Kirti0111/emg-imu-fatigue-aware-gesture-dataset

FATIGUE-GR数据集是一个多模态数据集，专为扩展的人机交互中的疲劳感知手势识别而设计。该数据集通过Delsys Avanti EMG和IMU传感器从41名参与者在虚拟现实（VR）环境中的互动中收集数据。参与者在虚拟现实中玩五种不同的VR游戏，每种游戏由一种特定的手部手势控制，包括空气点击、滑动、捏合、握拳和抓取。每场比赛持续20分钟，参与者在每20秒使用Borg CR量表（0-10）报告他们的主观疲劳感。数据收集分为两个阶段进行，每个手势之间有10分钟的休息时间，两个阶段之间至少有2小时的间隔，以减少疲劳的延续。这种设置允许研究人员分析在真实的VR互动中随时间的推移疲劳进展和手势识别的情况。

The FATIGUE-GR dataset is a multimodal dataset designed for fatigue-aware gesture recognition in extended human-computer interaction. The data was collected from 41 participants using Delsys Avanti EMG and IMU sensors while interacting in a virtual reality (VR) environment. Participants played five VR games, each controlled by a distinct hand gesture: air tap, swipe, pinch, fist, and grab. Each game lasted up to 20 minutes, and participants reported their subjective fatigue every 20 seconds using the Borg CR scale (0–10). The data collection was conducted in two sessions with a 10-minute break between consecutive gestures and a minimum 2-hour gap between the two sessions to reduce carryover fatigue. This setup allows researchers to analyze fatigue progression and gesture recognition over time in realistic VR interactions.