Evidence map›Paper›PMID 42197904›Full record

ArticleSensors (Basel, Switzerland)2026

Biomechanical Analysis of the Field Hockey Sweep Skill Using Inertial Measurement Units.

Hillary Cox, Rachel V Vitali

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

2 authors.

Hillary CoxDepartment of Mechanical Engineering, University of Iowa, Iowa City, IA 52242, USA.
Rachel V VitaliDepartment of Mechanical Engineering, University of Iowa, Iowa City, IA 52242, USA.ORCID 0000-0002-1436-6148

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable sensors like inertial measurement units (IMUs) can quantify sport technique in natural settings, yet field hockey-specific skill analyses remain limited. This exploratory study investigated how relative foot placement, stick orientation, and lower body kinematics at impact relate to performance of the field hockey sweep skill. Eight experienced female participants performed sweeps under three foot positions relative to the ball (in front, in line, and behind) while IMUs recorded body segment and stick motion. Sweep performance was characterized by accuracy, bounciness, and ball speed. Placing the foot in front of the ball was associated with reduced ball speed and a trend toward lower accuracy relative to the in-line reference, whereas placing the foot behind the ball did not differ from in line on any outcome. Stick roll at impact emerged as a consistent trial-level predictor, with a more open face associated with a greater likelihood of a bouncy sweep and slightly increasing ball speed. Stick pitch and lower limb joint angles were not significant within-participant predictors. However, between-participant analyses indicated that larger knee angles and smaller hip angles were associated with greater accuracy, while smaller average pitch was associated with faster ball speed. Together, these findings indicate that some aspects of sweep performance are amenable to immediate technique adjustments whereas others reflect stable individual movement tendencies. These findings provide a foundation for future work on offering evidence-based guidance for technique refinement and potential implications for injury risk reduction.

Indexed as

HockeyAdultBiomechanical PhenomenaFemaleHumansMovementWearable Electronic Devicesfield hockeyinertial measurement unitsport performancewearable sensors

Identifiers

PMID42197904
PMCPMC13210656

What OpenQuestion holds

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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.