EEG-EMG-WristMotion Dataset

<pre>The goal of this experiment is to identify potential biomarkers in EEG and EMG signals that, combined with wrist kinematic data, enable an objective assessment of motor performance during wrist-related tasks.<br><br>To achieve this, we used the Biomech Wrist—a 3-degree-of-freedom wrist rehabilitation exoskeleton designed to support Flexion-Extension, Ulnar-Radial Deviation, and Pronation-Supination movements. The device is integrated with a virtual interface that allows users to control an on-screen cursor.<br><br>During the task, visual targets appear at various positions on the screen, and participants are instructed to move the cursor toward each target. Throughout the experiment, EEG signals from the motor cortex, EMG signals from four primary muscles involved in Flexion-Extension and Ulnar-Radial Deviation, and wrist joint angles from the exoskeleton's motor encoders are simultaneously recorded.<br></pre>

本实验旨在识别脑电图（EEG）与肌电图（EMG）信号中的潜在生物标志物，结合手腕运动学数据，实现腕部相关任务中运动表现的客观评估。<br><br>为达成该研究目标，本研究采用了生物力学手腕康复外骨骼（Biomech Wrist）——一款具备三自由度的康复设备，可支持屈伸（Flexion-Extension）、尺偏-桡偏（Ulnar-Radial Deviation）以及旋前-旋后（Pronation-Supination）三类运动。该设备集成了虚拟交互界面，允许使用者操控屏幕光标。<br><br>实验过程中，屏幕上将呈现不同位置的视觉靶标，参与者需将光标移动至各对应靶标处。在整个实验周期内，研究人员将同步采集运动皮层的脑电图信号、参与屈伸与尺偏-桡偏运动的四块主要肌肉的肌电图信号，以及该外骨骼电机编码器采集的腕关节角度数据。

搜集汇总

背景与挑战

背景概述

该数据集旨在通过EEG和EMG信号结合手腕运动学数据，评估手腕相关任务中的运动表现。实验使用Biomech Wrist外骨骼设备，记录运动皮层EEG信号、主要肌肉EMG信号以及手腕关节角度，用于研究神经生物标志物。数据集涉及多模态记录，适用于神经学和神经肌肉疾病研究。