A BCI user awareness of an error is associated with a cortical signature named error-related potential (ErrP). The incorporation of ErrPs' detection in BCIs can improve BCIs' performance. This work is three-folded. First, we investigate if an ErrP classifier is transferable from able-bodied participants to participants with spinal cord injury (SCI). Second, we test this generic ErrP classifier with SCI and control participants, in an online experiment without offline calibration. Third, we investigate the morphology of ErrPs in both groups of participants. We used previously recorded electroencephalographic (EEG) data from able-bodied participants to train an ErrP classifier. We tested the classifier asynchronously, in an online experiment with 16 new participants: 8 participants with SCI and 8 able-bodied control participants. The experiment had no offline calibration and participants received feedback regarding the ErrPs' detection from its start. The generic classifier was not trained with the user's brain signals. Still, its performance was optimized during the online experiment with the use of personalized decision thresholds. Participants with SCI presented a non-homogenous ErrP morphology, and four of them did not present clear ErrP signals. The generic classifier performed above chance level in participants with clear ErrP signals, independently of the SCI (11 out of 16 participants). Three out of the five participants that obtained chance level results with the generic classifier would have not benefited from the use of a personalized classifier. This work shows the feasibility of transferring an ErrP classifier from able-bodied participants to participants with SCI, for asynchronous detection of ErrPs in an online experiment without offline calibration, which provided immediate feedback to the users.

中文翻译：

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通过适应预训练的通用分类器，在线异步检测脊髓损伤参与者中与错误相关的电位

BCI用户对错误的了解与名为错误相关电位（ErrP）的皮质签名相关。将ErrPs检测合并到BCI中可以提高BCI的性能。这项工作是三方面的。首先，我们研究ErrP分类器是否可以从健全的参与者转移到患有脊髓损伤（SCI）的参与者。其次，我们在没有离线校准的在线实验中，与SCI和控制参与者一起测试了这个通用的ErrP分类器。第三，我们调查了两组参与者的ErrPs形态。我们使用以前从身体健全的参与者记录的脑电图（EEG）数据来训练ErrP分类器。我们在一个在线实验中以16位新参与者异步测试了分类器：8位SCI参与者和8位健康对照参与者。实验没有离线校准，参与者从一开始就收到有关ErrPs检测的反馈。通用分类器未使用用户的大脑信号进行训练。尽管如此，它的性能还是在在线实验期间使用个性化决策阈值进行了优化。参加SCI的参与者呈现出不均一的ErrP形态，其中四个没有呈现清晰的ErrP信号。通用分类器以清晰的ErrP信号在参与者中的机会水平以上，独立于SCI（16名参与者中的11名）。使用通用分类器获得机会级别结果的五分之三的参与者不会从使用个性化分类器中受益。