Evidence map›Paper›PMID 39982287›Full record

ArticleJournal of functional morphology and kinesiology2025

Tennis Timing Assessment by a Machine Learning-Based Acoustic Detection System: A Pilot Study.

Lucio Caprioli, Amani Najlaoui, Francesca Campoli, Aatheethyaa Dhanasekaran, Saeid Edriss, Cristian Romagnoli, Andrea Zanela, Elvira Padua, Vincenzo Bonaiuto, Giuseppe Annino

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of functional morphology and kinesiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Lucio CaprioliSports Engineering Laboratory, Department of Industrial Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.ORCID 0009-0005-4049-5225
Amani NajlaouiSports Engineering Laboratory, Department of Industrial Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.
Francesca CampoliSports Engineering Laboratory, Department of Industrial Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.ORCID 0009-0004-1342-5881
Aatheethyaa DhanasekaranSports Engineering Laboratory, Department of Industrial Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.
Saeid EdrissSports Engineering Laboratory, Department of Industrial Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.ORCID 0009-0000-0224-8294
Cristian RomagnoliDepartment of Human Science and Promotion of Quality of Life, San Raffaele Rome University, 00166 Rome, Italy.ORCID 0000-0003-0904-634X
Andrea ZanelaRobotics and Artificial Intelligence Laboratory-ENEA "Casaccia" Research Centre, 00123 Rome, Italy.ORCID 0000-0001-5606-4175
Elvira PaduaDepartment of Human Science and Promotion of Quality of Life, San Raffaele Rome University, 00166 Rome, Italy.ORCID 0000-0001-5227-2567
Vincenzo BonaiutoSports Engineering Laboratory, Department of Industrial Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.ORCID 0000-0002-2328-4793
Giuseppe AnninoHuman Performance Laboratory, Centre of Space Bio-Medicine, Department of Medicine Systems, University of Rome Tor Vergata, 00133 Rome, Italy.ORCID 0000-0001-8578-6046

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

acoustic detectionmachine learningperformance analysistennistiming

Identifiers

PMID39982287
PMCPMC11843912

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.