Evidence map›Paper›PMID 41794846›Full record

ArticleScientific data2026

Kinetic Human Movement Ontology: a semantic terminology model to symbolically represent physiological movement.

Muhammad Amith, Vivian Ha, Eloisa Nguyen, Yang Gong, Ahsiya Lin, Cui Tao, Licong Cui

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Muhammad Amith *Department of Biostatistics and Data Science, University of Texas Medical Branch, 301 University Blvd, Galveston, 77555, Texas, USA. muamith@utmb.edu.ORCID http://orcid.org/0000-0003-4333-1857
Vivian Ha *Wiess School of Natural Sciences & Department of Kinesiology, Rice University, 6100 Main Street, Houston, 77005-1827, Texas, USA.
Eloisa Nguyen *Seattle Pacific University, 3307 3rd Ave West, Seattle, 98119-1997, WA, USA.
Yang GongMcWilliams School of Biomedical Informatics, University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, 77033, Texas, USA.
Ahsiya LinOntoData Research and Solutions LLC, Bethesda, Maryland, 20817, USA.ORCID http://orcid.org/0000-0003-2620-0345
Cui TaoDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Jacksonville, 32224, Florida, USA.
Licong CuiMcWilliams School of Biomedical Informatics, University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, 77033, Texas, USA. licong.cui@uth.tmc.edu.

Funding

Standardizing and Harmonizing Behavioral and Social Science Research Factors in Alzheimer's Disease through Ontology-Based ApproachesU01AG088076 · NIA · MAYO CLINIC JACKSONVILLE · PI Jiang Bian, Cui Tao · 2024 to 2026
$2.3M
AHRQ HHS R01 HS027846Cancer Prevention and Research Institute of Texas (Cancer Prevention Research Institute of Texas) RP210042Cancer Prevention and Research Institute of Texas (Cancer Prevention Research Institute of Texas) RP220244NIA NIH HHS U01 AG088076U.S. Department of Health & Human Services | Agency for Healthcare Research and Quality (AHRQ) R01HS027846U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) U01AG088076
6 · The paper itself

Abstract

Cataloging physiological and anatomical terminologies may provide a fundamental basis for bridging the involvement of muscles, skeletal, and other essential parts in human movement, in addition to understanding their role on human morbidity. We present a general formalized ontology model that focuses on anatomical and physiological entities that are active during human movement, called the Kinetic Human Movement Ontology (KHMO). We developed a model to represent human movement that links human postures using OWL2. We used the model to assemble various open-sourced controlled terminologies involved in human movement - anatomical entities, physiological terms, etc. KHMO presents 1954 classes, 42 properties, and 1921 logical axioms, and passed logical satisfiability and consistency tests. Compared to physical activity-related ontologies, KHMO exhibited high semiotic quality, including high domain coverage. KHMO is publicly available as an open-source resource on our GitHub repository, and we provide software for data management of our ontology model. We envision furthering the research of our work to interoperate with human data movement and for data curation and harmonization endeavors.

Indexed as

Biological OntologiesMovementHumansSemanticsTerminology as Topic

Identifiers

PMID41794846
PMCPMC13144411

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.