Collaborative Approach in the Development of High‐Performance Brain–Computer Interfaces for a Neuroprosthetic Arm: Translation from Animal Models to Human Control

Our research group recently demonstrated that a person with tetraplegia could use a brain–computer interface (BCI) to control a sophisticated anthropomorphic robotic arm with skill and speed approaching that of an able‐bodied person. This multiyear study exemplifies important principles in translating research from foundational theory and animal experiments into a clinical study. We present a roadmap that may serve as an example for other areas of clinical device research as well as an update on study results. Prior to conducting a multiyear clinical trial, years of animal research preceded BCI testing in an epilepsy monitoring unit, and then in a short‐term (28 days) clinical investigation. Scientists and engineers developed the necessary robotic and surgical hardware, software environment, data analysis techniques, and training paradigms. Coordination among researchers, funding institutes, and regulatory bodies ensured that the study would provide valuable scientific information in a safe environment for the study participant. Finally, clinicians from neurosurgery, anesthesiology, physiatry, psychology, and occupational therapy all worked in a multidisciplinary team along with the other researchers to conduct a multiyear BCI clinical study. This teamwork and coordination can be used as a model for others attempting to translate basic science into real‐world clinical situations.

[1]  R. Jacob Vogelstein,et al.  A Real-Time Virtual Integration Environment for Neuroprosthetics and Rehabilitation , 2011 .

[2]  Erik Scheme,et al.  A real-time virtual integration environment for the design and development of neural prosthetic systems , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  Nicolas Y. Masse,et al.  Reach and grasp by people with tetraplegia using a neurally controlled robotic arm , 2012, Nature.

[4]  Donald W. Marquaridt Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation , 1970 .

[5]  A B Schwartz,et al.  Direct cortical representation of drawing. , 1994, Science.

[6]  Amanda C Rossman The physiology of the nicotinic acetylcholine receptor and its importance in the administration of anesthesia. , 2011, AANA journal.

[7]  M Fitzharris,et al.  The global map for traumatic spinal cord injury epidemiology: update 2011, global incidence rate , 2013, Spinal Cord.

[8]  N E Crone Functional mapping with ECoG spectral analysis. , 2000, Advances in neurology.

[9]  A. P. Georgopoulos,et al.  Cortical mechanisms related to the direction of two-dimensional arm movements: relations in parietal area 5 and comparison with motor cortex , 1983, Experimental Brain Research.

[10]  Jennifer L. Collinger,et al.  Classification of hand posture from electrocorticographic signals recorded during varying force conditions , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[11]  R. Lesser,et al.  Functional mapping of human sensorimotor cortex with electrocorticographic spectral analysis. I. Alpha and beta event-related desynchronization. , 1998, Brain : a journal of neurology.

[12]  Gustavo P. Sudre,et al.  Decoding semantic information from human electrocorticographic (ECoG) signals , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[13]  N. Crone,et al.  High-frequency gamma oscillations and human brain mapping with electrocorticography. , 2006, Progress in brain research.

[14]  David M. Santucci,et al.  Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates , 2003, PLoS biology.

[15]  Rasmus Ischebeck,et al.  Threshold for Trapping Positrons in the Wake Driven by a Ultra‐relativistic Electron Bunch , 2009 .

[16]  Dawn M. Taylor,et al.  Direct Cortical Control of 3D Neuroprosthetic Devices , 2002, Science.

[17]  Janice J Eng,et al.  Reorganization and preservation of motor control of the brain in spinal cord injury: a systematic review. , 2009, Journal of neurotrauma.

[18]  J. Wolpaw,et al.  Decoding two-dimensional movement trajectories using electrocorticographic signals in humans , 2007, Journal of neural engineering.

[19]  A. Schwartz,et al.  High-performance neuroprosthetic control by an individual with tetraplegia , 2013, The Lancet.

[20]  A. Schwartz,et al.  Work toward real-time control of a cortical neural prothesis. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[21]  A. Krassioukov,et al.  A systematic review of the management of autonomic dysreflexia after spinal cord injury. , 2009, Archives of physical medicine and rehabilitation.

[22]  T. N. Lal,et al.  Classifying EEG and ECoG signals without subject training for fast BCI implementation: comparison of nonparalyzed and completely paralyzed subjects , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[23]  D J Weber,et al.  Human motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movements , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[24]  H. Bae,et al.  Sevoflurane Concentrations Required to Block Autonomic Hyperreflexia during Transurethral Litholapaxy in Patients with Complete Spinal Cord Injury , 2008, Anesthesiology.

[25]  A P Georgopoulos,et al.  On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex , 1982, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[26]  I. Fried,et al.  Coupling Between Neuronal Firing, Field Potentials, and fMRI in Human Auditory Cortex , 2005, Science.

[27]  Jennifer L. Collinger,et al.  Craniux: A LabVIEW-Based Modular Software Framework for Brain-Machine Interface Research , 2011, Comput. Intell. Neurosci..

[28]  Jong Un Lee,et al.  Remifentanil Decreases Sevoflurane Requirements to Block Autonomic Hyperreflexia During Transurethral Litholapaxy in Patients with High Complete Spinal Cord Injury , 2011, Anesthesia and analgesia.

[29]  D. Wong,et al.  Surgical aspects of autonomic dysreflexia. , 1997, The journal of spinal cord medicine.

[30]  N Jeremy Hill,et al.  Recording human electrocorticographic (ECoG) signals for neuroscientific research and real-time functional cortical mapping. , 2012, Journal of visualized experiments : JoVE.

[31]  Monica A. Perez,et al.  Neural interface technology for rehabilitation: exploiting and promoting neuroplasticity. , 2010, Physical medicine and rehabilitation clinics of North America.

[32]  H. Yokoi,et al.  Electrocorticographic control of a prosthetic arm in paralyzed patients , 2012, Annals of neurology.

[33]  A. P. Georgopoulos,et al.  Primate motor cortex and free arm movements to visual targets in three- dimensional space. I. Relations between single cell discharge and direction of movement , 1988, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[34]  R. Lesser,et al.  Functional mapping of human sensorimotor cortex with electrocorticographic spectral analysis. II. Event-related synchronization in the gamma band. , 1998, Brain : a journal of neurology.

[35]  Kathryn Ziegler-Graham,et al.  Estimating the prevalence of limb loss in the United States: 2005 to 2050. , 2008, Archives of physical medicine and rehabilitation.

[36]  Michael L. Boninger,et al.  Toward Synergy-Based Brain-Machine Interfaces , 2011, IEEE Transactions on Information Technology in Biomedicine.

[37]  Naotaka Fujii,et al.  Long-Term Asynchronous Decoding of Arm Motion Using Electrocorticographic Signals in Monkeys , 2009, Front. Neuroeng..

[38]  Gerwin Schalk,et al.  A brain–computer interface using electrocorticographic signals in humans , 2004, Journal of neural engineering.

[39]  P. Hambly,et al.  Anaesthesia for chronic spinal cord lesions , 1998, Anaesthesia.

[40]  Kapil D. Katyal,et al.  Revolutionizing Prosthetics software technology , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

[41]  Jon A. Mukand,et al.  Neuronal ensemble control of prosthetic devices by a human with tetraplegia , 2006, Nature.

[42]  D. Moran,et al.  Cortical Adaptation to a Chronic Micro-Electrocorticographic Brain Computer Interface , 2013, The Journal of Neuroscience.

[43]  G. Schalk,et al.  Brain-Computer Interfaces Using Electrocorticographic Signals , 2011, IEEE Reviews in Biomedical Engineering.

[44]  Wei Wang,et al.  Sparse linear regression with elastic net regularization for brain-computer interfaces , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[45]  J. Martyn,et al.  Regulation of Skeletal Muscle Acetylcholine Receptors , 1993 .

[46]  K. Fish,et al.  Cardiovascular complications during anesthesia in chronic spinal cord injured patients. , 1981, Anesthesiology.

[47]  L. Miller,et al.  Restoration of grasp following paralysis through brain-controlled stimulation of muscles , 2012, Nature.

[48]  Michael J. Black,et al.  Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia , 2008, Journal of neural engineering.

[49]  Samuel T. Clanton,et al.  Brain-Computer Interface Control of an Anthropomorphic Robotic Arm , 2011 .

[50]  Miriam Zacksenhouse,et al.  Cortical Ensemble Adaptation to Represent Velocity of an Artificial Actuator Controlled by a Brain-Machine Interface , 2005, The Journal of Neuroscience.

[51]  D J Weber,et al.  A fuzzy logic model for hand posture control using human cortical activity recorded by micro-ECog electrodes , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[52]  R. Lyle A performance test for assessment of upper limb function in physical rehabilitation treatment and research , 1981, International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation.

[53]  R. Kass,et al.  Decoding and cortical source localization for intended movement direction with MEG. , 2010, Journal of neurophysiology.

[54]  M. Devivo,et al.  Trends in new injuries, prevalent cases, and aging with spinal cord injury. , 2011, Archives of physical medicine and rehabilitation.

[55]  A. P. Georgopoulos,et al.  Neuronal population coding of movement direction. , 1986, Science.

[56]  S. Meagher Instant neural control of a movement signal , 2002 .

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

[58]  Robin C. Ashmore,et al.  An Electrocorticographic Brain Interface in an Individual with Tetraplegia , 2013, PloS one.

[59]  B. Schoelkopf,et al.  Transition from the locked in to the completely locked-in state: A physiological analysis , 2011, Clinical Neurophysiology.

[60]  R. S. Jaffe,et al.  Up‐and-down Regulation of Skeletal Muscle Acetylcholine Receptors Effects on Neuromuscular Blockers , 1992, Anesthesiology.

[61]  Rajesh P. N. Rao,et al.  Cortical activity during motor execution, motor imagery, and imagery-based online feedback , 2010, Proceedings of the National Academy of Sciences.

[62]  E. Fetz Operant Conditioning of Cortical Unit Activity , 1969, Science.

[63]  Gerwin Schalk BCIs That Use Electrocorticographic Activity , 2012 .

[64]  R. Deane,et al.  Anesthesia and the Control of Blood Pressure in Patients with Spinal Cord Injury , 1982, Anesthesia and analgesia.

[65]  Stuart D. Harshbarger,et al.  An Overview of the Developmental Process for the Modular Prosthetic Limb , 2011 .