EEG and EMG dataset for the detection of errors introduced by an active orthosis device
Niklas Kueper, Kartik Chari, Judith B\"utef\"ur, Julia Habenicht, Su, Kyoung Kim, Tobias Rossol, Marc Tabie, Frank Kirchner, and Elsa Andrea, Kirchner

TL;DR
This paper introduces an open dataset of EEG and EMG recordings from subjects using an active orthosis, including deliberate errors, to aid research in error detection and tactile error recognition in assistive devices.
Contribution
It provides a novel, publicly accessible dataset with detailed experimental setup data for studying error detection in EEG during orthosis-assisted movements.
Findings
Behavioral analysis across subjects
Event-related potential analysis for error detection
Dataset availability for future research
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…
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Taxonomy
TopicsEEG and Brain-Computer Interfaces · Muscle activation and electromyography studies · Motor Control and Adaptation
