WAY-EEG-GAL is a dataset designed to allow critical tests of techniques to decode sensation, intention, and action from scalp EEG recordings in humans who perform a grasp-and-lift task. Twelve partici
Brain-computer interface (BCI) enables bodyless communication with machines or devices; this is done using the translation of the electrical activity in the brain (EEG) signals into outputs command. M
Dataset Overview This dataset contains electroencephalographic (EEG) recordings from participants performing motor imagery (MI) for biological limbs (left and right arms) and a novel extra virtual ar
BNCI2003_IVa Motor Imagery数据集是一个包含脑电图（EEG）信号的数据集，主要用于视觉运动想象任务的研究。数据集包含5名健康受试者的5次记录，每次记录使用118个通道，采样率为100 Hz。数据集的总时长为4小时，大小为492.7 MB。数据集的许可证为CC-BY-4.0，适用于脑机接口（BCI）和神经科学研究。数据集可以通过EEGDash工具加载，支持PyTorch和br
