Evidence map›Paper›PMID 38676160›Full record

ArticleSensors (Basel, Switzerland)2024

Development and Evaluation of a Hybrid Measurement System to Determine the Kinematics of the Wrist.

Jason Dellai, Martine A Gilles, Olivier Remy, Laurent Claudon, Gilles Dietrich

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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

5 authors.

Jason DellaiInstitut National de Recherche et de Sécurité (INRS), 54519 Vandoeuvre-lès-Nancy, France.
Martine A GillesInstitut National de Recherche et de Sécurité (INRS), 54519 Vandoeuvre-lès-Nancy, France.
Olivier RemyInstitut National de Recherche et de Sécurité (INRS), 54519 Vandoeuvre-lès-Nancy, France.
Laurent ClaudonInstitut National de Recherche et de Sécurité (INRS), 54519 Vandoeuvre-lès-Nancy, France.
Gilles DietrichInstitut des Sciences du Sport Santé de Paris (URP 3625), Université Paris Cité, 75015 Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optical Motion Capture Systems (OMCSs) are considered the gold standard for kinematic measurement of human movements. However, in situations such as measuring wrist kinematics during a hairdressing activity, markers can be obscured, resulting in a loss of data. Other measurement methods based on non-optical data can be considered, such as magneto-inertial measurement units (MIMUs). Their accuracy is generally lower than that of an OMCS. In this context, it may be worth considering a hybrid system [MIMU + OMCS] to take advantage of OMCS accuracy while limiting occultation problems. The aim of this work was (1) to propose a methodology for coupling a low-cost MIMU (BNO055) to an OMCS in order to evaluate wrist kinematics, and then (2) to evaluate the accuracy of this hybrid system [MIMU + OMCS] during a simple hairdressing gesture. During hair cutting gestures, the root mean square error compared with the OMCS was 4.53° (1.45°) for flexion/extension, 5.07° (1.30°) for adduction/abduction, and 3.65° (1.19°) for pronation/supination. During combing gestures, they were significantly higher, but remained below 10°. In conclusion, this system allows for maintaining wrist kinematics in case of the loss of hand markers while preserving an acceptable level of precision (<10°) for ergonomic measurement or entertainment purposes.

Indexed as

WristAdultBiomechanical PhenomenaFemaleHumansMaleMovementRange of Motion, Articularaccuracyhybrid systemMIMUoptical motion capture systemwrist kinematic

Identifiers

PMID38676160
PMCPMC11053611

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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.