Literature DB >> 18849098

Kinematic trajectories while walking within the Lokomat robotic gait-orthosis.

Joseph Hidler1, Wessel Wisman, Nathan Neckel.   

Abstract

Background One of the most popular robot assisted rehabilitation devices used is the Lokomat. Unfortunately, not much is known about the behaviors exhibited by subjects in this device. The goal of this study was to evaluate the kinematic patterns of individuals walking inside the Lokomat compared to those demonstrated on a treadmill. Methods Six healthy subjects walked on a treadmill and inside the Lokomat while the motions of the subject and Lokomat were tracked. Joint angles and linear motion were determined for Lokomat and treadmill walking. We also evaluated the variability of the patterns, and the repeatability of measuring techniques. Findings The overall kinematics in the Lokomat are similar to those on a treadmill, however there was significantly more hip and ankle extension, and greater hip and ankle range of motion in the Lokomat (P<0.05). Additionally, the linear movement of joints was reduced in the Lokomat. Subjects tested on repeated sessions presented consistent kinematics, demonstrating the ability to consistently setup and test subjects. Interpretation The reduced degrees of freedom in the Lokomat are believed to be the reason for the specific kinematic differences. We found that despite being firmly attached to the device there was still subject movement relative to the Lokomat. This led to variability in the patterns, where subjects altered their gait pattern from step to step. These results are clinically important as a variable step pattern has been shown to be a more effective gait training strategy than one which forces the same kinematic pattern in successive steps.

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Year:  2008        PMID: 18849098     DOI: 10.1016/j.clinbiomech.2008.08.004

Source DB:  PubMed          Journal:  Clin Biomech (Bristol, Avon)        ISSN: 0268-0033            Impact factor:   2.063


  33 in total

1.  Modelling of the toe trajectory during normal gait using circle-fit approximation.

Authors:  Juan Fang; Kenneth J Hunt; Le Xie; Guo-Yuan Yang
Journal:  Med Biol Eng Comput       Date:  2015-11-20       Impact factor: 2.602

Review 2.  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

3.  Individuals Poststroke Do Not Perceive Their Spatiotemporal Gait Asymmetries as Abnormal.

Authors:  Clinton J Wutzke; Richard A Faldowski; Michael D Lewek
Journal:  Phys Ther       Date:  2015-04-02

4.  Effect of a robotic restraint gait training versus robotic conventional gait training on gait parameters in stroke patients.

Authors:  Céline Bonnyaud; Raphael Zory; Julien Boudarham; Didier Pradon; Djamel Bensmail; Nicolas Roche
Journal:  Exp Brain Res       Date:  2013-11-10       Impact factor: 1.972

5.  The effects of robot assisted gait training on temporal-spatial characteristics of people with spinal cord injuries: A systematic review.

Authors:  Stephen Clive Hayes; Christopher Richard James Wilcox; Hollie Samantha Forbes White; Natalie Vanicek
Journal:  J Spinal Cord Med       Date:  2018-02-05       Impact factor: 1.985

6.  Kinematic, muscular, and metabolic responses during exoskeletal-, elliptical-, or therapist-assisted stepping in people with incomplete spinal cord injury.

Authors:  T George Hornby; Catherine R Kinnaird; Carey L Holleran; Miriam R Rafferty; Kelly S Rodriguez; Julie B Cain
Journal:  Phys Ther       Date:  2012-06-14

7.  Hardware Development and Locomotion Control Strategy for an Over-Ground Gait Trainer: NaTUre-Gaits.

Authors:  Trieu Phat Luu; Kin Huat Low; Xingda Qu; Hup Boon Lim; Kay Hiang Hoon
Journal:  IEEE J Transl Eng Health Med       Date:  2014-01-30       Impact factor: 3.316

8.  Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training.

Authors:  Alexander Duschau-Wicke; Andrea Caprez; Robert Riener
Journal:  J Neuroeng Rehabil       Date:  2010-09-10       Impact factor: 4.262

9.  Allowing intralimb kinematic variability during locomotor training poststroke improves kinematic consistency: a subgroup analysis from a randomized clinical trial.

Authors:  Michael D Lewek; Theresa H Cruz; Jennifer L Moore; Heidi R Roth; Yasin Y Dhaher; T George Hornby
Journal:  Phys Ther       Date:  2009-06-11

10.  Pilot study of Lokomat versus manual-assisted treadmill training for locomotor recovery post-stroke.

Authors:  Kelly P Westlake; Carolynn Patten
Journal:  J Neuroeng Rehabil       Date:  2009-06-12       Impact factor: 4.262

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