantified with the rehabilitation outcome measures adopted in this study. Therefore it can be concluded that the BCI supported MI is a feasible intervention as part of a post-stroke rehabilitation protocol combining both PP and MI practice of rehabilitation tasks. Although these findings are promising, the scope of the final conclusions is limited by the small sample size and the lack of a control group.