Target pose recognition (offline & HITL experiment dataset)

This dataset captures the upper limb and trunk movement kinematics, as well as surface electromyography (sEMG) data from 7 upper-arm muscles, of 10 non-disabled human subjects. The data was collected during forward-reaching actions toward 9 spatial locations in the parasagittal plane, 10 iterations for each location. The dataset can be used to analyze human movement patterns and develop algorithms for the control of movement in assistive robotic devices, such as active transhumeral prostheses.The experiment was conducted in a virtual reality (VR) environment using a head-mounted display (HMD).The spatial locations of the targets are designed to elicit specific upper limb joint displacements.The kinematics recorded include shoulder, scapular, and trunk movements.The muscles monitored include biceps brachii short/long head, triceps brachii lateral/long head, and anterior/middle/posterior deltoid.The experiment was approved by the University of Melbourne Human Research Ethics Committee, project ID 11878.For more details please refer to the GitHub repository:https://github.com/tianshi-yu/UpperLimbReachingData_HRL_Unimelb