A Kinematic, Imaging and Electromyography Dataset for Human Muscular Manipulability Index Prediction

Overview

Journal Sci Data

Specialty Science

Date 2023 Mar 11

PMID 36906700

Authors

Oscar G Hernandez

Jose M Lopez-Castellanos

Carlos A Jara

Gabriel J Garcia

Andres Ubeda

Vicente Morell-Gimenez

Francisco Gomez-Donoso

Affiliations

Soon will be listed here.

Abstract

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.

Citing Articles

Reach&Grasp: a multimodal dataset of the whole upper-limb during simple and complex movements.

Di Domenico D, Forsiuk I, Muller-Cleve S, Tanzarella S, Garro F, Marinelli A Sci Data. 2025; 12(1):233.

PMID: 39920160 PMC: 11805991. DOI: 10.1038/s41597-025-04552-5.

Multisensory Evaluation of Muscle Activity and Human Manipulability during Upper Limb Motor Tasks.

Lopez-Castellanos J, Ramon J, Pomares J, Garcia G, Ubeda A Biosensors (Basel). 2023; 13(7).

PMID: 37504097 PMC: 10377320. DOI: 10.3390/bios13070697.

A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction.

Hernandez O, Lopez-Castellanos J, Jara C, Garcia G, Ubeda A, Morell-Gimenez V Sci Data. 2023; 10(1):132.

PMID: 36906700 PMC: 10008528. DOI: 10.1038/s41597-023-02031-3.

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