Intelligent Systems Research Centre (ISRC), University of Ulster, Magee Campus, Derry, N, Ireland, UK.
J Neuroeng Rehabil. 2010 Dec 14;7:60. doi: 10.1186/1743-0003-7-60.
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.
现在有足够的证据表明，使用一种康复方案，包括运动想象（MI）练习和有目标的物理康复任务的实践（PP），可以促进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，很难确认 MI 期间的患者参与度。幸运的是，基于脑电图的脑机接口（BCI）可以为 MI 活动提供在线测量，作为 BCI 用户的神经反馈，帮助他们更好地专注于 MI 任务。然而，新手 BCI 用户的初始表现可能相当中等，可能会导致挫败感。本文报告了一项初步研究，该研究使用 BCI 系统在方案的 MI 部分为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。参与者每周两天接受多达十二次 30 分钟的 MI 练习（与相同持续时间的 PP 练习相结合），为期六周。BCI 神经反馈性能基于 MI 任务分类准确性（CA）率进行评估。一套包括动作研究臂测试（ARAT）和握力（GS）在内的结果测量方法用于评估上肢功能恢复。此外，由于中风患者经常经历身体疲劳，这可能会影响方案的有效性，因此定期评估他们的疲劳和情绪水平。
所有参与者都观察到至少一项结果测量指标的积极改善，而 ARAT 的改善接近最小临床重要差异（MCID）。对于新手参与者，MI 诱导的感觉运动节律（SMR）调制模式的在线 CA 以侧化事件相关去同步化（ERD）和事件相关同步化（ERS）效应的形式表现出来，在有限的 12 次训练中，其范围在 60-75%之间。只有两名参与者在第一次和最后一次会议之间的 ERD/ERS 变化具有统计学意义。
总的来说，关键的观察结果是，作为中风后康复方案的一部分，结合了 PP 和 MI 练习的康复任务，适度的 BCI 分类性能并没有阻碍采用本研究中康复结果测量方法量化的积极康复趋势。因此，可以得出结论，BCI 支持的 MI 是一种可行的干预措施。尽管这些发现很有希望，但由于样本量小且缺乏对照组，最终结论的范围有限。
