A Mixed-Signal VLSI System for Producing Temporally Adapting Intraspinal Microstimulation Patterns for Locomotion

Neural pathways can be artificially activated through the use of electrical stimulation. For individuals with a spinal cord injury, intraspinal microstimulation, using electrical currents on the order of 125 μA, can produce muscle contractions and joint torques in the lower extremities suitable for restoring walking. The work presented here demonstrates an integrated circuit implementing a state-based control strategy where sensory feedback and intrinsic feed forward control shape the stimulation waveforms produced on-chip. Fabricated in a 0.5 μm process, the device was successfully used in vivo to produce walking movements in a model of spinal cord injury. This work represents progress towards an implantable solution to be used for restoring walking in individuals with spinal cord injuries.

[1]  A. Prochazka,et al.  Spinal Cord Microstimulation Generates Functional Limb Movements in Chronically Implanted Cats , 2000, Experimental Neurology.

[2]  G. E. Goslow,et al.  The cat step cycle: Hind limb joint angles and muscle lengths during unrestrained locomotion , 1973, Journal of morphology.

[3]  Sergiy Yakovenko,et al.  Spatiotemporal activation of lumbosacral motoneurons in the locomotor step cycle. , 2002, Journal of neurophysiology.

[4]  Ralph Etienne-Cummings,et al.  Implementation of functional components of the Locomotion Processing Unit , 2011, 2011 IEEE Biomedical Circuits and Systems Conference (BioCAS).

[5]  R. J. Vogelstein,et al.  Restoring the sense of touch with a prosthetic hand through a brain interface , 2013, Proceedings of the National Academy of Sciences.

[6]  V. Mushahwar,et al.  Selective activation of muscle groups in the feline hindlimb through electrical microstimulation of the ventral lumbo-sacral spinal cord. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[7]  R. Stein,et al.  Feed forward and feedback control for over-ground locomotion in anaesthetized cats , 2012, Journal of neural engineering.

[8]  Vivian K Mushahwar,et al.  The effects of intraspinal microstimulation on spinal cord tissue in the rat. , 2010, Biomaterials.

[9]  J. F. Yang,et al.  Surface EMG profiles during different walking cadences in humans. , 1985, Electroencephalography and clinical neurophysiology.

[10]  Simon A. Overduin,et al.  Microstimulation Activates a Handful of Muscle Synergies , 2012, Neuron.

[11]  V. Mushahwar,et al.  A Physiologically-based Controller for Generating Overground Locomotion using Functional Electrical Stimulation , 2007 .

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

[13]  Alexander Kraskov,et al.  Ventral Premotor–Motor Cortex Interactions in the Macaque Monkey during Grasp: Response of Single Neurons to Intracortical Microstimulation , 2011, The Journal of Neuroscience.

[14]  M. Graziano,et al.  Complex Movements Evoked by Microstimulation of Precentral Cortex , 2002, Neuron.

[15]  Su Ling Chong,et al.  BIONic WalkAide for correcting foot drop , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[16]  Joseph E O'Doherty,et al.  A learning–based approach to artificial sensory feedback leads to optimal integration , 2014, Nature Neuroscience.

[17]  R B Stein,et al.  Locomotion Processing Unit , 2010, 2010 Biomedical Circuits and Systems Conference (BioCAS).

[18]  V. Mushahwar,et al.  Intraspinal microstimulation generates functional movements after spinal-cord injury , 2004, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[19]  A. Prochazka,et al.  Intraspinal micro stimulation generates locomotor-like and feedback-controlled movements , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[20]  A. Prochazka,et al.  Comparison of natural and artificial control of movement , 1993 .

[21]  Yasuhisa Hasegawa,et al.  Sit-to-Stand and Stand-to-Sit Transfer Support for Complete Paraplegic Patients with Robot Suit HAL , 2010, Adv. Robotics.

[22]  Robert G. Grossman,et al.  NeuroRex: A clinical neural interface roadmap for EEG-based brain machine interfaces to a lower body robotic exoskeleton , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[23]  R J Triolo,et al.  Muscle selection and walking performance of multichannel FES systems for ambulation in paraplegia. , 1997, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[24]  J Mizrahi,et al.  Recruitment, force and fatigue characteristics of quadriceps muscles of paraplegics isometrically activated by surface functional electrical stimulation. , 1990, Journal of biomedical engineering.

[25]  Tobi Delbrück,et al.  Bias Current Generators with Wide Dynamic Range , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[26]  R. Romo,et al.  Neuronal Correlates of a Perceptual Decision in Ventral Premotor Cortex , 2004, Neuron.

[27]  K W Horch,et al.  Muscle recruitment through electrical stimulation of the lumbo-sacral spinal cord. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[28]  K. Deisseroth,et al.  Optogenetics , 2013, Proceedings of the National Academy of Sciences.

[29]  L. Mertz,et al.  The Next Generation of Exoskeletons: Lighter, Cheaper Devices Are in the Works , 2012, IEEE Pulse.

[30]  Richard B. Stein,et al.  Restoring stepping after spinal cord injury using intraspinal microstimulation and novel control strategies , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[31]  A. Prochazka,et al.  Sensory control of locomotion: reflexes versus higher-level control. , 2002, Advances in experimental medicine and biology.

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

[33]  C. Kufta,et al.  Feasibility of a visual prosthesis for the blind based on intracortical microstimulation of the visual cortex , 1996 .

[34]  Philippe O. Pouliquen A ratioless and biasless static CMOS level shifter , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.

[35]  K. Pearson,et al.  Computer simulation of stepping in the hind legs of the cat: an examination of mechanisms regulating the stance-to-swing transition. , 2005, Journal of neurophysiology.

[36]  R B Stein,et al.  Real-time control of walking using recordings from dorsal root ganglia , 2013, Journal of neural engineering.

[37]  V. Mushahwar,et al.  Strategies for Generating Prolonged Functional Standing Using Intramuscular Stimulation or Intraspinal Microstimulation , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[38]  V. Vanderhorst,et al.  Organization of lumbosacral motoneuronal cell groups innervating hindlimb, pelvic floor, and axial muscles in the cat , 1997, The Journal of comparative neurology.

[39]  Bernhard A. Sabel,et al.  Changes in visual cortex excitability in blind subjects as demonstrated by transcranial magnetic stimulation. , 2002, Brain : a journal of neurology.

[40]  J. Halbertsma The stride cycle of the cat: the modelling of locomotion by computerized analysis of automatic recordings. , 1983, Acta physiologica Scandinavica. Supplementum.

[41]  Ralph Etienne-Cummings,et al.  A Silicon Central Pattern Generator Controls Locomotion in Vivo , 2008, IEEE Transactions on Biomedical Circuits and Systems.

[42]  R. Jacob Baker,et al.  CMOS Circuit Design, Layout, and Simulation , 1997 .

[43]  Nitish V. Thakor,et al.  Decoding of Individuated Finger Movements Using Surface Electromyography , 2009, IEEE Transactions on Biomedical Engineering.

[44]  H. Herr,et al.  Adaptive control of a variable-impedance ankle-foot orthosis to assist drop-foot gait , 2004, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[45]  S. Cogan Neural stimulation and recording electrodes. , 2008, Annual review of biomedical engineering.