Literature DB >> 35664504

Quantitative assessment of training effects using EksoGT® exoskeleton in Parkinson's disease patients: A randomized single blind clinical trial.

M Romanato1, F Spolaor1, C Beretta2, F Fichera2, A Bertoldo1, D Volpe2, Z Sawacha1,3.   

Abstract

Background: Gait alterations are among the most disabling motor-symptoms associated with Parkinson's Disease (PD): reduced stride length, stride velocity and lower limb joint range of motion are hallmarks of parkinsonian gait. Research focusing on optimal functional rehabilitation methods has been directed towards powered lower-limb exoskeletons which combines the advantages delivered from the grounded robotic devices with the ability to train the patient in a real-world environment. As gait involves both central (CNS) and peripheral nervous systems (PNS), targeted rehabilitation must restore not only mechanics but also neurophysiological gait patterns.
Methods: Two cohorts of subjects will be enrolled and equally distributed between one group (n = 25) who will undergo a functional kinematic therapy, and one group (n = 25) who will undergo an overground wearable-exoskeleton training. Participants are evaluated at three time points: before the therapy (T0), after the therapy (T1), 4-weeks after T1 (T2). Comprehensive gait analysis and surface electromyography will be combined into neuromusculoskeletal modelling to determine modifications at the PNS level. Functional magnetic resonance imaging coupled with electroencephalography will be used to determine modifications at the CNS level.
Conclusion: The findings of the proposed trial will likely give substantial solutions for the management of gait and postural disorders in PD where valid interventions are lacking. The coupling of movement evaluation, which assesses neuromuscular and biomechanical features, with neurological data, will better define the impact of the therapy on the relationship between PD motor alterations and brain activity. This will provide an active treatment that is personalized and shared to large populations.
© 2022 Published by Elsevier Inc.

Entities:  

Keywords:  Clinical gait analysis; Neurophysiological assessment; Parkinson's disease; Rehabilitation; robotic gait training

Year:  2022        PMID: 35664504      PMCID: PMC9156880          DOI: 10.1016/j.conctc.2022.100926

Source DB:  PubMed          Journal:  Contemp Clin Trials Commun        ISSN: 2451-8654


  36 in total

1.  Brain Network Connectivity and Topological Analysis During Voluntary Arm Movements.

Authors:  Silvia Francesca Storti; Emanuela Formaggio; Paolo Manganotti; Gloria Menegaz
Journal:  Clin EEG Neurosci       Date:  2015-08-05       Impact factor: 1.843

2.  Estimation of musculotendon parameters for scaled and subject specific musculoskeletal models using an optimization technique.

Authors:  Luca Modenese; Elena Ceseracciu; Monica Reggiani; David G Lloyd
Journal:  J Biomech       Date:  2015-11-18       Impact factor: 2.712

3.  Comparison of lower limb muscle strength between diabetic neuropathic and healthy subjects using OpenSim.

Authors:  Alessandra Scarton; Ilse Jonkers; Annamaria Guiotto; Fabiola Spolaor; Gabriella Guarneri; Angelo Avogaro; Claudio Cobelli; Zimi Sawacha
Journal:  Gait Posture       Date:  2017-07-31       Impact factor: 2.840

4.  The Activities-specific Balance Confidence (ABC) Scale.

Authors:  L E Powell; A M Myers
Journal:  J Gerontol A Biol Sci Med Sci       Date:  1995-01       Impact factor: 6.053

5.  A new anatomically based protocol for gait analysis in children.

Authors:  Alberto Leardini; Zimi Sawacha; Gabriele Paolini; Stefania Ingrosso; Roberto Nativo; Maria Grazia Benedetti
Journal:  Gait Posture       Date:  2007-02-08       Impact factor: 2.840

6.  Robot-assisted gait training in patients with Parkinson disease: a randomized controlled trial.

Authors:  Alessandro Picelli; Camilla Melotti; Francesca Origano; Andreas Waldner; Antonio Fiaschi; Valter Santilli; Nicola Smania
Journal:  Neurorehabil Neural Repair       Date:  2012-01-18       Impact factor: 3.919

7.  Ankle dorsiflexion as an fMRI paradigm to assay motor control for walking during rehabilitation.

Authors:  Bruce H Dobkin; Ann Firestine; Michele West; Kaveh Saremi; Roger Woods
Journal:  Neuroimage       Date:  2004-09       Impact factor: 6.556

8.  Biomechanical assessment of balance and posture in subjects with ankylosing spondylitis.

Authors:  Zimi Sawacha; Elena Carraro; Silvia Del Din; Annamaria Guiotto; Lara Bonaldo; Leonardo Punzi; Claudio Cobelli; Stefano Masiero
Journal:  J Neuroeng Rehabil       Date:  2012-08-29       Impact factor: 4.262

9.  Robot-assisted walking training for individuals with Parkinson's disease: a pilot randomized controlled trial.

Authors:  Patrizio Sale; Maria Francesca De Pandis; Domenica Le Pera; Ivan Sova; Veronica Cimolin; Andrea Ancillao; Giorgio Albertini; Manuela Galli; Fabrizio Stocchi; Marco Franceschini
Journal:  BMC Neurol       Date:  2013-05-24       Impact factor: 2.474

10.  MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation.

Authors:  Alice Mantoan; Claudio Pizzolato; Massimo Sartori; Zimi Sawacha; Claudio Cobelli; Monica Reggiani
Journal:  Source Code Biol Med       Date:  2015-11-16
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