Scholarlink

<p>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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

High-Density EEG and Multi-Muscle EMG Dataset during Object Prehension with a sensorized Grasping Box in Humans

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月18日

查看全文
  • G. Lomele,
  • T. Lencioni,
  • S. D’Ambrosio,
  • A. Comanducci,
  • F. Lucchetti,
  • A. Marzegan,
  • C. Derchi,
  • S. Garzonio,
  • T. Atzori,
  • M. Rabuffetti,
  • P. Castiglioni,
  • M. Ferrarin,
  • L. Fornia

摘要

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.