Khan Asad Mansoor, Khawaja Sajid Gul, Akram Muhammad Usman, Khan Ali Saeed
Department of Computer and Software Engineering, CEME, National University of Sciences and Technology, Islamabad, Pakistan.
Data Brief. 2020 Nov 19;33:106543. doi: 10.1016/j.dib.2020.106543. eCollection 2020 Dec.
In this paper, we present the data set of surface electromyography (sEMG) and an Inertial Measurement Unit (IMU) against human muscle activity during routine activities. The Myo Thalamic Armband is used to acquire the signals from muscles below the elbow. The dataset comprises of raw sEMG, accelerometer, gyro and derived orientation signals for four different activities. The four activities, which are selected for this dataset acquisition, are resting, typing, push up exercise and lifting a heavy object. Therefore, there are five associated files against each activity. The IMU data can be fused with the sEMG data for better classification of activities especially to separate aggressive and normal activities. The data is valuable for researchers working on assistive computer aided support systems for subjects with disabilities due to physical or mental disorder.
在本文中，我们展示了在日常活动期间针对人体肌肉活动的表面肌电图（sEMG）和惯性测量单元（IMU）数据集。肌电丘脑臂带用于采集肘部以下肌肉的信号。该数据集包括四种不同活动的原始sEMG、加速度计、陀螺仪和派生的方向信号。为该数据集采集所选的四种活动为休息、打字、俯卧撑运动和举重物。因此，每种活动有五个相关文件。IMU数据可与sEMG数据融合，以更好地对活动进行分类，特别是区分剧烈活动和正常活动。该数据对于致力于为因身体或精神障碍而残疾的受试者提供辅助计算机辅助支持系统的研究人员来说很有价值。
