Showing 10 of 575 datasets · page 56 of 58
BIDS-EMG dataset - HDsEMG recordings of tibialis anterior and vastus lateralis during isometric contractions at 10-80% MVC, 16 subjects, 256-channel grids (MUniverse benchmark)
BIDS-EMG dataset - HDsEMG recordings of tibialis anterior during isometric contractions at 30% and 50% MVC, 6 subjects, 256-channel grids (MUniverse benchmark)
A multimodal neuroimaging dataset combining EEG, eye-tracking, and high-speed video recordings from 31 healthy participants performing a 4-class steady-state visually evoked potential (SSVEP) brain-computer interface task. The dataset comprises 3,024 trials across 63 sessions with 64-channel EEG recordings plus 1 EOG and 1 stimulus channel at 1000 Hz sampling rate, designed to investigate ocular activity patterns and their relationship to BCI performance across multiple paradigms.
A multimodal neuroimaging dataset combining EEG and eye-tracking recordings from 31 healthy participants performing motor imagery tasks. The dataset comprises 2,520 trials across 63 sessions, with participants imagining left and right hand movements in response to visual cues. Recorded at 1000 Hz using a 64-channel Neuroscan system, this dataset supports brain-computer interface research and motor imagery analysis.
This dataset comprises EEG recordings from 10 healthy participants performing a P300 speller task using a 6×6 character matrix. The study compares two stimulus conditions—famous faces and inverting—to evaluate their effects on online P300 classification performance using language models. Data were collected across 2 sessions per subject with 3 runs per session, sampled at 256 Hz from 32 EEG channels.
A multimodal neuroimaging dataset combining EEG, eye-tracking, and high-speed video recordings from 31 healthy participants performing motor imagery and motor execution tasks. The dataset comprises 2,520 trials across 63 sessions with 64-channel EEG recordings at 1000 Hz sampling rate, focusing on left and right hand grasping imagery. This resource supports the development and benchmarking of brain-computer interface (BCI) systems for motor control applications.
A motor imagery EEG dataset comprising 31 healthy participants performing left and right hand grasping imagery tasks across multiple sessions. The dataset includes 2,520 trials recorded at 1000 Hz using a 64-channel Neuroscan system with standardized electrode montage, designed for brain-computer interface research and motor control applications.
A code-modulated visual evoked potential (cVEP) brain-computer interface dataset from 30 healthy participants performing an offline BCI task with a calculator grid stimulus. This derivative dataset demonstrates a calibration-free approach that progressively reduces training data requirements while maintaining classification performance, ultimately achieving zero-training BCI operation through neural encoding models and reconvolution techniques.