Department of Health Science and Technology, Aalborg University, 9000 Aalborg, Denmark.
Centre for Chiropractic Research, New Zealand College of Chiropractic, Auckland 1060, New Zealand.
Sensors (Basel). 2022 Feb 21;22(4):1676. doi: 10.3390/s22041676.
Brain-computer interface performance may be reduced over time, but adapting the classifier could reduce this problem. Error-related potentials (ErrPs) could label data for continuous adaptation. However, this has scarcely been investigated in populations with severe motor impairments. The aim of this study was to detect ErrPs from single-trial EEG in offline analysis in participants with cerebral palsy, an amputation, or stroke, and determine how much discriminative information different brain regions hold. Ten participants with cerebral palsy, eight with an amputation, and 25 with a stroke attempted to perform 300-400 wrist and ankle movements while a sham BCI provided feedback on their performance for eliciting ErrPs. Pre-processed EEG epochs were inputted in a multi-layer perceptron artificial neural network. Each brain region was used as input individually (Frontal, Central, Temporal Right, Temporal Left, Parietal, and Occipital), the combination of the Central region with each of the adjacent regions, and all regions combined. The Frontal and Central regions were most important, and adding additional regions only improved performance slightly. The average classification accuracies were 84 ± 4%, 87± 4%, and 85 ± 3% for cerebral palsy, amputation, and stroke participants. In conclusion, ErrPs can be detected in participants with motor impairments; this may have implications for developing adaptive BCIs or automatic error correction.
脑机接口的性能可能随时间下降，但通过自适应分类器可以减少这个问题。错误相关电位（ErrPs）可以对数据进行标记，以便进行连续自适应。然而，在严重运动障碍的人群中，这种方法几乎没有被研究过。本研究旨在离线分析中从脑瘫、截肢或中风患者的单试 EEG 中检测 ErrPs，并确定不同脑区包含多少可区分的信息。10 名脑瘫患者、8 名截肢患者和 25 名中风患者尝试进行 300-400 次腕部和踝部运动，而虚假 BCI 会根据他们的表现提供反馈以引发 ErrPs。预处理后的 EEG 时段被输入到多层感知机人工神经网络中。每个脑区都单独作为输入（额叶、中央、右侧颞叶、左侧颞叶、顶叶和枕叶），中央区与每个相邻区的组合，以及所有区的组合。额叶和中央区最重要，增加额外的区域仅略微提高了性能。脑瘫、截肢和中风患者的平均分类准确率分别为 84±4%、87±4%和 85±3%。总之，在运动障碍患者中可以检测到 ErrPs；这可能对开发自适应 BCI 或自动错误纠正具有重要意义。
