Literature DB >> 18073325

An accelerometry-based comparison of 2 robotic assistive devices for treadmill training of gait.

Jean-Philippe Regnaux1, Kaveh Saremi, Jon Marehbian, Bernard Bussel, Bruce H Dobkin.   

Abstract

OBJECTIVE: Two commercial robotic devices, the Gait Trainer (GT) and the Lokomat (LOKO), assist task-oriented practice of walking. The gait patterns induced by these motor-driven devices have not been characterized and compared.
METHODS: A healthy participant chose the most comfortable gait pattern on each device and for treadmill (TM) walking at 1, 2 (maximum for the GT), and 3 km/h and over ground at similar speeds. A system of accelerometers on the thighs and feet allowed the calculation of spatiotemporal features and accelerations during the gait cycle.
RESULTS: At the 1 and 2 km/h speed settings, single-limb stance times were prolonged on the devices compared with overground walking. Differences on the LOKO were decreased by adjusting the hip and knee angles and step length. At the 3 km/h setting, the LOKO approximated the participant's overground parameters. Irregular accelerations and decelerations from toe-off to heel contact were induced by the devices, especially at slower speeds.
CONCLUSIONS: The LOKO and GT impose mechanical constraints that may alter leg accelerations-decelerations during stance and swing phases, as well as stance duration, especially at their slower speed settings, that are not found during TM and overground walking. The potential impact of these perturbations on training to improve gait needs further study.

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Year:  2007        PMID: 18073325     DOI: 10.1177/1545968307310050

Source DB:  PubMed          Journal:  Neurorehabil Neural Repair        ISSN: 1545-9683            Impact factor:   3.919


  10 in total

1.  Plantar Pressure Distribution During Robotic-Assisted Gait in Post-stroke Hemiplegic Patients.

Authors:  Jin Kyu Yang; Na El Ahn; Dae Hyun Kim; Deog Young Kim
Journal:  Ann Rehabil Med       Date:  2014-04-29

2.  Predicting the long-term effects of human-robot interaction: a reflection on responsibility in medical robotics.

Authors:  Edoardo Datteri
Journal:  Sci Eng Ethics       Date:  2011-07-29       Impact factor: 3.525

Review 3.  The promise of mHealth: daily activity monitoring and outcome assessments by wearable sensors.

Authors:  Bruce H Dobkin; Andrew Dorsch
Journal:  Neurorehabil Neural Repair       Date:  2011 Nov-Dec       Impact factor: 3.919

4.  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

5.  Should body weight-supported treadmill training and robotic-assistive steppers for locomotor training trot back to the starting gate?

Authors:  Bruce H Dobkin; Pamela W Duncan
Journal:  Neurorehabil Neural Repair       Date:  2012-03-12       Impact factor: 3.919

6.  Innovative gait robot for the repetitive practice of floor walking and stair climbing up and down in stroke patients.

Authors:  Stefan Hesse; Andreas Waldner; Christopher Tomelleri
Journal:  J Neuroeng Rehabil       Date:  2010-06-28       Impact factor: 4.262

Review 7.  Progressive Staging of Pilot Studies to Improve Phase III Trials for Motor Interventions.

Authors:  Bruce H Dobkin
Journal:  Neurorehabil Neural Repair       Date:  2009 Mar-Apr       Impact factor: 3.919

8.  Recent advances in rehabilitation of stroke survivors.

Authors:  Veronika I Skvortsova; Elena A Kovrazhkina
Journal:  F1000 Med Rep       Date:  2009-03-24

Review 9.  Robot-assisted gait training for stroke patients: current state of the art and perspectives of robotics.

Authors:  Giovanni Morone; Stefano Paolucci; Andrea Cherubini; Domenico De Angelis; Vincenzo Venturiero; Paola Coiro; Marco Iosa
Journal:  Neuropsychiatr Dis Treat       Date:  2017-05-15       Impact factor: 2.570

Review 10.  The Three Laws of Neurorobotics: A Review on What Neurorehabilitation Robots Should Do for Patients and Clinicians.

Authors:  Marco Iosa; Giovanni Morone; Andrea Cherubini; Stefano Paolucci
Journal:  J Med Biol Eng       Date:  2016-02-09       Impact factor: 1.553

  10 in total

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