Evidence map›Paper›PMID 40644231›Full record

ArticleIEEE ... International Conference on Rehabilitation Robotics : [proceedings]2025

A Customizable Fitting Protocol for the Body-Machine Interface.

Fiona A Neylon, Andrew Thompson, Rachel Kalvakota, Corinne Fischer, Fabio Rizzoglio, Lee Miller, Brenna D Argall

Abstract read
In one paragraph

Article in IEEE ... International Conference on Rehabilitation Robotics : [proceedings], 2025. 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

7 authors.

Fiona A Neylon
Andrew Thompson
Rachel Kalvakota
Corinne Fischer
Fabio Rizzoglio
Lee Miller
Brenna D Argall

Funding

Human and Machine Learning for Customized Control of Assistive RobotsR01EB024058 · NIBIB · REHABILITATION INSTITUTE OF CHICAGO D/B/A SHIRLEY RYAN ABILITYLAB · PI ARGALL, BRENNA · 2018 to 2024
$1.4M
NIBIB NIH HHS R01 EB024058
6 · The paper itself

Abstract

In this work, we present a case study evaluation that compares two methods of fitting the Body-Machine Interface (BoMI) to an individual with cervical spinal cord injury for the purpose of operating a robotic arm in 6-D. A BoMI is a control interface created by recording body movements and mapping them to the controls of a device or machine, and has shown promise for individuals with motor impairments whose access to standard interfaces is otherwise limited. Results from this case study show a one-size-fits-all placement strategy is not a sufficient fitting method for an individual with severe upper extremity limitations. However, when a flexible fitting protocol informed by a clinical evaluation is applied, we see improvement in two key categories: (1) success in map fitting and (2) robot task results. Informed by the case study analyses, we develop a novel method to customize and fit the BoMI to users in a way that is analogous to how commonly used assistive technologies are fit clinically: the BoMI Customization Evaluation (BCE). This new method of customization is determined from a physical evaluation conducted by a clinician in conjunction with participant feedback and BoMI engineers. Deployment of this novel method within a full evaluation study is underway. The current work focuses on the evolution to this protocol.

Indexed as

RoboticsSpinal Cord InjuriesUser-Computer InterfaceAdultHumansMale

Identifiers

PMID40644231
PMCPMC12558442

What OpenQuestion holds

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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.