Evidence map›Paper›PMID 39409252›Full record

ArticleSensors (Basel, Switzerland)2024

Virtual Obstacle Avoidance Strategy: Navigating through a Complex Environment While Interacting with Virtual and Physical Elements.

Fabiana Machado, Matheus Loureiro, Marcio Bezerra, Carla Zimerer, Ricardo Mello, Anselmo Frizera

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Functions and Sensors of Smart Walkers From 2015 to 2024: Scoping Review.JMIR rehabilitation and assistive technologies · 2026
    Review
  2. 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

6 authors.

Fabiana MachadoGraduate Program in Informatics, Federal University of Espírito Santo, Vitória 29075-910, ES, Brazil.ORCID 0000-0003-0996-8651
Matheus LoureiroGraduate Program in Electrical Engineering, Federal University of Espírito Santo, Vitória 29075-910, ES, Brazil.
Marcio BezerraGraduate Program in Electrical Engineering, Federal University of Espírito Santo, Vitória 29075-910, ES, Brazil.
Carla ZimererGraduate Program in Electrical Engineering, Federal University of Espírito Santo, Vitória 29075-910, ES, Brazil.
Ricardo MelloGraduate Program in Electrical Engineering, Federal University of Espírito Santo, Vitória 29075-910, ES, Brazil.ORCID 0000-0003-0420-4273
Anselmo FrizeraGraduate Program in Informatics, Federal University of Espírito Santo, Vitória 29075-910, ES, Brazil.ORCID 0000-0002-0687-3967

Funding

Brazilian National Council for Scientific and Technological Development - CNPq 308155/2023-8Brazilian National Council for Scientific and Technological Development - CNPq 403753/2021-0Financiadora de Estudos e Projetos - FINEP 2784/20Fundação de Amparo à Pesquisa e Inovação do Espírito Santo - FAPES 2022-C5K3HFundação de Amparo à Pesquisa e Inovação do Espírito Santo - FAPES 2022-D48XBFundação de Amparo à Pesquisa e Inovação do Espírito Santo - FAPES 2023-XDHHW
6 · The paper itself

Abstract

Robotic walking devices can be used for intensive exercises to enhance gait rehabilitation therapies. Mixed Reality (MR) techniques may improve engagement through immersive and interactive environments. This article introduces an MR-based multimodal human-robot interaction strategy designed to enable shared control with a Smart Walker. The MR system integrates virtual and physical sensors to (i) enhance safe navigation and (ii) facilitate intuitive mobility training in personalized virtual scenarios by using an interface with three elements: an arrow to indicate where to go, laser lines to indicate nearby obstacles, and an ellipse to show the activation zone. The multimodal interaction is context-based; the presence of nearby individuals and obstacles modulates the robot's behavior during navigation to simplify collision avoidance while allowing for proper social navigation. An experiment was conducted to evaluate the proposed strategy and the self-explanatory nature of the interface. The volunteers were divided into four groups, with each navigating under different conditions. Three evaluation methods were employed: task performance, self-assessment, and observational measurement. Analysis revealed that participants enjoyed the MR system and understood most of the interface elements without prior explanation. Regarding the interface, volunteers who did not receive any introductory explanation about the interface elements were mostly able to guess their purpose. Volunteers that interacted with the interface in the first session provided more correct answers. In future research, virtual elements will be integrated with the physical environment to enhance user safety during navigation, and the control strategy will be improved to consider both physical and virtual obstacles.

Indexed as

RoboticsVirtual RealityAdultFemaleGaitHumansMaleUser-Computer InterfaceWalkingYoung Adultfeedbackmixed realitynavigationproxemicsshared controlsmart walker

Identifiers

PMID39409252
PMCPMC11479164

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.