Evidence map›Paper›PMID 42655391›Full record

ArticleSensors (Basel, Switzerland)2026

Effects of Different Marker Set Configurations on Tennis Stroke Recognition Performance: A Three-Dimensional Kinematic Study Based on MiniRocket.

Qiang Xu, Dian Jiao, Yuanwu Zhu, Yiqing Wang, Yunchao Ma

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. 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

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

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

5 authors.

Qiang XuCollege of P.E. and Sports, Beijing Normal University, Beijing 100875, China.
Dian JiaoCollege of P.E. and Sports, Beijing Normal University, Beijing 100875, China.
Yuanwu ZhuCollege of P.E. and Sports, Beijing Normal University, Beijing 100875, China.
Yiqing WangCollege of Systems and Society, Australian National University, Canberra, ACT 2601, Australia.
Yunchao MaCollege of P.E. and Sports, Beijing Normal University, Beijing 100875, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Three-dimensional motion capture provides high-fidelity kinematic trajectories, but the extent to which different marker configurations retain discriminative information for tennis stroke recognition remains unclear. This study combined 3D motion capture with MiniRocket to compare seven upper-limb and racket marker configurations using data from 40 tennis-trained participants, 13 stroke types, and 10,133 valid movement samples. The configurations were the full-information group (ALL), full-arm group (AB), forearm group (FA), forearm + racket group (FR), upper-arm group (UA), racket group (RK), and watch group (WT). Model performance was evaluated using leave-one-subject-out cross-validation. All configurations achieved high performance in the three-class task. In the 13-class task, Macro-F1 was highest for ALL (78.76%), followed closely by FR (78.71%) and RK (78.28%). Holm-adjusted pairwise comparisons showed no significant differences among ALL, FR, and RK. FR significantly outperformed AB, FA, UA, and WT, whereas RK significantly outperformed FA, UA, and WT. Serve and overhead strokes were easiest to recognize, while several fine-grained baseline and net-play strokes showed lower F1-scores. These findings indicate that discriminative information is more strongly represented in the forearm-wrist-racket chain rather than simply increasing with marker count.

Indexed as

TennisAdultBiomechanical PhenomenaFemaleHumansMaleMotion CaptureMovementaction recognitionmachine learningmarker-set configurationMiniRockettennisthree-dimensional motion capture

Identifiers

PMID42655391
PMCPMC13517808

What Socratic holds

Textmetadata
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 Socratic graph.