ArticleData in brief2026
EEG and EMG dataset for analyzing movement-related cortical potentials in hand gesture tasks.
Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This dataset contains electroencephalography (EEG) and electromyography (EMG) recordings acquired during the execution of specific motor tasks aimed at eliciting movement-related cortical potentials (MRCP). The goal is to provide an accessible resource for research in brain-computer interfaces (BCI), neurorehabilitation, and EEG-based prosthetic control. Data were collected from 40 healthy participants aged 18-30 years across five sessions, each comprising ten right-hand fist closure movements, guided by a custom Python-based visual interface. EEG signals were recorded using a 32-channel EMOTIV Flex 2 wireless system following the international 10-10 system, with a sampling rate of 128 Hz and electrode placement focused on the central cortical areas. All recordings, including raw EEG, raw EMG, and event triggers synchronized with the visual interface, were stored in .CSV format. To demonstrate that the EEG recordings in the dataset contain sufficient low-frequency information for MRCP analysis, we applied a standard preprocessing pipeline consisting of a common average reference (CAR), a Anti-Laplacian spatial filter, and a 0.1-1 Hz Butterworth band-pass filter. This procedure was used only for internal validation
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.