Evidence map›Paper›PMID 35013870›Full record

ReviewMedical & biological engineering & computing2022

Skills assessment metrics of electric powered wheelchair driving in a virtual environment: a survey.

Angela A R de Sá, Yann Morère, Eduardo L M Naves

Open access · greenAbstract readReview
PubMed Publisher
In one paragraph

Review in Medical & biological engineering & computing, 2022. 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
0.8field-weighted citation impact, top 26% of its field
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, 7 citations in OpenAlex.

  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

3 authors at 2 institutions in 2 countries.

Angela A R de SáFaculty of Electrical Engineering, Federal University of Uberlândia, Assistive Technologies Group, Av Joao Naves de Avila, 2160 - Bloco 3N, Uberlandia, Brazil. angelaabreu@gmail.com.ORCID http://orcid.org/0000-0002-1818-8270
Yann MorèreLCOMS - Laboratoire de Conception, Optimisation Et Modélisation Des Systèmes, Université de Lorraine, 7 rue Marconi, 57070, Metz, France.ORCID http://orcid.org/0000-0002-2499-7576
Eduardo L M NavesFaculty of Electrical Engineering, Federal University of Uberlândia, Assistive Technologies Group, Av Joao Naves de Avila, 2160 - Bloco 3N, Uberlandia, Brazil.ORCID http://orcid.org/0000-0003-4175-723X
Universidade Federal de Uberlândia · BRLaboratoire de Conception et d'Intégration des Systèmes · FR

Funding

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (BR) Finance Code 001
6 · The paper itself

Abstract

The purpose of this review is to present studies on the parameters for assessing the skills of users of electric wheelchair driving simulators in a virtual environment. In addition, this study also aims to identify the most widely used and validated parameters for the quantification of electric wheelchair driving ability in a virtual environment and to suggest challenges for future research. To carry out this research, the criteria of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were adopted. Literature searches in English, French, and Portuguese were conducted up to December 2020 in the PubMed, SciELO, Science Direct, World Wide Science, and Scopus databases. The keywords used were electric wheelchair, simulator, performance indicators, performance skills, driving skills, training platform, virtual environment, and virtual reality. We excluded studies involving "real" wheelchairs without a simulator in a virtual environment. We have selected a total of 42 items. In these studies, we identified 32 parameters (3 qualitative and 29 quantitative) that are used as parameters for the evaluation of the ability to control a powered wheelchair in a virtual environment. Although the amount of research in this area has increased significantly in recent years, additional studies are still needed to provide a more accurate and objective assessment of skills among the target population. A challenge for future work is the increasing application of artificial intelligence techniques and the exploration of biomedical data measurements, which may be a promising alternative to improve the quantification of user competencies.

Indexed as

Virtual RealityWheelchairsArtificial IntelligenceHumansUser-Computer InterfaceElectric powered wheelchairSimulatorSkills drivingVirtual environment

Identifiers

PMID35013870
OpenAlexW4206209402

What OpenQuestion 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 OpenQuestion graph.