BNCI2003_IVa Motor Imagery dataset
…BCI datasets, used extensively for benchmarking classification algorithms. The dataset was part…
- Participants
- 5
- Channels
- 118 (10-05)
- Citations
- 86
- HED
- v8.4.0
- Size
- 735 MB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
100 results for "benchmark dataset" · page 8 of 10 · ranked by relevance
…BCI datasets, used extensively for benchmarking classification algorithms. The dataset was part…
This dataset comprises EEG recordings from a P300 visual matrix speller study comparing three unsupervised learning methods (Expectation-Maximization, Learning from Label Proportions, and their combination MIX) for brain-computer interface decoding. Twelve healthy participants performed a copy-spelling task using a modified 6×6 character grid extended with 10 # symbols as visual blanks (46 total symbols), recorded at 1000 Hz from 31 EEG channels. The study demonstrates that unsupervised learning methods can achieve performance comparable to supervised approaches without requiring calibration data.
…898300) ## NEMAR / MOABB Benchmark Collection This BIDS-formatted dataset was converted from…
This dataset comprises intracranial EEG (iEEG) recordings from 12 epilepsy surgery patients enrolled in the RESPect (Registry for Epilepsy Surgery Patients) study at the University Medical Center of Utrecht. The collection includes both intraoperative electrocorticography (ECoG) recordings from six patients and long-term iEEG monitoring data from six patients (three ECoG, three stereo-encephalography). All data are organized according to the Brain Imaging Data Structure (BIDS) specification to facilitate standardized access and analysis of clinical neurophysiology data.
…https://github.com/jml226/Home-Appliance-Control-Dataset - **Publication year**: 2024 ## References…
This multimodal dataset comprises EEG, ECG, and pupillometry recordings from participants performing an n-back working memory task at four difficulty levels (1-back through 4-back). Data were collected using a combined mobile EEG+ECG system synchronized with a Pupil Labs eye tracker via Lab Streaming Layer, and converted from raw XDF recordings into BIDS format. The dataset is intended to support research on cognitive workload assessment across multiple physiological modalities.
…https://github.com/jml226/Home-Appliance-Control-Dataset - **Publication year**: 2024 ## References…
…The dataset comprises 125 patients (51 female, 41\%) from 5 different European…
The Brain, Body, and Behaviour Dataset - Experiment 3 is a multimodal neurophysiological dataset comprising 29 subjects across 2 sessions designed to investigate the effects of attentional state on learning from educational videos. Participants watched six educational videos under two conditions: attentive (with post-video testing) and distracted (with concurrent cognitive load), while simultaneous recordings of brain activity, cardiovascular function, eye movements, and head motion were collected. The dataset includes concurrent EEG, ECG, EOG, gaze tracking, pupil size, and head position data, along with behavioral measures including memory questionnaires and ADHD symptom assessments.
…10.82901/nemar.on002885) This dataset is a part of the data…