Evidence map›Paper›PMID 35433138›Full record

ArticleIEEE transactions on human-machine systems2021

Curb Negotiation With Dynamic Human-Robotic Wheelchair Collaboration.

Jorge L Candiotti, Brandon J Daveler, Sivashankar Sivakanthan, Garrett G Grindle, Rosemarie Cooper, Rory A Cooper

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on human-machine systems, 2021. 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
1.9field-weighted citation impact, top 13% 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, 6 citations in OpenAlex.

  1. User Field Testing for Robot Wheelchairs: A Mixed-Method Approach.IEEE ... International Conference on Rehabilitation Robotics : [proceedings] · 2025
    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 at 2 institutions in 1 country.

Jorge L CandiottiCenter of Excellence in Wheelchairs and Robotics Engineering, Veterans Affairs Pittsburgh Healthcare Systems and Human Engineering Research Laboratories, Pittsburgh, PA 15206 USA.ORCID 0000-0002-4326-2022
Brandon J DavelerCenter of Excellence in Wheelchairs and Robotics Engineering, Veterans Affairs Pittsburgh Healthcare Systems and Human Engineering Research Laboratories, Pittsburgh, PA 15206 USA; School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260 USA.
Sivashankar SivakanthanCenter of Excellence in Wheelchairs and Robotics Engineering, Veterans Affairs Pittsburgh Healthcare Systems and Human Engineering Research Laboratories, Pittsburgh, PA 15206 USA; School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260 USA.ORCID 0000-0001-6121-5142
Garrett G GrindleCenter of Excellence in Wheelchairs and Robotics Engineering, Veterans Affairs Pittsburgh Healthcare Systems and Human Engineering Research Laboratories, Pittsburgh, PA 15206 USA; School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260 USA.
Rosemarie CooperCenter of Excellence in Wheelchairs and Robotics Engineering, Veterans Affairs Pittsburgh Healthcare Systems and Human Engineering Research Laboratories, Pittsburgh, PA 15206 USA; School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260 USA.
Rory A CooperCenter of Excellence in Wheelchairs and Robotics Engineering, Veterans Affairs Pittsburgh Healthcare Systems and Human Engineering Research Laboratories, Pittsburgh, PA 15206 USA; School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260 USA.ORCID 0000-0003-0405-5773
University of Pittsburgh · USVA Pittsburgh Healthcare System · US

Funding

RRD VA I50 RX002998RRD VA IK1 RX003076RRD VA IK6 RX003916
6 · The paper itself

Abstract

Wheelchair users often face architectural barriers such as curbs, limiting their accessibility, mobility, and participation in their communities. The mobility enhancement robotic (MEBot) wheelchair was developed to navigate over such architectural barriers. Its application allows wheelchair users to negotiate curbs automatically while the user remains in control. The application was optimized from a manual to a semiautomated process based on wheelchair users' feedback. The optimized application was evaluated by experienced wheelchair users who navigated over curbs of different heights. Participants evaluated MEBot in terms of effectiveness, workload demand, and usability. Ten participants successfully ascended and descended curbs of different heights at an average completion time of 55.7 ± 19.5 and 30.3 ± 9.1 s, respectively. MEBot maintained stability during the process, while participants reported low levels of effort, frustration, and overall cognitive demand to operate MEBot. Furthermore, participants were satisfied with the ease of learning and using the MEBot curb negotiation application to overcome the curbs but suggested less wheel adjustment for comfort and a faster pace to overcome curbs during real-world conditions.

Indexed as

Architectural barriershuman–robot interactionstep climbingusabilitywheelchair

Identifiers

PMID35433138
PMCPMC9009297
OpenAlexW4205486579

What OpenQuestion holds

Textmetadata
LicenceTDM
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.