Literature DB >> 28597018

Robotic devices and brain-machine interfaces for hand rehabilitation post-stroke.

Alistair C McConnell1, Renan C Moioli, Fabricio L Brasil, Marta Vallejo, David W Corne, Patricia A Vargas, Adam A Stokes.   

Abstract

OBJECTIVE: To review the state of the art of robotic-aided hand physiotherapy for post-stroke rehabilitation, including the use of brain-machine interfaces. Each patient has a unique clinical history and, in response to personalized treatment needs, research into individualized and at-home treatment options has expanded rapidly in recent years. This has resulted in the development of many devices and design strategies for use in stroke rehabilitation.
METHODS: The development progression of robotic-aided hand physiotherapy devices and brain-machine interface systems is outlined, focussing on those with mechanisms and control strategies designed to improve recovery outcomes of the hand post-stroke. A total of 110 commercial and non-commercial hand and wrist devices, spanning the 2 major core designs: end-effector and exoskeleton are reviewed.
RESULTS: The growing body of evidence on the efficacy and relevance of incorporating brain-machine interfaces in stroke rehabilitation is summarized. The challenges involved in integrating robotic rehabilitation into the healthcare system are discussed.
CONCLUSION: This review provides novel insights into the use of robotics in physiotherapy practice, and may help system designers to develop new devices.

Entities:  

Mesh:

Year:  2017        PMID: 28597018     DOI: 10.2340/16501977-2229

Source DB:  PubMed          Journal:  J Rehabil Med        ISSN: 1650-1977            Impact factor:   2.912


  10 in total

1.  Effectiveness of interventions to improve hand motor function in individuals with moderate to severe stroke: a systematic review protocol.

Authors:  Hewei Wang; Ray Arceo; Shugeng Chen; Li Ding; Jie Jia; Jun Yao
Journal:  BMJ Open       Date:  2019-09-27       Impact factor: 2.692

2.  Brain-computer interface robotics for hand rehabilitation after stroke: a systematic review.

Authors:  Paul Dominick E Baniqued; Emily C Stanyer; Muhammad Awais; Ali Alazmani; Andrew E Jackson; Mark A Mon-Williams; Faisal Mushtaq; Raymond J Holt
Journal:  J Neuroeng Rehabil       Date:  2021-01-23       Impact factor: 4.262

3.  Exploring New Potential Applications for Hand Exoskeletons: Power Grip to Assist Human Standing.

Authors:  Jorge A Diez; Victor Santamaria; Moiz I Khan; José M Catalán; Nicolas Garcia-Aracil; Sunil K Agrawal
Journal:  Sensors (Basel)       Date:  2020-12-23       Impact factor: 3.576

4.  Motor Imagery-Based Brain-Computer Interface Combined with Multimodal Feedback to Promote Upper Limb Motor Function after Stroke: A Preliminary Study.

Authors:  Yi-Qian Hu; Tian-Hao Gao; Jie Li; Jia-Chao Tao; Yu-Long Bai; Rong-Rong Lu
Journal:  Evid Based Complement Alternat Med       Date:  2021-11-03       Impact factor: 2.629

5.  Testing of a 3D printed hand exoskeleton for an individual with stroke: a case study.

Authors:  Drew R Dudley; Brian A Knarr; Ka-Chun Siu; Jean Peck; Brian Ricks; Jorge M Zuniga
Journal:  Disabil Rehabil Assist Technol       Date:  2019-08-06

6.  Effects of brain-computer interface training on upper limb function recovery in stroke patients: A protocol for systematic review and meta-analysis.

Authors:  Xiali Xue; Huan Tu; Zhongyi Deng; Ling Zhou; Ning Li; Xiaokun Wang
Journal:  Medicine (Baltimore)       Date:  2021-06-11       Impact factor: 1.817

7.  Development of a Low-Cost EEG-Controlled Hand Exoskeleton 3D Printed on Textiles.

Authors:  Rommel S Araujo; Camille R Silva; Severino P N Netto; Edgard Morya; Fabricio L Brasil
Journal:  Front Neurosci       Date:  2021-06-25       Impact factor: 4.677

Review 8.  Challenges and Opportunities for the Future of Brain-Computer Interface in Neurorehabilitation.

Authors:  Colin Simon; David A E Bolton; Niamh C Kennedy; Surjo R Soekadar; Kathy L Ruddy
Journal:  Front Neurosci       Date:  2021-07-02       Impact factor: 4.677

9.  Comparison of EEG measurement of upper limb movement in motor imagery training system.

Authors:  Arpa Suwannarat; Setha Pan-Ngum; Pasin Israsena
Journal:  Biomed Eng Online       Date:  2018-08-02       Impact factor: 2.819

10.  Reliability, validity and discriminant ability of a robotic device for finger training in patients with subacute stroke.

Authors:  Marco Germanotta; Valerio Gower; Dionysia Papadopoulou; Arianna Cruciani; Cristiano Pecchioli; Rita Mosca; Gabriele Speranza; Catuscia Falsini; Francesca Cecchi; Federica Vannetti; Angelo Montesano; Silvia Galeri; Furio Gramatica; Irene Aprile
Journal:  J Neuroeng Rehabil       Date:  2020-01-03       Impact factor: 4.262

  10 in total

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