Literature DB >> 33501117

A Novel Robot-Aided Upper Limb Rehabilitation Training System Based on Multimodal Feedback.

Lizheng Pan1,2, Lu Zhao1, Aiguo Song2, Zeming Yin1, Shigang She1.   

Abstract

During robot-aided rehabilitation exercises, monotonous, and repetitive actions can, to the subject, feel tedious and tiring, so improving the subject's motivation and active participation in the training is very important. A novel robot-aided upper limb rehabilitation training system, based on multimodal feedback, is proposed in this investigation. To increase the subject's interest and participation, a friendly graphical user interface and diversiform game-based rehabilitation training tasks incorporating multimodal feedback are designed, to provide the subject with colorful and engaging motor training. During this training, appropriate visual, auditory, and tactile feedback is employed to improve the subject's motivation via multi-sensory incentives relevant to the training performance. This approach is similar to methods applied by physiotherapists to keep the subject focused on motor training tasks. The experimental results verify the effectiveness of the designed multimodal feedback strategy in promoting the subject's participation and motivation.
Copyright © 2019 Pan, Zhao, Song, Yin and She.

Entities:  

Keywords:  motion training; multimodal feedback; rehabilitation robot; stroke; upper limb

Year:  2019        PMID: 33501117      PMCID: PMC7805779          DOI: 10.3389/frobt.2019.00102

Source DB:  PubMed          Journal:  Front Robot AI        ISSN: 2296-9144


  20 in total

1.  A novel approach to stroke rehabilitation: robot-aided sensorimotor stimulation.

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Journal:  Neurology       Date:  2000-05-23       Impact factor: 9.910

2.  Robots integrated with virtual reality simulations for customized motor training in a person with upper extremity hemiparesis: a case study.

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Journal:  J Neurol Phys Ther       Date:  2012-06       Impact factor: 3.649

3.  Effect of viewing angle on arm reaching while standing in a virtual environment: potential for virtual rehabilitation.

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Journal:  Acta Psychol (Amst)       Date:  2010-02

4.  Efficacy and safety of non-immersive virtual reality exercising in stroke rehabilitation (EVREST): a randomised, multicentre, single-blind, controlled trial.

Authors:  Gustavo Saposnik; Leonardo G Cohen; Muhammad Mamdani; Sepideth Pooyania; Michelle Ploughman; Donna Cheung; Jennifer Shaw; Judith Hall; Peter Nord; Sean Dukelow; Yongchai Nilanont; Felipe De Los Rios; Lisandro Olmos; Mindy Levin; Robert Teasell; Ashley Cohen; Kevin Thorpe; Andreas Laupacis; Mark Bayley
Journal:  Lancet Neurol       Date:  2016-06-27       Impact factor: 44.182

Review 5.  Robot-aided sensorimotor training in stroke rehabilitation.

Authors:  Bruce T Volpe; Hermano Igo Krebs; Neville Hogan
Journal:  Adv Neurol       Date:  2003

6.  The impact of mild stroke on meaningful activity and life satisfaction.

Authors:  Dorothy F Edwards; Michele Hahn; Carolyn Baum; Alexander W Dromerick
Journal:  J Stroke Cerebrovasc Dis       Date:  2006 Jul-Aug       Impact factor: 2.136

7.  Video capture virtual reality as a flexible and effective rehabilitation tool.

Authors:  Patrice L Weiss; Debbie Rand; Noomi Katz; Rachel Kizony
Journal:  J Neuroeng Rehabil       Date:  2004-12-20       Impact factor: 4.262

8.  Patient-Centered Robot-Aided Passive Neurorehabilitation Exercise Based on Safety-Motion Decision-Making Mechanism.

Authors:  Lizheng Pan; Aiguo Song; Suolin Duan; Zhuqing Yu
Journal:  Biomed Res Int       Date:  2017-01-16       Impact factor: 3.411

Review 9.  Recent Advances in the Therapeutic and Diagnostic Use of Liposomes and Carbon Nanomaterials in Ischemic Stroke.

Authors:  Lorena F Fernandes; Gisele E Bruch; André R Massensini; Frédéric Frézard
Journal:  Front Neurosci       Date:  2018-07-05       Impact factor: 4.677

10.  A task-specific interactive game-based virtual reality rehabilitation system for patients with stroke: a usability test and two clinical experiments.

Authors:  Joon-Ho Shin; Hokyoung Ryu; Seong Ho Jang
Journal:  J Neuroeng Rehabil       Date:  2014-03-06       Impact factor: 4.262

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