Literature DB >> 21857778

Role of Robotics in Neurorehabilitation.

Joseph Hidler1, Robert Sainburg.   

Abstract

Over the past decade, rehabilitation hospitals have begun to incorporate robotics technologies into the daily treatment schedule of many patients. These interventions hold greater promise than simply replicating traditional therapy, because they allow therapists an unprecedented ability to specify and monitor movement features such as speed, direction, amplitude, and joint coordination patterns and to introduce controlled perturbations into therapy. We argue that to fully realize the potential of robotic devices in neurorehabilitation, it is necessary to better understand the specific aspects of movement that should be facilitated in rehabilitation. In this article, we first discuss neurorecovery in the context of motor control and learning principles that can provide guidelines to rehabilitation professionals for enhancing recovery of motor function. We then discuss how robotic devices can be used to support such activities.

Entities:  

Year:  2011        PMID: 21857778      PMCID: PMC3157701          DOI: 10.1310/sci1701-42

Source DB:  PubMed          Journal:  Top Spinal Cord Inj Rehabil        ISSN: 1082-0744


  26 in total

1.  Hindlimb locomotor and postural training modulates glycinergic inhibition in the spinal cord of the adult spinal cat.

Authors:  R D de Leon; H Tamaki; J A Hodgson; R R Roy; V R Edgerton
Journal:  J Neurophysiol       Date:  1999-07       Impact factor: 2.714

2.  An objective and standardized test of hand function.

Authors:  R H Jebsen; N Taylor; R B Trieschmann; M J Trotter; L A Howard
Journal:  Arch Phys Med Rehabil       Date:  1969-06       Impact factor: 3.966

3.  Interaction of visual and proprioceptive feedback during adaptation of human reaching movements.

Authors:  Robert A Scheidt; Michael A Conditt; Emanuele L Secco; Ferdinando A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2005-01-19       Impact factor: 2.714

4.  Moving effortlessly in three dimensions: does Donders' law apply to arm movement?

Authors:  J F Soechting; C A Buneo; U Herrmann; M Flanders
Journal:  J Neurosci       Date:  1995-09       Impact factor: 6.167

5.  The coordination of arm movements: an experimentally confirmed mathematical model.

Authors:  T Flash; N Hogan
Journal:  J Neurosci       Date:  1985-07       Impact factor: 6.167

6.  Visual modulation of proprioceptive reflexes during movement.

Authors:  Pratik K Mutha; Philippe Boulinguez; Robert L Sainburg
Journal:  Brain Res       Date:  2008-10-02       Impact factor: 3.252

7.  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

8.  Directional biases reveal utilization of arm's biomechanical properties for optimization of motor behavior.

Authors:  Jacob A Goble; Yanxin Zhang; Yury Shimansky; Siddharth Sharma; Natalia V Dounskaia
Journal:  J Neurophysiol       Date:  2007-07-11       Impact factor: 2.714

9.  Quantification of functional weakness and abnormal synergy patterns in the lower limb of individuals with chronic stroke.

Authors:  Nathan Neckel; Marlena Pelliccio; Diane Nichols; Joseph Hidler
Journal:  J Neuroeng Rehabil       Date:  2006-07-20       Impact factor: 4.262

10.  Protocol for the Locomotor Experience Applied Post-stroke (LEAPS) trial: a randomized controlled trial.

Authors:  Pamela W Duncan; Katherine J Sullivan; Andrea L Behrman; Stanley P Azen; Samuel S Wu; Stephen E Nadeau; Bruce H Dobkin; Dorian K Rose; Julie K Tilson
Journal:  BMC Neurol       Date:  2007-11-08       Impact factor: 2.474

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  11 in total

1.  Trunk robot rehabilitation training with active stepping reorganizes and enriches trunk motor cortex representations in spinal transected rats.

Authors:  Chintan S Oza; Simon F Giszter
Journal:  J Neurosci       Date:  2015-05-06       Impact factor: 6.167

2.  Multisensory integration for motor control and adaptation.

Authors:  Stephen Helms Tillery; Robert L Sainburg
Journal:  J Mot Behav       Date:  2012       Impact factor: 1.328

3.  Adjustable Parameters and the Effectiveness of Adjunct Robot-Assisted Gait Training in Individuals with Chronic Stroke.

Authors:  Shih-Ching Chen; Jiunn-Horng Kang; Chih-Wei Peng; Chih-Chao Hsu; Yen-Nung Lin; Chien-Hung Lai
Journal:  Int J Environ Res Public Health       Date:  2022-07-04       Impact factor: 4.614

4.  Plasticity and alterations of trunk motor cortex following spinal cord injury and non-stepping robot and treadmill training.

Authors:  Chintan S Oza; Simon F Giszter
Journal:  Exp Neurol       Date:  2014-04-03       Impact factor: 5.330

Review 5.  Clinical application of the Hybrid Assistive Limb (HAL) for gait training-a systematic review.

Authors:  Anneli Wall; Jörgen Borg; Susanne Palmcrantz
Journal:  Front Syst Neurosci       Date:  2015-03-25

6.  Improving Challenge/Skill Ratio in a Multimodal Interface by Simultaneously Adapting Game Difficulty and Haptic Assistance through Psychophysiological and Performance Feedback.

Authors:  Carlos Rodriguez-Guerrero; Kristel Knaepen; Juan C Fraile-Marinero; Javier Perez-Turiel; Valentin Gonzalez-de-Garibay; Dirk Lefeber
Journal:  Front Neurosci       Date:  2017-05-01       Impact factor: 4.677

Review 7.  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

8.  Development of KIINCE: A kinetic feedback-based robotic environment for study of neuromuscular coordination and rehabilitation of human standing and walking.

Authors:  Wendy L Boehm; Kreg G Gruben
Journal:  J Rehabil Assist Technol Eng       Date:  2018-09-20

9.  Effect of assist-as-needed robotic gait training on the gait pattern post stroke: a randomized controlled trial.

Authors:  J F Alingh; B M Fleerkotte; A C H Geurts; J H Buurke; B E Groen; J S Rietman; V Weerdesteyn; E H F van Asseldonk
Journal:  J Neuroeng Rehabil       Date:  2021-02-05       Impact factor: 4.262

10.  Active robotic training improves locomotor function in a stroke survivor.

Authors:  Chandramouli Krishnan; Rajiv Ranganathan; Shailesh S Kantak; Yasin Y Dhaher; William Z Rymer
Journal:  J Neuroeng Rehabil       Date:  2012-08-20       Impact factor: 4.262

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