Publication
EEG and EMG dataset for the detection of errors introduced by an active orthosis device
Niklas Kueper; Kartik Chari; Judith Bütefür; Julia Habenicht; Su Kyoung Kim; Tobias Rossol; Marc Tabie; Frank Kirchner; Elsa Andrea Kirchner
In: Frontiers in Human Neuroscience, Vol. 18, Frontiers, 1/2024.
Abstract
This paper presents a dataset containing
recordings of the electroencephalogram (EEG) and the
electromyogram (EMG) from eight subjects who were assisted
in moving their right arm by an active orthosis device. The
supported movements were elbow joint movements, i.e., flexion
and extension of the right arm. While the orthosis was actively
moving the subject's arm, some errors were deliberately
introduced for a short duration of time. During this time, the
orthosis moved in the opposite direction. In this paper, we
explain the experimental setup and present some behavioral
analyses across all subjects. Additionally, we present an
average event-related potential analysis for one subject to offer
insights into the data quality and the EEG activity caused by
the error introduction. The dataset described herein is openly
accessible. The aim of this study was to provide a dataset
to the research community, particularly for the development
of new methods in the asynchronous detection of erroneous
events from the EEG. We are especially interested in the tactile
and haptic-mediated recognition of errors, which has not yet
been sufficiently investigated in the literature. We hope that
the detailed description of the orthosis and the experiment will
enable its reproduction and facilitate a systematic investigation
of the influencing factors in the detection of erroneous behavior
of assistive systems by a large community.