Evidence map›Paper›PMID 41602810›Full record

ArticleFrontiers in sports and active living2025

Reliability assessment of markerless technologies in biomechanical motion analysis: a performance comparison.

Ibrahim Cem Balci, Irem Sayin, Serkan Salturk, Rana Gursoy, Umut Ozsoy, Husnu Caglar Dogru, Gokhan Akca, Ali Eraslan, Onurcan Sahin, Ali Anil Demircali and 1 more

Abstract read
In one paragraph

Article in Frontiers in sports and active living, 2025. 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. Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026
    Review
  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

11 authors.

Ibrahim Cem Balci *Department of Mechatronics Engineering, Yildiz Technical University, Istanbul, Türkiye.
Irem Sayin *Department of Mechatronics Engineering, Yildiz Technical University, Istanbul, Türkiye.
Serkan SalturkDepartment of Informatics, Yildiz Technical University, Istanbul, Türkiye.
Rana GursoyDepartment of Mechatronics Engineering, Yildiz Technical University, Istanbul, Türkiye.
Umut OzsoyDepartment of Anatomy, Akdeniz University, Antalya, Türkiye.
Husnu Caglar DogruFaculty of Communication/Radio, Television and Cinema, Canakkale Onsekiz Mart University, Canakkale, Türkiye.
Gokhan AkcaFaculty of Communication/Radio, Television and Cinema, Canakkale Onsekiz Mart University, Canakkale, Türkiye.
Ali EraslanDepartment of Sports Medicine, University of Health Sciences, Antalya Training and Research Hospital, Antalya, Türkiye.
Onurcan SahinDepartment of Mechatronics Engineering, Yildiz Technical University, Istanbul, Türkiye.
Ali Anil DemircaliDepartment of Metabolism, Digestion, and Reproduction, Faculty of Medicine, Imperial College London, London United Kingdom.
Huseyin UvetDepartment of Mechatronics Engineering, Yildiz Technical University, Istanbul, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Body tracking systems are utilized in various areas such as health and sports. In these areas, it is crucial to identify the most accurate and appropriate system for the intended design of the study. Methods: This study evaluates the reliability of markerless motion capture systems compared to a marker-based system (OptiTrack) as the gold standard. The systems assessed include StereoLabs ZED 2i, MediaPipe (2D and 3D), and YOLOv8 Pose (8n and 8x-p6). Simple upper and lower limb movements were analyzed under controlled conditions in a single participant. Intraclass Correlation Coefficient (ICC) values and Bland-Altman analysis were mainly used to evaluate agreement between systems, with some other techniques explored to provide additional perspective. Results: The results indicate that StereoLabs ZED 2i achieved the highest reliability among markerless systems (ICC: 0.92 for multi camera, 0.88 for single stereo camera), while MediaPipe 2D showed competitive performance (ICC: 0.85). Discussion: In providing comprehensive evaluations and uncovering performance differences that have been largely overlooked in the literature, our work not only questions existing paradigms but also lays a foundation for future research aimed at developing precise and scalable motion-tracking technologies. These findings contribute to understanding the applicability of markerless technologies in biomechanics.

Indexed as

artificial intelligence in sportsbody trackingmarker-based motion capturemarkerless motion capturemotion analysispose estimationreliability assessmentsports technology

Identifiers

PMID41602810
PMCPMC12833419

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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.