Understanding how cortical areas control prehension movements requires synchronized neural and muscular data. For this aim, we introduce a novel open-access dataset of synchronized EEG and EMG recordings during prehension movements. The dataset combines high-density EEG (64 channels) with EMG recordings from 13 upper-limb muscles collected during prehension movements associated with 3 grip types: precision grip (thumb–index, PG), whole-hand power grasp (WH), and an unconventional grip (thumb–ring finger, UG). Data were acquired from 14 healthy participants performing visually guided prehension using a custom sensorized device that precisely timestamps action events, including go signals, object contacts, and lift completions. Each trial was divided into a dynamic phase (reaching, grasping, lifting) and a final isometric phase (holding), enabling investigation of transient and sustained motor activity. The extensive multi-muscle EMG recordings allow extraction of muscle synergy patterns that can be analyzed alongside EEG features to study cortico-muscular interactions. This dataset supports research on the neural control of complex hand movements, sensorimotor integration, and adaptive brain–computer interfaces. It provides a comprehensive resource for neuroscientists, engineers, and clinicians interested in motor control and its translation into rehabilitation practice.
Lomele et al. (2026) studied this question.