Evidence map›Paper›PMID 41413829›Full record

Trial reportJournal of neuroengineering and rehabilitation2025

Haptic interaction with a human partner for ankle training in chronic stroke: a pilot study.

Matthew R Short, Laura Bandini, Daniel Ludvig, Lorenzo Vianello, Vittorio Sanguineti, Jose L Pons

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04578665 (Human-like Robotic Controllers for Enhanced Motor Learning), which is not on this 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.

NCT04578665 nasuspendednot on this map

Human-like Robotic Controllers for Enhanced Motor Learning

TypeinterventionalSponsorShirley Ryan AbilityLabRan2021 to 2026Enrolled764ConditionsStroke, Spinal Cord InjuriesArmsBehavioral Interaction Conditions, Haptic Impedance Level, Skill Level of Partner, Robot Controller Showcase
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

6 authors.

Matthew R Short *Shirley Ryan AbilityLab, Chicago, IL, USA. matthewshort35@gmail.com.
Laura Bandini *Shirley Ryan AbilityLab, Chicago, IL, USA. laura.bandini@edu.unige.it.
Daniel LudvigShirley Ryan AbilityLab, Chicago, IL, USA.
Lorenzo VianelloShirley Ryan AbilityLab, Chicago, IL, USA.
Vittorio SanguinetiDepartment of Informatics, Bioengineering, Robotics and System Engineering, University of Genoa, Genoa, Italy.
Jose L PonsShirley Ryan AbilityLab, Chicago, IL, USA.

Funding

National Science Foundation/National Robotics Initiative 2024488
6 · The paper itself

Abstract

backgroundSensorimotor impairments following stroke frequently result in diminished voluntary control of the ankle, contributing to deficits in balance and gait. Robotic training paradigms targeting ankle motor control often use an assist-as-needed strategy, where compliant guidance is provided to assist movements towards a target trajectory. However, interaction with "perfect" reference trajectories may overly constrain movements during training and has been shown to limit learning in many upper-limb contexts; alternatives to robotic assistance have rarely been explored for post-stroke ankle training. Inspired by human-robot-human interaction studies, we investigated whether physical interaction with a therapist-termed human interaction-offers advantages over traditional trajectory guidance regarding short-term learning.

methodsIn a within-subject design, nine individuals with chronic stroke (61.6 ± 14.3 years) performed a 1-DoF visuomotor tracking task while wearing ankle robots designed to train dorsiflexion and plantarflexion movements. Two robotic training methods were evaluated in separate visits: (1) compliant connection to a sinusoidal target trajectory (i.e., trajectory guidance) and (2) compliant connection to a physical therapist who tracked the same target trajectory (i.e., human interaction). In each visit, tracking performance (i.e., errors, movement smoothness) and muscle activation were evaluated during and immediately after training.

resultsBoth training types improved tracking accuracy and movement smoothness during training, however random error was more significantly suppressed with trajectory guidance. Immediately after training, we found no significant difference in tracking accuracy or movement smoothness across training types. However, participants demonstrated significantly higher dorsiflexor activation after training with human interaction compared to trajectory guidance.

conclusionOur results suggest that human interaction is a viable strategy for training ankle movements in chronic stroke participants, likely by providing assistance without over-constraining an individual's movement smoothness or variability. Training while physically interacting with a partner could serve as an effective alternative to conventional robot-guided therapy for post-stroke ankle rehabilitation, though further studies with larger cohorts are needed to assess the generalization of this approach regarding long-term retention and functional improvement. Registry: clinicaltrials.gov, TRN: NCT04578665, Registration date: 8 October 2020.

Indexed as

AnkleRoboticsStrokeStroke RehabilitationAgedChronic DiseaseFemaleHumansMaleMiddle AgedPilot ProjectsPsychomotor PerformanceAnkleChronic strokeHuman-human physical interactionRehabilitation robotics

Identifiers

PMID41413829
PMCPMC12829194

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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.