Evidence map›Paper›PMID 40969319›Full record

ArticleIEEE robotics and automation letters2025

Robotic Ankle Exoskeleton and Limb Angle Biofeedback for Assisting Stroke Gait: A Feasibility Study.

Kinsey R Herrin, Yi-Tsen Pan, Trisha M Kesar, Gregory S Sawicki, Aaron J Young

Abstract read
In one paragraph

Article in IEEE robotics and automation letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

5 authors.

Kinsey R HerrinGeorge W. Woodruff School of Mechanical Engineering and the Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332.
Yi-Tsen PanGeorge W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332.
Trisha M KesarEmory University, Atlanta, GA 30322.
Gregory S SawickiGeorge W. Woodruff School of Mechanical Engineering, School of Biological Sciences and the Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332.
Aaron J YoungGeorge W. Woodruff School of Mechanical Engineering and the Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332.

Funding

Personalized Hip vs Ankle Exoskeleton Assistance with Biofeedback to Enhance Mobility Post-StrokeR01HD113598 · NICHD · GEORGIA INSTITUTE OF TECHNOLOGY · PI Trisha Kesar, Gregory Stephen Sawicki · 2024 to 2026
$1.6M
NICHD NIH HHS R01 HD113598
6 · The paper itself

Abstract

Post-stroke gait is slow, energetically costly, and unstable. Rehabilitation is necessary to encourage, retrain, and assist proper gait mechanics in stroke survivors. Evidence indicates robotic ankle exoskeletons can improve gait outcomes in stroke survivors, however challenges remain with proper lower limb positioning for optimal receipt of the assistance. Biofeedback can be used to improve positioning of the limb for receipt of robotic ankle exoskeleton assistance. In this study, four stroke survivors used bilateral powered robotic ankle exoskeletons (Dephy Exoboots) and an innovative, custom-designed vibrotactile-audio biofeedback interface targeting trailing limb angle to test the hypotheses that each intervention alone improves gait outcomes over baseline, and when combined they improve outcomes over either intervention alone. Compared to baseline, we found increases in average paretic propulsive impulse during the biofeedback-only and exoskeleton-plus-biofeedback conditions. Biofeedback alone induced the greatest increase on average self-selected walking speed, and the combination of exoskeleton assistance and biofeedback increased speed more compared to the robotic exoskeleton-only condition. Our preliminary results indicate that biofeedback in combination with a robotic exoskeleton produces greater synergistic benefits on gait performance than the use of an exoskeleton alone.

Indexed as

BiofeedbackGaitProsthetics and ExoskeletonsStrokeWearable Robotics

Identifiers

PMID40969319
PMCPMC12442855

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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.