KIMHu: A Kinematic, Imaging and electroMyography dataset for Human muscular manipulation index prediction

  1. Hernández, Óscar G. 1
  2. Lopez-Castellanos, Jose M. 1
  3. Jara, Carlos A. 1
  4. Garcia, Gabriel J. 1
  5. Ubeda, Andres 1
  6. Morell-Gimenez, Vicente 1
  7. Gomez-Donoso, Francisco 1
  1. 1 Universitat d'Alacant
    info

    Universitat d'Alacant

    Alicante, España

    ROR https://ror.org/05t8bcz72

Éditeur: Science Data Bank

Année de publication: 2023

Type: Dataset

CC0 1.0

DOI: 10.57760/SCIENCEDB.01902 lock_openAccès ouvert editor

Résumé

Human Muscular Manipulability is a metric that measures the comfort of an specific pose and it can be used for a variety of applications related to healthcare. For this reason, we introduce 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. The methodology followed to acquire and process the data is also presented for future replication. A specific analysis framework for Human Muscular Manipulability is proposed in order to provide benchmarking tools based on this dataset.Changes in version 2 are reflected only in the dataset description, general information and list of authors