Evidence map›Paper›PMID 41709873›Full record

ArticlePNAS nexus2026

Projecting the new body: How body image evolves during learning to walk with a wearable robot.

I-Chieh Lee, Huan Min, Ming Liu, He Huang

Abstract read
In one paragraph

Article in PNAS nexus, 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.

I-Chieh LeeLampe Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, USA.ORCID https://orcid.org/0000-0001-7094-6270
Huan MinLampe Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, USA.ORCID https://orcid.org/0009-0009-3615-868X
Ming LiuLampe Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, USA.ORCID https://orcid.org/0000-0003-0998-4221
He HuangLampe Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, USA.ORCID https://orcid.org/0000-0001-5581-1423

Funding

Toward Restoration of Normative Postural Control and Stability using Neural Control of Powered Prosthetic AnklesR01HD110519 · NICHD · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI He Huang · 2023 to 2026
$2.5M
NICHD NIH HHS R01 HD110519
6 · The paper itself

Abstract

Advances in wearable robotics challenge the traditional definition of human motor systems, as wearable robots redefine body structure, movement capability, and wearers' perception of their bodies. While these devices can empower the wearer's motor performance, there is limited understanding of how they affect the wearer's conscious, subjective experience of their own body (or body image), especially with regard to dynamic movements. This study examined changes in perceived body image as individuals learned to walk with a robotic leg over multi-day training. We measured gait performance and perceived body image via the selected coefficient of perceived motion after each training session. By extending human motor learning theory to wearer-robot systems, we hypothesized that perceived body image when walking with a robotic leg co-evolves with actual gait improvement and becomes more certain and more accurate to actual motion. Our results confirmed that motor learning improved both physical and perceived gait patterns toward normal, indicating that via practice the wearers incorporated the robotic leg into their sensorimotor systems to improve wearer-robot movement coordination. However, a persistent discrepancy between perceived and actual motion remained, likely due to the absence of direct sensation/control of the prosthesis. Additionally, the perceptual overestimation at later training sessions might limit further motor improvement. These findings suggest that enhancing the human sense of wearable robots and frequently calibrating the perception of body image are essential for effective training with wearable robots and for developing embodied assistive technologies.

Indexed as

human–robot interactionlearning robotic deviceperception of body imagepowered prosthetic leg

Identifiers

PMID41709873
PMCPMC12910506

What OpenQuestion holds

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LicenceCC BY-NC
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.