Participant 7 in the WAY-EEG-GAL dataset. 328 grasp-and-lift trials with different weights and surfaces during which EEG, EMG, kinematics, and kinetics were recorded.

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 participants performed lifting series in which the object’s weight (165, 330, or 660g), surface friction (sandpaper, suede, or silk surface), or both, were changed unpredictably between trials, thus enforcing changes in fingertip force coordination. In each of a total of 3,936 trials, the participant was cued to reach for the object, grasp it with the thumb and index finger, lift it and hold it for a couple of seconds, put it back on the support surface, release it, and, lastly, to return the hand to a designated rest position. We recorded EEG (32 channels), EMG (five arm and hand muscles), the 3D position of both the hand and object, and force/torque at both contact plates.WAY-EEG-GAL是一款专为开展关键技术验证而设计的数据集，旨在基于执行抓握-举起任务的人类受试者的头皮脑电（electroencephalogram, EEG）记录，解码其感知、意图与动作。共有12名受试者参与实验，他们完成了多组举升任务：实验中，物体的重量（165g、330g或660g）、表面摩擦力（对应砂纸、绒面革或丝绸材质表面），或两者兼具，会在各试次间随机变化，从而迫使受试者调整指尖的力量协调模式。在总计3936次试次中，每一试次都会向受试者发出动作提示：伸手抓取目标物体，以拇指与食指捏住该物体，将其举起并保持数秒，随后放回支撑平面并松开，最后将手返回至指定的休息位置。本次实验同步记录了多模态数据：32通道脑电信号、5块手臂与手部肌肉的肌电（electromyogram, EMG）信号、双手与目标物体的三维位置信息，以及两块接触板处的力与扭矩数据。