"REH-MI: EEG Motor Imagery Dataset from the Same Limb for Rehabilitation Applications"

"The REH-MI dataset is an EEG motor imagery (MI) dataset developed for rehabilitation-oriented research. It comprises 9,180 trials recorded using a 32-channel Emotiv EPOC Flex headset from 18 healthy, right-handed male participants across two sessions. Each trial corresponds to one of four right-hand conditions: imagined finger movement, wrist movement, elbow flexion, or rest, totaling 510 trials per subject. The data collection protocol incorporated signal quality checks, including impedance monitoring and electrode placement verification, followed by bad-trial flagging and classification-based validity checks after recording. REH-MI addresses the scarcity of same-limb MI datasets aimed at post-stroke rehabilitation and is expected to support studies in BCI-driven neurorehabilitation, assistive technology, and motor-function decoding."

REH-MI数据集是一款面向康复研究开发的脑电运动想象（EEG motor imagery, MI）数据集。该数据集包含9180个试次，由32通道Emotiv EPOC Flex头戴式设备采集，受试者为18名健康右利手男性，实验分为两个时段。每个试次对应四类右手相关任务之一：想象手指运动、腕部运动、肘部屈曲或静息状态，每名受试者总计完成510个试次。数据采集流程包含信号质量校验环节，具体包括阻抗监测与电极放置验证；采集完成后，还会进行坏试次标记以及基于分类的有效性验证。REH-MI数据集弥补了面向脑卒中后康复的同侧肢体运动想象数据集的稀缺性，有望为脑机接口（Brain-Computer Interface, BCI）驱动的神经康复、辅助技术以及运动功能解码相关研究提供支撑。

搜集汇总

背景与挑战

背景概述

REH-MI是一个专为康复研究设计的EEG运动想象数据集，包含9,180个试验，使用32通道设备从18名健康右利手男性参与者记录，覆盖四种右手运动想象任务（手指、手腕、肘部运动和休息）。该数据集通过严格的信号质量检查确保数据有效性，旨在解决同一肢体运动想象数据稀缺问题，支持BCI驱动的神经康复和辅助技术研究。