Literature DB >> 25850089

Effects of Innovative WALKBOT Robotic-Assisted Locomotor Training on Balance and Gait Recovery in Hemiparetic Stroke: A Prospective, Randomized, Experimenter Blinded Case Control Study With a Four-Week Follow-Up.

Soo-Yeon Kim, Li Yang, In Jae Park, Eun Joo Kim, Min Su JoshuaPark, Sung Hyun You, Yun-Hee Kim, Hyun-Yoon Ko, Yong-Il Shin.   

Abstract

The present clinical investigation was to ascertain whether the effects of WALKBOT-assisted locomotor training (WLT) on balance, gait, and motor recovery were superior or similar to the conventional locomotor training (CLT) in patients with hemiparetic stroke. Thirty individuals with hemiparetic stroke were randomly assigned to either WLT or CLT. WLT emphasized on a progressive, conventional locomotor retraining practice (40 min) combined with the WALKBOT-assisted, haptic guidance and random variable locomotor training (40 min) whereas CLT involved conventional physical therapy alone (80 min). Both intervention dosages were standardized and provided for 80 min, five days/week for four weeks. Clinical outcomes included function ambulation category (FAC), Berg balance scale (BBS), Korean modified Barthel index (K-MBI), modified Ashworth scale (MAS), and EuroQol-5 dimension (EQ-5D) before and after the four-week program as well as at follow-up four weeks after the intervention. Two-way repeated measure ANOVA showed significant interaction effect (time × group) for FAC (p=0.02), BBS (p=0.03) , and K-MBI (p=0.00) across the pre-training, post-training, and follow-up tests, indicating that WLT was more beneficial for balance, gait and daily activity function than CLT alone. However, no significant difference in other variables was observed. This is the first clinical trial that highlights the superior, augmented effects of the WALKBOT-assisted locomotor training on balance, gait and motor recovery when compared to the conventional locomotor training alone in patients with hemiparetic stroke.

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Year:  2015        PMID: 25850089     DOI: 10.1109/TNSRE.2015.2404936

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  17 in total

1.  A 3D Computer Vision-Guided Robotic Companion for Non-Contact Human Assistance and Rehabilitation.

Authors:  Tao Shen; Md Rayhan Afsar; He Zhang; Cang Ye; Xiangrong Shen
Journal:  J Intell Robot Syst       Date:  2020-09-21       Impact factor: 2.646

Review 2.  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

3.  Comparisons between Locomat and Walkbot robotic gait training regarding balance and lower extremity function among non-ambulatory chronic acquired brain injury survivors.

Authors:  Hoo Young Lee; Jung Hyun Park; Tae-Woo Kim
Journal:  Medicine (Baltimore)       Date:  2021-05-07       Impact factor: 1.889

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.  A Review of Robot-Assisted Lower-Limb Stroke Therapy: Unexplored Paths and Future Directions in Gait Rehabilitation.

Authors:  Bradley Hobbs; Panagiotis Artemiadis
Journal:  Front Neurorobot       Date:  2020-04-15       Impact factor: 2.650

Review 6.  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

7.  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

8.  Gait Improvement in Chronic Stroke Survivors by Using an Innovative Gait Training Machine: A Randomized Controlled Trial.

Authors:  Patcharee Kooncumchoo; Phuwarin Namdaeng; Somrudee Hanmanop; Bunyong Rungroungdouyboon; Kultida Klarod; Sirirat Kiatkulanusorn; Nongnuch Luangpon
Journal:  Int J Environ Res Public Health       Date:  2021-12-25       Impact factor: 3.390

9.  Abnormal synergistic gait mitigation in acute stroke using an innovative ankle-knee-hip interlimb humanoid robot: a preliminary randomized controlled trial.

Authors:  Chanhee Park; Mooyeon Oh-Park; Amy Bialek; Kathleen Friel; Dylan Edwards; Joshua Sung H You
Journal:  Sci Rep       Date:  2021-11-24       Impact factor: 4.379

10.  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
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