Smart Wheelchair and Sensor System for Tracking Performance and Accessibility in Urban Environments.

Franz Konstantin Fuss, Adin Ming Tan, Oren Tirosh, Yehuda Weizman

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Franz Konstantin FussChair of Biomechanics, Faculty of Engineering Science, University of Bayreuth, D-95447 Bayreuth, Germany.ORCID 0000-0001-9846-0985

Adin Ming TanChair of Biomechanics, Faculty of Engineering Science, University of Bayreuth, D-95447 Bayreuth, Germany.

Oren TiroshSchool of Health and Biomedical Sciences, RMIT University, Bundoora, VIC 3083, Australia.ORCID 0000-0002-2281-6399

Yehuda WeizmanChair of Biomechanics, Faculty of Engineering Science, University of Bayreuth, D-95447 Bayreuth, Germany.ORCID 0000-0001-9736-8300

Funding

Swinburne University and Scope 00000

6 · The paper itself

Abstract

Wheelchair users face significant mobility limitations related to both medical issues (e.g., musculoskeletal strain, pressure ulcers) and urban accessibility challenges. This pilot study introduces a sensor system integrating an inertial measurement unit (IMU), GPS (Global Positioning System), and a pressure-measuring seat to monitor distance travelled, speed, and posture in relation to real-world conditions. Seven participants navigated an approximately 800-metre outdoor course, divided into 13 sections, while real-time data were recorded. The results showed an average speed of 1.24 ± 0.41 m/s with peak speeds of up to 2.67 m/s. The centre of pressure on the seat fluctuated by an average of 25 mm in the x and y directions (left-right: COPx, back-forward: COPy). The data for average speed, COPx, and COPy showed significant differences between most of the 13 sections, with large, very large, and huge effect sizes. Comparing the speed, COPx, and COPy data with respect to distance travelled, and correlating them between the seven participants by applying the rank-sum method to the mean R

Indexed as

WheelchairsEquipment DesignGeographic Information SystemsHumansPilot ProjectsPostureassistive technologycentre of pressureGPSinertial measurement unit (IMU)pressure sensing seat matpropulsionreal-world kinematic analysisvelocitywheelchair biomechanics

Identifiers

PMID42122380

DOI10.3390/s26092657

PMCPMC13165794

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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.