Literature DB >> 25306125

Can robot-assisted movement training (Lokomat) improve functional recovery and psychological well-being in chronic stroke? Promising findings from a case study.

Rocco Salvatore Calabrò, Simone Reitano, Antonio Leo, Rosaria De Luca, Corrado Melegari, Placido Bramanti.   

Abstract

The Lokomat is a robotic device that has been widely used for gait rehabilitation in several neurological disorders, with a positive effect also in the chronic phase. We describe the case of a 54-yearold female with post-stroke moderate-to-severe chronic hemiplegia, whose force, gait and balance significantly improved after intensive training with Lokomat Pro. We also noted a positive impact of Lokomat on mood and coping styles. This may be partly related to the task-oriented exercises with computerized visual feedback, which in turn can be considered an important tool for increasing patients' motor output, involvement and motivation during gait training. Augmented feedback during robot-assisted gait appears to be a promising way of facilitating gait and physical function, but also of improving psychological and cognitive status.

Entities:  

Mesh:

Year:  2014        PMID: 25306125      PMCID: PMC4198163     

Source DB:  PubMed          Journal:  Funct Neurol        ISSN: 0393-5264


  5 in total

1.  Enhanced gait-related improvements after therapist- versus robotic-assisted locomotor training in subjects with chronic stroke: a randomized controlled study.

Authors:  T George Hornby; Donielle D Campbell; Jennifer H Kahn; Tobey Demott; Jennifer L Moore; Heidi R Roth
Journal:  Stroke       Date:  2008-05-08       Impact factor: 7.914

2.  Over-ground and robotic-assisted locomotor training in adults with chronic stroke: a blinded randomized clinical trial.

Authors:  Carolyn P Kelley; Jason Childress; Corwin Boake; Elizabeth A Noser
Journal:  Disabil Rehabil Assist Technol       Date:  2012-09-20

3.  Multicenter randomized clinical trial evaluating the effectiveness of the Lokomat in subacute stroke.

Authors:  Joseph Hidler; Diane Nichols; Marlena Pelliccio; Kathy Brady; Donielle D Campbell; Jennifer H Kahn; T George Hornby
Journal:  Neurorehabil Neural Repair       Date:  2009-01       Impact factor: 3.919

4.  Computerized visual feedback: an adjunct to robotic-assisted gait training.

Authors:  Raphael Banz; Marc Bolliger; Gery Colombo; Volker Dietz; Lars Lünenburger
Journal:  Phys Ther       Date:  2008-09-04

Review 5.  Treadmill training is effective for ambulatory adults with stroke: a systematic review.

Authors:  Janaine C Polese; Louise Ada; Catherine M Dean; Lucas R Nascimento; Luci F Teixeira-Salmela
Journal:  J Physiother       Date:  2013-06       Impact factor: 7.000

  5 in total
  8 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.  Effects of Robotic Neurorehabilitation on Body Representation in Individuals with Stroke: A Preliminary Study Focusing on an EEG-Based Approach.

Authors:  Maria Grazia Maggio; Antonino Naro; Alfredo Manuli; Giuseppa Maresca; Tina Balletta; Desirèe Latella; Rosaria De Luca; Rocco Salvatore Calabrò
Journal:  Brain Topogr       Date:  2021-03-04       Impact factor: 3.020

3.  Feasibility of Rehabilitation Training With a Newly Developed, Portable, Gait Assistive Robot for Balance Function in Hemiplegic Patients.

Authors:  Junhyun Sung; Sehoon Choi; Hyunbae Kim; Gyuhan Lee; Changsoo Han; Younghoon Ji; Dongbin Shin; Seunghoon Hwang; Deokwon Yun; Hyeyoun Jang; Mi Jung Kim
Journal:  Ann Rehabil Med       Date:  2017-04-27

Review 4.  Assessing Effectiveness and Costs in Robot-Mediated Lower Limbs Rehabilitation: A Meta-Analysis and State of the Art.

Authors:  Giorgio Carpino; Alessandra Pezzola; Michele Urbano; Eugenio Guglielmelli
Journal:  J Healthc Eng       Date:  2018-06-04       Impact factor: 2.682

Review 5.  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

6.  Improving neuropsychiatric symptoms following stroke using virtual reality: A case report.

Authors:  Rosaria De Luca; Alfredo Manuli; Carmen De Domenico; Emanuele Lo Voi; Antonio Buda; Giuseppa Maresca; Alessia Bramanti; Rocco Salvatore Calabrò
Journal:  Medicine (Baltimore)       Date:  2019-05       Impact factor: 1.817

7.  Optimal Intervention Timing for Robotic-Assisted Gait Training in Hemiplegic Stroke.

Authors:  Lingchao Xie; Bu Hyun Yoon; Chanhee Park; Joshua Sung H You
Journal:  Brain Sci       Date:  2022-08-10

8.  Response to: Comment on "Assessing Effectiveness and Costs in Robot-Mediated Lower Limbs Rehabilitation: A Meta-Analysis and State of the Art".

Authors:  Giorgio Carpino; Alessandra Pezzola; Michele Urbano; Eugenio Guglielmelli
Journal:  J Healthc Eng       Date:  2019-09-24       Impact factor: 2.682

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.