Evidence map›Paper›PMID 41159116›Full record

ArticleData in brief2025

LSC-54: A landmark-based dataset for colombian sign language.

Juan E Mora-Zarate, Claudia L Garzón-Castro, Jorge A Castellanos-Rivillas

Abstract read
In one paragraph

Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Juan E Mora-ZarateResearch Group CAPSAB, Universidad de La Sabana, Engineering Faculty, Chía, Cundinamarca Colombia.
Claudia L Garzón-CastroResearch Group CAPSAB, Universidad de La Sabana, Engineering Faculty, Chía, Cundinamarca Colombia.
Jorge A Castellanos-RivillasUniversidad de La Sabana, Engineering Faculty, Chía, Cundinamarca Colombia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

According to the World Health Organization, hearing disabilities are increasing globally, highlighting the need to support the deaf community. In countries such as Colombia, access to sign language education remains limited. Recent advances in Computer Vision have proven effective in promoting sign language learning through real-time interaction. In response to this need, a time-series dataset was developed to represent signs from Colombian Sign Language (CSL), including 11 colors, 33 courtesy phrases, and the numbers 1-10. This dataset served as input for the development of a technological tool aimed at supporting the teaching of CSL vocabulary. It includes both static and dynamic signs, represented as 3D coordinate data of the face, torso and hands. The dataset was built using recordings from 22 participants, each performing sign between three to five times. To increase data diversity and improve model performance, the dataset was augmented by a factor of 45. The data acquisition process involved: A user interface for recording sign language videos; post-processing (extracting coordinates via MediaPipe, and imputing missing hand data), and storing processed data in JSON files.

Indexed as

Colombian sign languageComputer VisionDeafnessPose estimationSign language recognition

Identifiers

PMID41159116
PMCPMC12557509

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.