Literature DB >> 25110624

Applications of Brain-Machine Interface Systems in Stroke Recovery and Rehabilitation.

Anusha Venkatakrishnan1, Gerard E Francisco2, Jose L Contreras-Vidal1.   

Abstract

Stroke is a leading cause of disability, significantly impacting the quality of life (QOL) in survivors, and rehabilitation remains the mainstay of treatment in these patients. Recent engineering and technological advances such as brain-machine interfaces (BMI) and robotic rehabilitative devices are promising to enhance stroke neu-rorehabilitation, to accelerate functional recovery and improve QOL. This review discusses the recent applications of BMI and robotic-assisted rehabilitation in stroke patients. We present the framework for integrated BMI and robotic-assisted therapies, and discuss their potential therapeutic, assistive and diagnostic functions in stroke rehabilitation. Finally, we conclude with an outlook on the potential challenges and future directions of these neurotechnologies, and their impact on clinical rehabilitation.

Entities:  

Keywords:  Brain–machine interfaces; Clinical trials; Functional recovery; Neuroplasticity; Neurorehabilitation; Robotic exoskeletons; Robotic-assisted rehabilitation; Stroke

Year:  2014        PMID: 25110624      PMCID: PMC4122129          DOI: 10.1007/s40141-014-0051-4

Source DB:  PubMed          Journal:  Curr Phys Med Rehabil Rep        ISSN: 2167-4833


  57 in total

1.  Towards brain-robot interfaces in stroke rehabilitation.

Authors:  M Gomez-Rodriguez; M Grosse-Wentrup; J Hill; A Gharabaghi; B Scholkopf; J Peters
Journal:  IEEE Int Conf Rehabil Robot       Date:  2011

2.  Robot-based hand motor therapy after stroke.

Authors:  Craig D Takahashi; Lucy Der-Yeghiaian; Vu Le; Rehan R Motiwala; Steven C Cramer
Journal:  Brain       Date:  2007-12-20       Impact factor: 13.501

3.  Powered ankle exoskeletons reveal the metabolic cost of plantar flexor mechanical work during walking with longer steps at constant step frequency.

Authors:  Gregory S Sawicki; Daniel P Ferris
Journal:  J Exp Biol       Date:  2009-01       Impact factor: 3.312

4.  Body weight support by virtual model control of an impedance controlled exoskeleton (LOPES) for gait training.

Authors:  Herman van der Kooij; Bram Koopman; Edwin H F van Asseldonk
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2008

Review 5.  Neurorobotic and hybrid management of lower limb motor disorders: a review.

Authors:  Juan C Moreno; Antonio J Del Ama; Ana de Los Reyes-Guzmán; Angel Gil-Agudo; Ramón Ceres; José L Pons
Journal:  Med Biol Eng Comput       Date:  2011-08-17       Impact factor: 2.602

Review 6.  Clinical designs of recent robot rehabilitation trials.

Authors:  Albert C Lo
Journal:  Am J Phys Med Rehabil       Date:  2012-11       Impact factor: 2.159

7.  High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton.

Authors:  Atilla Kilicarslan; Saurabh Prasad; Robert G Grossman; Jose L Contreras-Vidal
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2013

Review 8.  Restoration of whole body movement: toward a noninvasive brain-machine interface system.

Authors:  José Contreras-Vidal; Alessandro Presacco; Harshavardhan Agashe; Andrew Paek
Journal:  IEEE Pulse       Date:  2012-01       Impact factor: 0.924

9.  Combination of brain-computer interface training and goal-directed physical therapy in chronic stroke: a case report.

Authors:  Doris Broetz; Christoph Braun; Cornelia Weber; Surjo R Soekadar; Andrea Caria; Niels Birbaumer
Journal:  Neurorehabil Neural Repair       Date:  2010-06-02       Impact factor: 3.919

Review 10.  Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review.

Authors:  Gert Kwakkel; Boudewijn J Kollen; Hermano I Krebs
Journal:  Neurorehabil Neural Repair       Date:  2007-09-17       Impact factor: 3.919

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  18 in total

1.  Current Trends in Robot-Assisted Upper-Limb Stroke Rehabilitation: Promoting Patient Engagement in Therapy.

Authors:  Amy A Blank; James A French; Ali Utku Pehlivan; Marcia K O'Malley
Journal:  Curr Phys Med Rehabil Rep       Date:  2014-09

2.  Improving robotic stroke rehabilitation by incorporating neural intent detection: Preliminary results from a clinical trial.

Authors:  Jennifer L Sullivan; Nikunj A Bhagat; Nuray Yozbatiran; Ruta Paranjape; Colin G Losey; Robert G Grossman; Jose L Contreras-Vidal; Gerard E Francisco; Marcia K O'Malley
Journal:  IEEE Int Conf Rehabil Robot       Date:  2017-07

3.  Concerns in the Blurred Divisions between Medical and Consumer Neurotechnology.

Authors:  Andrew Y Paek; Justin A Brantley; Barbara J Evans; Jose L Contreras-Vidal
Journal:  IEEE Syst J       Date:  2020-12-18       Impact factor: 4.802

4.  Gait adaptation to visual kinematic perturbations using a real-time closed-loop brain-computer interface to a virtual reality avatar.

Authors:  Trieu Phat Luu; Yongtian He; Samuel Brown; Sho Nakagame; Jose L Contreras-Vidal
Journal:  J Neural Eng       Date:  2016-04-11       Impact factor: 5.379

5.  The H2 robotic exoskeleton for gait rehabilitation after stroke: early findings from a clinical study.

Authors:  Magdo Bortole; Anusha Venkatakrishnan; Fangshi Zhu; Juan C Moreno; Gerard E Francisco; Jose L Pons; Jose L Contreras-Vidal
Journal:  J Neuroeng Rehabil       Date:  2015-06-17       Impact factor: 4.262

6.  Coarse electrocorticographic decoding of ipsilateral reach in patients with brain lesions.

Authors:  Guy Hotson; Matthew S Fifer; Soumyadipta Acharya; Heather L Benz; William S Anderson; Nitish V Thakor; Nathan E Crone
Journal:  PLoS One       Date:  2014-12-29       Impact factor: 3.240

7.  Control of an Ambulatory Exoskeleton with a Brain-Machine Interface for Spinal Cord Injury Gait Rehabilitation.

Authors:  Eduardo López-Larraz; Fernando Trincado-Alonso; Vijaykumar Rajasekaran; Soraya Pérez-Nombela; Antonio J Del-Ama; Joan Aranda; Javier Minguez; Angel Gil-Agudo; Luis Montesano
Journal:  Front Neurosci       Date:  2016-08-03       Impact factor: 4.677

8.  Face-Computer Interface (FCI): Intent Recognition Based on Facial Electromyography (fEMG) and Online Human-Computer Interface With Audiovisual Feedback.

Authors:  Bo Zhu; Daohui Zhang; Yaqi Chu; Xingang Zhao; Lixin Zhang; Lina Zhao
Journal:  Front Neurorobot       Date:  2021-07-16       Impact factor: 2.650

9.  Negligible Motion Artifacts in Scalp Electroencephalography (EEG) During Treadmill Walking.

Authors:  Kevin Nathan; Jose L Contreras-Vidal
Journal:  Front Hum Neurosci       Date:  2016-01-13       Impact factor: 3.169

10.  Factors of Influence on the Performance of a Short-Latency Non-Invasive Brain Switch: Evidence in Healthy Individuals and Implication for Motor Function Rehabilitation.

Authors:  Ren Xu; Ning Jiang; Natalie Mrachacz-Kersting; Kim Dremstrup; Dario Farina
Journal:  Front Neurosci       Date:  2016-01-21       Impact factor: 4.677

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