Evidence map›Paper›PMID 25599426›Full record

ArticleSensors (Basel, Switzerland)2015

Pose estimation with a Kinect for ergonomic studies: evaluation of the accuracy using a virtual mannequin.

Pierre Plantard, Edouard Auvinet, Anne-Sophie Le Pierres, Franck Multon

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Musculoskeletal Risks: RULA Bibliometric Review.International journal of environmental research and public health · 2020
    Review
  6. Article
  7. Article
  8. Filtered pose graph for efficient kinect pose reconstruction.Multimedia tools and applications · 2017
    Article
  9. Article
  10. Article
  11. 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

4 authors.

Pierre PlantardLaboratory, University Rennes 2, ENS Rennes, Avenue Robert Schuman, 35170 Bruz, France. pierre.plantard@irisa.fr.
Edouard AuvinetEcole Polytechnique de Montréal, C.P. 6079, Succursale Centre-ville, Montréal, H3C 3A7 QC, Canada. edouard.auvinet@polymtl.ca.
Anne-Sophie Le PierresFAURECIA Automotive Seating, ZI de Brières les Scellés, B.P. 89 91152 Etampes, France. anne-sophie.lepierres@faurecia.com.
Franck MultonLaboratory, University Rennes 2, ENS Rennes, Avenue Robert Schuman, 35170 Bruz, France. Franck.Multon@irisa.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analyzing human poses with a Kinect is a promising method to evaluate potentials risks of musculoskeletal disorders at workstations. In ecological situations, complex 3D poses and constraints imposed by the environment make it difficult to obtain reliable kinematic information. Thus, being able to predict the potential accuracy of the measurement for such complex 3D poses and sensor placements is challenging in classical experimental setups. To tackle this problem, we propose a new evaluation method based on a virtual mannequin. In this study, we apply this method to the evaluation of joint positions (shoulder, elbow, and wrist), joint angles (shoulder and elbow), and the corresponding RULA (a popular ergonomics assessment grid) upper-limb score for a large set of poses and sensor placements. Thanks to this evaluation method, more than 500,000 configurations have been automatically tested, which would be almost impossible to evaluate with classical protocols. The results show that the kinematic information obtained by the Kinect software is generally accurate enough to fill in ergonomic assessment grids. However inaccuracy strongly increases for some specific poses and sensor positions. Using this evaluation method enabled us to report configurations that could lead to these high inaccuracies. As a supplementary material, we provide a software tool to help designers to evaluate the expected accuracy of this sensor for a set of upper-limb configurations. Results obtained with the virtual mannequin are in accordance with those obtained from a real subject for a limited set of poses and sensor placements.

Indexed as

ManikinsUser-Computer InterfaceAdultBiomechanical PhenomenaErgonomicsHumansJointsMovementPosture

Identifiers

PMID25599426
PMCPMC4327103

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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.