Evidence map›Paper›PMID 41540429›Full record

ArticleBiomedical engineering online2026

Standing balance therapy through portable and low-cost visual feedback training.

Mohammad Shushtari, William Pei, Derrick Lim, Kei Masani

Abstract read
In one paragraph

Article in Biomedical engineering online, 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.

Mohammad ShushtariInstitute of Biomedical Engineering, University of Toronto, 172 St. George St., Toronto, Ontario, M5R 0A3, Canada.
William PeiInstitute of Biomedical Engineering, University of Toronto, 172 St. George St., Toronto, Ontario, M5R 0A3, Canada.
Derrick LimInstitute of Biomedical Engineering, University of Toronto, 172 St. George St., Toronto, Ontario, M5R 0A3, Canada.
Kei MasaniInstitute of Biomedical Engineering, University of Toronto, 172 St. George St., Toronto, Ontario, M5R 0A3, Canada. k.masani@utoronto.ca.

Funding

Natural Sciences and Engineering Research Council of Canada DG RGPIN-2017- 06790Natural Sciences and Engineering Research Council of Canada PDF-587753 -2024Praxis Spinal Cord Institute Funding G2020-34
6 · The paper itself

Abstract

Individuals with incomplete spinal cord injury (iSCI) often fall due to decreased sensorimotor integration. Functional electrical stimulation (FES) therapy combined with visual feedback balance training (VFBT), termed FES+VFBT, can effectively improve standing balance in iSCI populations. Although promising, the need for force plates (FP), which are expensive and bulky, limits the translation of these methods to clinical and home settings. In this work, we propose a solution by replacing FP with Wii Balance Board (WBB), allowing for more accessible FES+VFBT at a lower cost in both clinical and community settings. Our investigations on ten non-injured participants reveal that WBB-based estimated center of mass (COM) has low prediction error and high correlation in both anteroposterior (RMSE: 4.13 ± 0.69 mm, r: 0.94 ± 0.02) and mediolateral directions (RMSE: 6.25 ± 1.80 mm, r: 0.92 ± 0.04) with ground FP-estimated COM, resulting in similar stimulation patterns obtained with the WBB-based approach, indicating that the WBB-based FES+VFBT system could yield a more accessible therapeutic strategy for balance rehabilitation in iSCI.

Indexed as

Costs and Cost AnalysisElectric Stimulation TherapyFeedback, SensoryPostural BalanceStanding PositionHumansBalanceRehabilitationVisual feedback training

Identifiers

PMID41540429
PMCPMC12903637

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.