Applications of Brain–Machine Interface Systems in Stroke Recovery and Rehabilitation

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 neurorehabilitation, 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.

[1]  H. S. Davis,et al.  A Controlled Study , 1966 .

[2]  R. Beaglehole,et al.  Recovery of motor function after stroke. , 1988, Stroke.

[3]  E Donchin,et al.  The mental prosthesis: assessing the speed of a P300-based brain-computer interface. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[4]  Kae Nakamura,et al.  Central mechanisms of motor skill learning , 2002, Current Opinion in Neurobiology.

[5]  M. Pepper,et al.  Design, development, and characteristics of an in-shoe triaxial pressure measurement transducer utilizing a single element of piezoelectric copolymer film , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[6]  Kaspar Althoefer,et al.  IEEE INT CONF ROBOT & AUTOMAT , 2003 .

[7]  M. Morari,et al.  Robotic Orthosis Lokomat: A Rehabilitation and Research Tool , 2003, Neuromodulation : journal of the International Neuromodulation Society.

[8]  V. Dietz,et al.  Biofeedback in gait training with the robotic orthosis Lokomat , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  Robert Riener,et al.  ARMin - robot for rehabilitation of the upper extremities , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[10]  Robert Riener,et al.  Robot-aided neurorehabilitation of the upper extremities , 2005, Medical and Biological Engineering and Computing.

[11]  P M Rossini,et al.  Neuroimaging experimental studies on brain plasticity in recovery from stroke. , 2007, Europa medicophysica.

[12]  Robert Riener,et al.  ARMin: a robot for patient-cooperative arm therapy , 2007, Medical & Biological Engineering & Computing.

[13]  H. van der Kooij,et al.  Design and Evaluation of the LOPES Exoskeleton Robot for Interactive Gait Rehabilitation , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[14]  E. Rocon,et al.  Lower-Limb Wearable Exoskeleton , 2007 .

[15]  B. Dobkin.  Brain–computer interface technology as a tool to augment plasticity and outcomes for neurological rehabilitation , 2007, The Journal of physiology.

[16]  Sandeep K Subramanian,et al.  Virtual reality environments for post-stroke arm rehabilitation , 2007, Journal of NeuroEngineering and Rehabilitation.

[17]  H.I. Krebs,et al.  Robot-Aided Neurorehabilitation: A Robot for Wrist Rehabilitation , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[18]  Shirley M Coyle,et al.  Brain–computer interface using a simplified functional near-infrared spectroscopy system , 2007, Journal of neural engineering.

[19]  Marcia Kilchenman O'Malley,et al.  Design, Control and Performance of RiceWrist: A Force Feedback Wrist Exoskeleton for Rehabilitation and Training , 2008, Int. J. Robotics Res..

[20]  H. Krebs,et al.  Effects of Robot-Assisted Therapy on Upper Limb Recovery After Stroke: A Systematic Review , 2008, Neurorehabilitation and neural repair.

[21]  J. Wolpaw,et al.  Brain–computer interfaces in neurological rehabilitation , 2008, The Lancet Neurology.

[22]  Bram Koopman,et al.  Body weight support by virtual model control of an impedance controlled exoskeleton (LOPES) for gait training. , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[23]  L. Der-Yeghiaian,et al.  Robot-based hand motor therapy after stroke. , 2007, Brain : a journal of neurology.

[24]  Ethan R. Buch,et al.  Think to Move: a Neuromagnetic Brain-Computer Interface (BCI) System for Chronic Stroke , 2008, Stroke.

[25]  Andrew S. Whitford,et al.  Cortical control of a prosthetic arm for self-feeding , 2008, Nature.

[26]  Eliane C Magdalon,et al.  Virtual reality environments to enhance upper limb functional recovery in patients with hemiparesis. , 2009, Studies in health technology and informatics.

[27]  I. Schwartz,et al.  The Effectiveness of Locomotor Therapy Using Robotic‐Assisted Gait Training in Subacute Stroke Patients: A Randomized Controlled Trial , 2009, PM & R : the journal of injury, function, and rehabilitation.

[28]  Cuntai Guan,et al.  A clinical study of motor imagery-based brain-computer interface for upper limb robotic rehabilitation , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[29]  S.K. Agrawal,et al.  Robot assisted gait training with active leg exoskeleton (ALEX) , 2009, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[30]  Sandeep K Subramanian,et al.  Kinematics of pointing movements made in a virtual versus a physical 3-dimensional environment in healthy and stroke subjects. , 2009, Archives of physical medicine and rehabilitation.

[31]  Daniel P. Ferris,et al.  Powered ankle exoskeletons reveal the metabolic cost of plantar flexor mechanical work during walking with longer steps at constant step frequency , 2009, Journal of Experimental Biology.

[32]  J. Hidler,et al.  Multicenter Randomized Clinical Trial Evaluating the Effectiveness of the Lokomat in Subacute Stroke , 2009, Neurorehabilitation and neural repair.

[33]  D. Mozaffarian,et al.  Heart disease and stroke statistics--2010 update: a report from the American Heart Association. , 2010, Circulation.

[34]  C. Neuper,et al.  Combining Brain–Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges , 2010, Front. Neurosci..

[35]  Grant D. Huang,et al.  Robot-assisted therapy for long-term upper-limb impairment after stroke. , 2010, The New England journal of medicine.

[36]  F. Champagne.  Epigenetic influence of social experiences across the lifespan. , 2010, Developmental psychobiology.

[37]  Cuntai Guan,et al.  Clinical study of neurorehabilitation in stroke using EEG-based motor imagery brain-computer interface with robotic feedback , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[38]  C. Braun,et al.  Combination of Brain-Computer Interface Training and Goal-Directed Physical Therapy in Chronic Stroke: A Case Report , 2010, Neurorehabilitation and neural repair.

[39]  Trent J. Bradberry,et al.  Reconstructing Three-Dimensional Hand Movements from Noninvasive Electroencephalographic Signals , 2010, The Journal of Neuroscience.

[40]  Jose L Pons,et al.  Rehabilitation Exoskeletal Robotics , 2010, IEEE Engineering in Medicine and Biology Magazine.

[41]  L. Zollo,et al.  Robotic technologies and rehabilitation: new tools for upper-limb therapy and assessment in chronic stroke. , 2011, European journal of physical and rehabilitation medicine.

[42]  José Luis Pons Rovira,et al.  Neurorobotic and hybrid management of lower limb motor disorders: a review , 2011, Medical & Biological Engineering & Computing.

[43]  Trent J. Bradberry,et al.  Fast attainment of computer cursor control with noninvasively acquired brain signals , 2011, Journal of neural engineering.

[44]  Michelle J. Johnson,et al.  Advances in upper limb stroke rehabilitation: a technology push , 2011, Medical & Biological Engineering & Computing.

[45]  Tadej Bajd,et al.  Rehabilitation robotics. , 2011, Technology and health care : official journal of the European Society for Engineering and Medicine.

[46]  R. Osu,et al.  Event related desynchronization-modulated functional electrical stimulation system for stroke rehabilitation: A feasibility study , 2012, Journal of NeuroEngineering and Rehabilitation.

[47]  Hyuk Oh,et al.  Cerebral cortical dynamics during visuomotor transformation: adaptation to a cognitive-motor executive challenge. , 2011, Psychophysiology.

[48]  M. Molinari,et al.  Rehabilitation of gait after stroke: a review towards a top-down approach , 2011, Journal of NeuroEngineering and Rehabilitation.

[49]  M. Grosse-Wentrup,et al.  Towards brain-robot interfaces in stroke rehabilitation , 2011, 2011 IEEE International Conference on Rehabilitation Robotics.

[50]  Vera Kaiser,et al.  First Steps Toward a Motor Imagery Based Stroke BCI: New Strategy to Set up a Classifier , 2011, Front. Neurosci..

[51]  J. Mcdonald,et al.  The changing field of rehabilitation: optimizing spontaneous regeneration and functional recovery. , 2012, Handbook of clinical neurology.

[52]  Corwin Boake,et al.  Robotic training and clinical assessment of upper extremity movements after spinal cord injury: a single case report. , 2012, Journal of rehabilitation medicine.

[53]  J. L. Contreras-Vidal,et al.  Restoration of Whole Body Movement: Toward a Noninvasive Brain-Machine Interface System , 2012, IEEE Pulse.

[54]  Robert Riener,et al.  Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study , 2013, Journal of NeuroEngineering and Rehabilitation.

[55]  Bram Koopman,et al.  Selective control of gait subtasks in robotic gait training: foot clearance support in stroke survivors with a powered exoskeleton , 2013, Journal of NeuroEngineering and Rehabilitation.

[56]  A. Lo,et al.  Clinical Designs of Recent Robot Rehabilitation Trials , 2012, American journal of physical medicine & rehabilitation.

[57]  Marcia Kilchenman O'Malley,et al.  System characterization of RiceWrist-S: A forearm-wrist exoskeleton for upper extremity rehabilitation , 2013, 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR).

[58]  Sook-Lei Liew,et al.  A clinical roadmap for brain-neural machine interfaces: trainees' perspectives on the 2013 international workshop , 2013, IEEE Pulse.

[59]  Atilla Kilicarslan,et al.  High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[60]  Georg Edelmayer,et al.  Home care robot for socially supporting the elderly: focus group studies in three European countries to screen user attitudes and requirements , 2013, International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation.

[61]  Jose L Pons,et al.  Development of a Exoskeleton for Lower Limb Rehabilitation , 2013 .

[62]  Nicola Vitiello,et al.  NEUROExos: A Powered Elbow Exoskeleton for Physical Rehabilitation , 2013, IEEE Transactions on Robotics.

[63]  P. F. M. J. Verschure,et al.  Using a Hybrid Brain Computer Interface and Virtual Reality System to Monitor and Promote Cortical Reorganization through Motor Activity and Motor Imagery Training , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[64]  Jae Jin Lee,et al.  Immediate effect of Walkbot robotic gait training on neuromechanical knee stiffness in spastic hemiplegia: a case report. , 2013, NeuroRehabilitation.

[65]  L. Cohen,et al.  Brain–machine interface in chronic stroke rehabilitation: A controlled study , 2013, Annals of neurology.

[66]  R. Gentili,et al.  Functional near-infrared spectroscopy-based correlates of prefrontal cortical dynamics during a cognitive-motor executive adaptation task , 2013, Front. Hum. Neurosci..

[67]  Hermano Igo Krebs,et al.  Clinical application of a modular ankle robot for stroke rehabilitation. , 2013, NeuroRehabilitation.

[68]  Rahsaan J. Holley,et al.  Robotic Therapy Provides a Stimulus for Upper Limb Motor Recovery After Stroke That Is Complementary to and Distinct From Conventional Therapy , 2014, Neurorehabilitation and neural repair.

[69]  J. L. Coronado,et al.  Neural Interfaces as Tools for Studying Brain Plasticity , 2014 .

[70]  Fitri Yakub,et al.  Recent trends for practical rehabilitation robotics, current challenges and the future , 2014, International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation.