Evidence map›Paper›PMID 41712772›Full record

ArticleJMIR mHealth and uHealth2026

Video-Based Motion Capture Smartphone Apps for Testing Human Motor Performance Skills: Scoping Review.

Clara Sophia Zoeller, Claudia Niessner, Manuel Fleps, Thorsten Klein, Anke Hanssen-Doose, Alexander Burchartz, Alexander Woll, Thorsten Stein

Abstract readScoping Review
In one paragraph

Article in JMIR mHealth and uHealth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

8 authors.

Clara Sophia Zoeller *Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, Karlsruhe, 76131, Germany.ORCID 0009-0005-3348-6603
Claudia Niessner *Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, Karlsruhe, 76131, Germany.ORCID 0000-0003-2094-0836
Manuel FlepsInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, Karlsruhe, 76131, Germany.ORCID 0009-0007-5091-8820
Thorsten KleinInstitute of Movement and Sport, Karlsruhe University of Education, Karlsruhe, Germany.ORCID 0009-0006-5123-7755
Anke Hanssen-DooseInstitute of Movement and Sport, Karlsruhe University of Education, Karlsruhe, Germany.ORCID 0000-0002-6204-5576
Alexander BurchartzInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, Karlsruhe, 76131, Germany.ORCID 0000-0003-1338-5395
Alexander WollInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, Karlsruhe, 76131, Germany.ORCID 0000-0002-5736-2980
Thorsten SteinInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, Karlsruhe, 76131, Germany.ORCID 0000-0002-7885-7085

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Good motor performance skills (MPS) are relevant in all stages of life. Higher MPS are associated with enhanced cognitive abilities and physical and mental health. The assessment of MPS is important to identify deficits in MPS at an early stage and to implement interventions to address these deficits. One method to assess MPS is through marker-based motion capture in a laboratory setting with multiple cameras. However, this approach is expensive and time-consuming, making it impractical, for example, in large-scale studies for MPS assessment. Recent advancements (eg, artificial intelligence) in technology (eg, smartphone cameras) have opened up innovative solutions for various challenges (eg, testing large sample sizes). A potential solution is using video-based smartphone apps to assess MPS through markerless motion capture with a single camera. Objective: The objectives of this scoping review were to summarize existing smartphone apps designed to digitally assess MPS through motion capture, identify the target population of the apps, determine whether the apps have been validated, and summarize the specific MPS that were assessed. Methods: The scoping review was conducted in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines. The search was conducted in March 2024 using PubMed, Scopus, SPORTDiscus, Web of Science, Education Resources Information Centre, and SAGE Publications. All included studies investigated video-based motion capture smartphone apps to assess MPS. Results: A total of 10 studies met the inclusion criteria. Seven different smartphone apps were used within the studies, 6 of which have already been validated. The MPS assessed through the apps were gait, breaststroke, running, countermovement jump, and shoulder mobility, and 1 study assessed a functional movement test battery. The studied populations were healthy adults, older adults, athletes, or individuals with neurological illnesses. Conclusions: The assessment of MPS through smartphone apps represents a promising tool, which can be used in a variety of fields, such as health and performance monitoring, coaching, and scientific research. In the future, more studies should focus on developing new smartphone apps to assess different MPS and validate these apps.

Indexed as

Mobile ApplicationsMotion CaptureMotor SkillsVideo RecordingHumansSmartphoneAI-based motion captureartificial intelligenceathletesautomated video assessmenthealthy adultskinematicsmental healthmobile healthmotion capturemotor assessmentmotor performance skillsneurological illnessesolderphysical healthscoping reviewsmartphone app

Identifiers

PMID41712772
PMCPMC12919747

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.