Evidence map›Paper›PMID 42348515›Full record

ArticlePloS one2026

Steps against the burden of Parkinson's disease (StepuP): Protocol of a randomized controlled trial elucidating the biomechanical and neurophysiological mechanisms of a speed dependent treadmill training intervention.

Anina Moira van Leeuwen, Julius Welzel, Ilaria D'Ascanio, Charlotte Lang, Vaishali Vinod, Pia Görrisen, Johanna Geritz, Clint Hansen, Eran Gazit, Shahar Siman Tov and 23 more

Abstract readClinical Trial Protocol
In one paragraph

Article in PloS one, 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

33 authors.

Anina Moira van LeeuwenDepartment of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0001-9620-2990
Julius WelzelDepartment of Neurology, University Hospital Schleswig-Holstein and Kiel University, Kiel, Germany.
Ilaria D'AscanioDepartment of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy.ORCID https://orcid.org/0009-0000-1568-7149
Charlotte LangInstitute for Biomechanics, ETH Zürich, Zürich, Switzerland.
Vaishali VinodDepartment of Neurology, University Hospital Schleswig-Holstein and Kiel University, Kiel, Germany.ORCID https://orcid.org/0000-0002-2951-2208
Pia GörrisenDepartment of Neurology, University Hospital Schleswig-Holstein and Kiel University, Kiel, Germany.
Johanna GeritzDepartment of Neurology, University Hospital Schleswig-Holstein and Kiel University, Kiel, Germany.
Clint HansenDepartment of Neurology, University Hospital Schleswig-Holstein and Kiel University, Kiel, Germany.
Eran GazitCenter for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Israel.
Shahar Siman TovCenter for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Israel.
Revital PrusakCenter for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Israel.
Ilaria CasadeiIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Angela ContriIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.ORCID https://orcid.org/0000-0002-6057-6816
Francesca TampelliniIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Leonardo PellicciariIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Giovanna LopaneIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Giovanna Calandra BuonauraIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Luca PalmeriniDepartment of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy.
Noman ZahidUniversity of New South Wales, Sydney, Australia.
Mehwish MehwishUniversity of New South Wales, Sydney, Australia.
Mayna RatanaponglekaUniversity of New South Wales, Sydney, Australia.
Husna RazeeUniversity of New South Wales, Sydney, Australia.
Frederic von WegnerUniversity of New South Wales, Sydney, Australia.
Bernadette C M van WijkDepartment of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0002-6129-0801
Sjoerd M BruijnDepartment of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0003-0290-2131
Deepak K RaviInstitute for Biomechanics, ETH Zürich, Zürich, Switzerland.
Yoshiro OkuboUniversity of New South Wales, Sydney, Australia.
Navrag B SinghInstitute for Biomechanics, ETH Zürich, Zürich, Switzerland.ORCID https://orcid.org/0000-0001-8074-041X
Matthew BrodieUniversity of New South Wales, Sydney, Australia.
Fabio La PortaIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Jeffrey M HausdorffCenter for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Israel.
Walter MaetzlerDepartment of Neurology, University Hospital Schleswig-Holstein and Kiel University, Kiel, Germany.
Jaap H van DieënDepartment of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0002-7719-5585

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveParkinson's disease can impair gait and stability, leading to reduced independence and increased fall risk. While speed dependent treadmill training (SDTT) is clinically effective, the specific biomechanical and neurophysiological mechanisms driving these improvements remain unclear. The "StepuP" multicenter randomized controlled trial aims to elucidate these mechanisms and determine whether training enriched with virtual reality or mechanical perturbations (SDTT+) enhances gait efficacy and transfer to daily life.

methodsWe will recruit 126 individuals with Parkinson's disease across four clinical sites and 21 healthy older adults as a reference group. Participants will be randomized to receive either standard SDTT or SDTT+ for 12 sessions. To capture the trajectory of recovery and retention, assessments will occur at three distinct timepoints: baseline, post-intervention, and a 12-week follow-up, each assessment including synchronized 64-channel electroencephalography (EEG), electromyography (EMG), and 3D kinematics. This multimodal setup allows for the quantification of cortical beta-band activity, corticomuscular coherence, and stability-related foot placement control. Furthermore, we will assess participant's satisfaction, usability, and engagement through questionnaires and interviews to understand individual adherence and barriers to training. SIGNIFICANCE: The primary clinical endpoint is comfortable overground walking speed. We hypothesize that gait improvements are mediated by improved stability-related foot placement and cortical sensorimotor integration. By correlating lab-based mechanistic changes with real-world mobility patterns and participant experiences, this study seeks to identify specific pathophysiological mechanisms engaged during the treadmill training. These insights will help distinguish responders from non-responders, facilitating the development of personalized, acceptable, and effective rehabilitation strategies.

Indexed as

Exercise TherapyParkinson DiseaseAgedBiomechanical PhenomenaElectroencephalographyElectromyographyExercise TestFemaleGaitHumansMaleMiddle AgedRandomized Controlled Trials as Topic

Identifiers

PMID42348515
PMCPMC13298929

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Registered trials

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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.