A Kinematic, Imaging And Electromyography Dataset For Human Muscular Manipulability Index Prediction

This article introduces KIMHu, a Kinematic, Imaging and electroMyography dataset for Human Muscular Manipulability index prediction. The dataset is comprised of images, depth maps, skeleton tracking data, electromyography recordings and 3 different Human Muscular Manipulability indexes of 20 participants performing different physical exercises with their arm. A specific analysis framework for Human Muscular Manipulability is proposed in order to provide benchmarking tools based on this dataset. Being able to estimate the Human Muscular Manipulability (HMM) index is very useful for a range of different tasks.