Literature DB >> 22436307

Virtual reality and robotics for stroke rehabilitation: where do we go from here?

Eric Wade1, Carolee J Winstein.   

Abstract

Promoting functional recovery after stroke requires collaborative and innovative approaches to neurorehabilitation research. Task-oriented training (TOT) approaches that include challenging, adaptable, and meaningful activities have led to successful outcomes in several large-scale multisite definitive trials. This, along with recent technological advances of virtual reality and robotics, provides a fertile environment for furthering clinical research in neurorehabilitation. Both virtual reality and robotics make use of multimodal sensory interfaces to affect human behavior. In the therapeutic setting, these systems can be used to quantitatively monitor, manipulate, and augment the users' interaction with their environment, with the goal of promoting functional recovery. This article describes recent advances in virtual reality and robotics and the synergy with best clinical practice. Additionally, we describe the promise shown for automated assessments and in-home activity-based interventions. Finally, we propose a broader approach to ensuring that technology-based assessment and intervention complement evidence-based practice and maintain a patient-centered perspective.

Entities:  

Mesh:

Year:  2011        PMID: 22436307     DOI: 10.1310/tsr1806-685

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


  13 in total

1.  Effect of combined low-frequency repetitive transcranial magnetic stimulation and virtual reality training on upper limb function in subacute stroke: a double-blind randomized controlled trail.

Authors:  Chan-Juan Zheng; Wei-Jing Liao; Wen-Guang Xia
Journal:  J Huazhong Univ Sci Technolog Med Sci       Date:  2015-04-16

2.  Considerations in the efficacy and effectiveness of virtual reality interventions for stroke rehabilitation: moving the field forward.

Authors:  Rachel Proffitt; Belinda Lange
Journal:  Phys Ther       Date:  2014-10-24

Review 3.  Infusing motor learning research into neurorehabilitation practice: a historical perspective with case exemplar from the accelerated skill acquisition program.

Authors:  Carolee Winstein; Rebecca Lewthwaite; Sarah R Blanton; Lois B Wolf; Laurie Wishart
Journal:  J Neurol Phys Ther       Date:  2014-07       Impact factor: 3.649

4.  Towards active lower limb prosthetic systems: design issues and solutions.

Authors:  Oliver Christ; Philipp Beckerle
Journal:  Biomed Eng Online       Date:  2016-12-19       Impact factor: 2.819

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

6.  A transformative subfield in rehabilitation science at the nexus of new technologies, aging, and disability.

Authors:  Carolee J Winstein; Philip S Requejo; Elizabeth M Zelinski; Sara J Mulroy; Eileen M Crimmins
Journal:  Front Psychol       Date:  2012-09-21

7.  Test-retest reliability of Kinect's measurements for the evaluation of upper body recovery of stroke patients.

Authors:  A Mobini; S Behzadipour; M Saadat
Journal:  Biomed Eng Online       Date:  2015-08-04       Impact factor: 2.819

8.  Kinematic and neurophysiological consequences of an assisted-force-feedback brain-machine interface training: a case study.

Authors:  Stefano Silvoni; Marianna Cavinato; Chiara Volpato; Giulia Cisotto; Clara Genna; Michela Agostini; Andrea Turolla; Ander Ramos-Murguialday; Francesco Piccione
Journal:  Front Neurol       Date:  2013-11-07       Impact factor: 4.003

9.  A geometric method for computing ocular kinematics and classifying gaze events using monocular remote eye tracking in a robotic environment.

Authors:  Tarkeshwar Singh; Christopher M Perry; Troy M Herter
Journal:  J Neuroeng Rehabil       Date:  2016-01-26       Impact factor: 4.262

10.  Stability of Kinect for range of motion analysis in static stretching exercises.

Authors:  Fatemeh Mortazavi; Ali Nadian-Ghomsheh
Journal:  PLoS One       Date:  2018-07-24       Impact factor: 3.240

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