Literature DB >> 25318782

Quantitative gait analysis in patients with Parkinson treated with deep brain stimulation: the effects of a robotic gait training.

Alice Nardo1, Federica Anasetti2, Domenico Servello3, Mauro Porta3.   

Abstract

BACKGROUND: Despite Deep Brain Stimulation (DBS) improves cardinal symptoms of Parkinson's Disease (PD), its effect on walking impairment is less evident. Robotic-assisted rehabilitation systems could serve as "add-on" physical therapy for PD patients. This systems are able to anticipate and correct the trajectory of patients' motion to improve their motor function recovery.
OBJECTIVE: Aim of the present study was the quantitative assessment of the effects of a Robotic-Assisted Rehabilitation Protocol (RARP) on gait patterns by means of three-dimensional gait analysis on PD patients treated with DBS.
METHODS: 9 patients with PD treated with DBS were submitted to 5 weeks robotic-assisted rehabilitation sessions. Three-dimensional gait analysis was performed before the starting session, and one day after the last session using an optoelectronic system with passive markers.
RESULTS: The RARP showed significant improvements on spatio-temporal gait parameters and on the Unified Parkinson's Disease Rating Scale motor score.
CONCLUSIONS: The RARP with Lokomat may have positive effects on spatio-temporal gait parameters of PD patients and it could be an adjunct therapy for patients treated with DBS. On the other hand kinematic and kinetic gait parameters did not show significant improvements, remaining almost comparable before and after the RARP.

Entities:  

Keywords:  Parkinson's disease; deep brain stimulation; gait analysis; locomotor system; robotic-assisted rehabilitation

Mesh:

Year:  2014        PMID: 25318782     DOI: 10.3233/NRE-141173

Source DB:  PubMed          Journal:  NeuroRehabilitation        ISSN: 1053-8135            Impact factor:   2.138


  5 in total

Review 1.  Robotic gait rehabilitation and substitution devices in neurological disorders: where are we now?

Authors:  Rocco Salvatore Calabrò; Alberto Cacciola; Francesco Bertè; Alfredo Manuli; Antonino Leo; Alessia Bramanti; Antonino Naro; Demetrio Milardi; Placido Bramanti
Journal:  Neurol Sci       Date:  2016-01-18       Impact factor: 3.307

2.  USE OF SPATIOTEMPORAL GAIT PARAMETERS TO DETERMINE RETURN TO SPORTS AFTER ACL RECONSTRUCTION.

Authors:  Gustavo Leporace; Leonardo Metsavaht; Gabriel Zeitoune; Thiago Marinho; Tainá Oliveira; Glauber Ribeiro Pereira; Liszt Palmeira D E Oliveira; Luiz Alberto Batista
Journal:  Acta Ortop Bras       Date:  2016 Mar-Apr       Impact factor: 0.513

3.  Deep Brain Stimulation Effects on Gait Pattern in Advanced Parkinson's Disease Patients.

Authors:  Daniela Navratilova; Alois Krobot; Pavel Otruba; Martin Nevrly; David Krahulik; Petr Kolar; Barbora Kolarova; Michaela Kaiserova; Katerina Mensikova; Miroslav Vastik; Sandra Kurcova; Petr Kanovsky
Journal:  Front Neurosci       Date:  2020-08-14       Impact factor: 4.677

Review 4.  Settings matter: a scoping review on parameters in robot-assisted gait therapy identifies the importance of reporting standards.

Authors:  Florian van Dellen; Rob Labruyère
Journal:  J Neuroeng Rehabil       Date:  2022-04-22       Impact factor: 5.208

Review 5.  Artificial intelligence applications and robotic systems in Parkinson's disease (Review).

Authors:  Lacramioara Perju-Dumbrava; Maria Barsan; Daniel Corneliu Leucuta; Luminita C Popa; Cristina Pop; Nicoleta Tohanean; Stefan L Popa
Journal:  Exp Ther Med       Date:  2021-12-17       Impact factor: 2.447

  5 in total

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