ArticleScientific data2023
A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A multimodal biomechanics dataset with synchronized kinematics and internal tissue motions during reaching.Scientific data · 2026Article
- EMG-Based Simulation for Optimization of Human-in-the-Loop Control in Simple Robotic Walking Assistance.Journal of sensor and actuator networks · 2025Article
- Reach&Grasp: a multimodal dataset of the whole upper-limb during simple and complex movements.Scientific data · 2025Article
- Assessment of upper limb motor control: establishing normative benchmarks for clinical applications.PeerJ · 2025Article
- Multisensory Evaluation of Muscle Activity and Human Manipulability during Upper Limb Motor Tasks.Biosensors · 2023Article
- A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction.Scientific data · 2023Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.