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

Niklas Kueper; Kartik Chari; Judith Bütefür; Julia Habenicht; Tobias Rossol; Su Kyoung Kim; Marc Tabie; Frank Kirchner; Elsa Andrea Kirchner

doi:10.3389/fnhum.2024.1304311

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

Front Hum Neurosci. 2024 Jan 22:18:1304311. doi: 10.3389/fnhum.2024.1304311. eCollection 2024.

Authors

Niklas Kueper^#¹, Kartik Chari^#¹, Judith Bütefür², Julia Habenicht², Tobias Rossol¹, Su Kyoung Kim¹, Marc Tabie¹, Frank Kirchner^{1

3}, Elsa Andrea Kirchner^{1

2}

Affiliations

¹ Robotics Innovation Centre, German Research Centre for Artificial Intelligence (DFKI), Bremen, Germany.
² Institute of Medical Technology Systems, University of Duisburg-Essen, Duisburg, Germany.
³ Robotics Lab, University of Bremen, Bremen, Germany.

^# Contributed equally.

No abstract available

Keywords: EEG; EMG; brain computer interface (BCI); dataset; error-related potential (ErrP); event-related potential (ERP); human-robot interaction (HRI); orthosis.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was funded by the German Federal Ministry of Education and Research (BMBF) under the project M-ROCK (Grant No.: 01IW21002) and by the Institute of Medical Systems at the University of Duisburg-Essen.