Evidence map›Paper›PMID 37873204›Full record

ArticlebioRxiv : the preprint server for biology2023

Gait adaptation to asymmetric hip stiffness applied by a robotic exoskeleton.

Banu Abdikadirova, Mark Price, Jonaz Moreno Jaramillo, Wouter Hoogkamer, Meghan E Huber

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Banu AbdikadirovaDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003 USA.
Mark PriceDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003 USA.
Jonaz Moreno JaramilloDepartment of Kinesiology, University of Massachusetts Amherst, Amherst, MA 01003 USA.
Wouter HoogkamerDepartment of Kinesiology, University of Massachusetts Amherst, Amherst, MA 01003 USA.
Meghan E HuberDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003 USA.
University of Massachusetts Amherst · US

Funding

Portable, robotic footwear for real-time control of foot-ground stiffnessR21EB033450 · NIBIB · UNIVERSITY OF MASSACHUSETTS AMHERST · PI HOOGKAMER, WOUTER, HUBER, MEGHAN E · 2022 to 2024
$613k
NIBIB NIH HHS R21 EB033450
6 · The paper itself

Abstract

Wearable exoskeletons show significant potential for improving gait impairments, such as interlimb asymmetry. However, a more profound understanding of whether exoskeletons are capable of eliciting neural adaptation is needed. This study aimed to characterize how individuals adapt to bilateral asymmetric joint stiffness applied by a hip exoskeleton, similar to split-belt treadmill training. Thirteen unimpaired individuals performed a walking trial on the treadmill while wearing the exoskeleton. The right side of the exoskeleton acted as a positive stiffness torsional spring, pulling the thigh towards the neutral standing position, while the left acted as a negative stiffness spring pulling the thigh away from the neutral standing position. The results showed that this intervention applied by a hip exoskeleton elicited adaptation in spatiotemporal and kinetic gait measures similar to split-belt treadmill training. These results demonstrate the potential of the proposed intervention for retraining symmetric gait.

Indexed as

Asymmetric gaitgait rehabilitationhip exoskeletonlocomotionneuromotor adaptation

Identifiers

PMID37873204
PMCPMC10592753
OpenAlexW4387535871

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.