Literature DB >> 21642064

Robot-assisted gait training for patients with hemiparesis due to stroke.

Stanley Fisher1, Leah Lucas, T Adam Thrasher.   

Abstract

Robot-assisted devices are becoming a popular alternative to manual facilitation in stroke rehabilitation. These devices have the potential to reduce therapist burden and treatment costs; however, their effectiveness in terms of functional recovery remains in question. This pilot study compared the outcomes of a stroke rehabilitation program that incorporates robot-assisted gait training (RAGT) with a more traditional therapy program that does not. Twenty hemiparetic stroke patients were recruited at a rehabilitation hospital in Houston, Texas, and were randomly assigned to 2 groups. The control group (n = 10) received 24 1-hour sessions of conventional physical therapy, whereas the RAGT group (n = 10) received 24 1-hour sessions of conventional physical therapy combined with RAGT on a treadmill. Gait function was assessed before and after treatment by an 8-m walk test, a 3-minute walk test, and the Tinetti balance assessment. Both groups showed significant improvement in all 3 outcome measures following treatment (P < .05), but there was no difference between groups. It is concluded that RAGT may provide improvements in balance and gait comparable with conventional physical therapy. A larger multicenter trial is required to investigate the effectiveness of RAGT in hemiparetic stroke.

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Mesh:

Year:  2011        PMID: 21642064     DOI: 10.1310/tsr1803-269

Source DB:  PubMed          Journal:  Top Stroke Rehabil        ISSN: 1074-9357            Impact factor:   2.119


  22 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

Review 2.  Electromechanical-assisted training for walking after stroke.

Authors:  Jan Mehrholz; Bernhard Elsner; Cordula Werner; Joachim Kugler; Marcus Pohl
Journal:  Cochrane Database Syst Rev       Date:  2013-07-25

Review 3.  Technological advances in interventions to enhance poststroke gait.

Authors:  Lynne R Sheffler; John Chae
Journal:  Phys Med Rehabil Clin N Am       Date:  2013-05       Impact factor: 1.784

Review 4.  Electromechanical-assisted training for walking after stroke.

Authors:  Jan Mehrholz; Simone Thomas; Cordula Werner; Joachim Kugler; Marcus Pohl; Bernhard Elsner
Journal:  Cochrane Database Syst Rev       Date:  2017-05-10

Review 5.  What is the evidence for physical therapy poststroke? A systematic review and meta-analysis.

Authors:  Janne Marieke Veerbeek; Erwin van Wegen; Roland van Peppen; Philip Jan van der Wees; Erik Hendriks; Marc Rietberg; Gert Kwakkel
Journal:  PLoS One       Date:  2014-02-04       Impact factor: 3.240

6.  Kinematics of turning during walking over ground and on a rotating treadmill.

Authors:  Janez Pavčič; Zlatko Matjačić; Andrej Olenšek
Journal:  J Neuroeng Rehabil       Date:  2014-08-23       Impact factor: 4.262

7.  Virtual Reality Reflection Therapy Improves Balance and Gait in Patients with Chronic Stroke: Randomized Controlled Trials.

Authors:  Taesung In; Kyeongjin Lee; Changho Song
Journal:  Med Sci Monit       Date:  2016-10-28

8.  Electromechanical-assisted training for walking after stroke.

Authors:  Jan Mehrholz; Simone Thomas; Joachim Kugler; Marcus Pohl; Bernhard Elsner
Journal:  Cochrane Database Syst Rev       Date:  2020-10-22

9.  Voluntary initiation of movement: multifunctional integration of subjective agency.

Authors:  Patrick Grüneberg; Hideki Kadone; Kenji Suzuki
Journal:  Front Psychol       Date:  2015-05-22

10.  Pilot study of locomotion improvement using hybrid assistive limb in chronic stroke patients.

Authors:  Hiroaki Kawamoto; Kiyotaka Kamibayashi; Yoshio Nakata; Kanako Yamawaki; Ryohei Ariyasu; Yoshiyuki Sankai; Masataka Sakane; Kiyoshi Eguchi; Naoyuki Ochiai
Journal:  BMC Neurol       Date:  2013-10-07       Impact factor: 2.474

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