EEG & EMG dataset for the detection of errors introduced by an active orthosis device

本数据集名为‘EEG & EMG dataset for the detection of errors introduced by an active orthosis device’，由德国人工智能研究中心和杜伊斯堡-埃森大学医学技术系统研究所合作创建。数据集包含8名受试者的EEG和EMG记录，这些受试者在进行右臂肘关节运动时，通过主动矫形器设备引入了短暂的运动方向错误。数据集的创建旨在为研究社区提供资源，特别是在开发新方法以异步检测EEG中的错误事件方面。通过详细描述矫形器和实验过程，本数据集旨在促进对辅助系统错误行为检测影响因素的系统研究，并探索触觉和力觉介导的错误识别，这一领域在文献中尚未得到充分研究。数据集的应用领域主要集中在通过EEG改善辅助技术的自然性和个性化支持，这对于康复治疗尤为重要。

This dataset, titled 'EEG & EMG dataset for the detection of errors introduced by an active orthosis device', was collaboratively created by the German Research Center for Artificial Intelligence and the Institute of Medical Technology Systems at the University of Duisburg-Essen. It contains EEG and EMG recordings from 8 participants who encountered transient movement direction errors induced by an active orthosis device while performing right elbow joint movements. The dataset was developed to provide resources for the global research community, particularly for advancing novel methods for the asynchronous detection of error-related events in EEG. By offering detailed descriptions of the orthosis device and the experimental protocol, this dataset aims to facilitate systematic research on the factors influencing error behavior detection in assistive systems, and to explore tactile and force-mediated error recognition—a research area that has not been sufficiently investigated in existing academic literature. The primary application scenarios of this dataset focus on improving the naturalness and personalized support of assistive technologies via EEG, which is particularly critical for rehabilitation therapy.