Literature DB >> 24476805

Robot-assisted gait training improves motor performances and modifies Motor Unit firing in poststroke patients.

C Chisari1, F Bertolucci, V Monaco, M Venturi, C Simonella, S Micera, B Rossi.   

Abstract

BACKGROUND: Robotics and related technologies are realizing their promise to improve the delivery of rehabilitation therapy but the mechanism by which they enhance recovery is still unknown. The electromechanical-driven gait orthosis Lokomat has demonstrated its utility for gait rehabilitation after stroke. AIM: To test the efficacy of Lokomat in gait retraining and to investigate the neurophysiological mechanisms underlying the recovery process.
DESIGN: Case series study.
SETTING: Unit of Neurorehabilitation of a University Hospital. POPULATION: Fifteen patients with post-stroke hemiparesis.
METHODS: Patients underwent a six weeks rehabilitative treatment provided by Lokomat. The outcome measures were: Fugl-Meyer Motor Scale (FMMS), Berg Balance Scale (BBS), 10 metres Walking Test (10mWT), Timed Up and Go test (TUG), 6 Minute Walking Test (6MWT). Strength and Motor Unit firing rate of vastus medialis (VM) were analyzed during isometric knee extension through an isokinetic dynamometer and surface EMG recording.
RESULTS: An increase of duration and covered distance, a decrease of body weight support and guidance force on the paretic side along the sessions were observed. The FMMS, the BBS, the TUG and the 6MWT demonstrated a significant improvement after the training. No increase of force was observed whereas a significant increase of firing rate of VM was recorded.
CONCLUSION: The evidence that the improvement of walking ability observed in our study determines a significant increase of firing rate of VM not accompanied by an increase of force could suggest an effect of training on motorneuronal firing rate that thus contributes to improve motor control. CLINICAL REHABILITATION IMPACT: Given the current wide use of robotics in gait retraining after stroke, our approach can contribute to clarify the mechanisms underlying its rehabilitative impact so as to incorporate the findings of evidence-based practice into appropriate treatment plans for persons poststroke.

Entities:  

Mesh:

Year:  2014        PMID: 24476805

Source DB:  PubMed          Journal:  Eur J Phys Rehabil Med        ISSN: 1973-9087            Impact factor:   2.874


  15 in total

1.  Adjustable Parameters and the Effectiveness of Adjunct Robot-Assisted Gait Training in Individuals with Chronic Stroke.

Authors:  Shih-Ching Chen; Jiunn-Horng Kang; Chih-Wei Peng; Chih-Chao Hsu; Yen-Nung Lin; Chien-Hung Lai
Journal:  Int J Environ Res Public Health       Date:  2022-07-04       Impact factor: 4.614

2.  Conflicting results of robot-assisted versus usual gait training during postacute rehabilitation of stroke patients: a randomized clinical trial.

Authors:  Giovanni Taveggia; Alberto Borboni; Chiara Mulé; Jorge H Villafañe; Stefano Negrini
Journal:  Int J Rehabil Res       Date:  2016-03       Impact factor: 1.479

Review 3.  Neuroplastic Changes Following Brain Ischemia and their Contribution to Stroke Recovery: Novel Approaches in Neurorehabilitation.

Authors:  Claudia Alia; Cristina Spalletti; Stefano Lai; Alessandro Panarese; Giuseppe Lamola; Federica Bertolucci; Fabio Vallone; Angelo Di Garbo; Carmelo Chisari; Silvestro Micera; Matteo Caleo
Journal:  Front Cell Neurosci       Date:  2017-03-16       Impact factor: 5.505

4.  Hemorrhagic versus ischemic stroke: Who can best benefit from blended conventional physiotherapy with robotic-assisted gait therapy?

Authors:  Frédéric Dierick; Mélanie Dehas; Jean-Luc Isambert; Soizic Injeyan; Anne-France Bouché; Yannick Bleyenheuft; Sigal Portnoy
Journal:  PLoS One       Date:  2017-06-02       Impact factor: 3.240

5.  Motor and psychosocial impact of robot-assisted gait training in a real-world rehabilitation setting: A pilot study.

Authors:  Cira Fundarò; Anna Giardini; Roberto Maestri; Silvia Traversoni; Michelangelo Bartolo; Roberto Casale
Journal:  PLoS One       Date:  2018-02-14       Impact factor: 3.240

6.  A Systematic Review Establishing the Current State-of-the-Art, the Limitations, and the DESIRED Checklist in Studies of Direct Neural Interfacing With Robotic Gait Devices in Stroke Rehabilitation.

Authors:  Olive Lennon; Michele Tonellato; Alessandra Del Felice; Roberto Di Marco; Caitriona Fingleton; Attila Korik; Eleonora Guanziroli; Franco Molteni; Christoph Guger; Rupert Otner; Damien Coyle
Journal:  Front Neurosci       Date:  2020-06-30       Impact factor: 4.677

Review 7.  The effect of 'device-in-charge' versus 'patient-in-charge' support during robotic gait training on walking ability and balance in chronic stroke survivors: A systematic review.

Authors:  Juliet Am Haarman; Jasper Reenalda; Jaap H Buurke; Herman van der Kooij; Johan S Rietman
Journal:  J Rehabil Assist Technol Eng       Date:  2016-11-29

8.  Robot-assisted gait training for balance and lower extremity function in patients with infratentorial stroke: a single-blinded randomized controlled trial.

Authors:  Ha Yeon Kim; Joon-Ho Shin; Sung Phil Yang; Min A Shin; Stephanie Hyeyoung Lee
Journal:  J Neuroeng Rehabil       Date:  2019-07-29       Impact factor: 4.262

Review 9.  Brain and Muscle: How Central Nervous System Disorders Can Modify the Skeletal Muscle.

Authors:  Stefania Dalise; Valentina Azzollini; Carmelo Chisari
Journal:  Diagnostics (Basel)       Date:  2020-12-04

10.  Effects of body weight support and guidance force settings on muscle synergy during Lokomat walking.

Authors:  Yosra Cherni; Maryam Hajizadeh; Fabien Dal Maso; Nicolas A Turpin
Journal:  Eur J Appl Physiol       Date:  2021-07-04       Impact factor: 3.078

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.