Shanghai Symposium on Neural-Machine Interfacing

Shanghai Symposium on Neural-Machine Interfacing Time： June 16, 2015 Location ： Takata Hall, School of Mechanical Engineering, Shanghai Jiao Tong University (Dongchuan Road 800, Minhang Campus), Shanghai Sponsor: State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Agenda: 08:15 ~ 08:30 Opening Ceremony Morning Session 08:30 ~ 09:30 09:30 ~ 10:30 10:30 ~ 11:00 Chair：Xiangyang Zhu Chair：Dingguo Zhang Dominique Durand, USA Interfacing with Nervous System for Selective Stimulation and Recording Dario Farina, Germany Decoding the Neural Drive to Muscles for Prosthetic Control Tea Break 11:00 ~ 12:00 David Liebetanz, Germany Steer by Ear: Myoelectric Auricular Control of Powered Wheelchairs for Individuals with Spinal Cord Injury 12:00 ~ 14:00 Lunch Afternoon Session 14:00 ~ 15:00 15:00 ~16:00 16:00 ~ 16:30 16:30 ~ 17:30 Chair：Ning Jiang Nitish Thakor, USA Decoding Brain-Machine Interface: Semi-invasive ECoG Approaches Levi Hargrove, USA Development of a Neural Interface for Lower Limb Prostheses Tea Break Max Ortiz Catalan, Sweden Towards Natural Control of Artificial Limbs using Neuromuscular Electrodes via an Osseointegrated Implant 18:30 ~ 21:00 Dinner Invited Speakers Dominique Durand Case Western Reserve University, USA Biography: Dominique M Durand is E.L Linsedth Professor of Biomedical Engineering and Neurosciences and Director of the Neural Engineering Center at Case Western Reserve University in Cleveland, Ohio He received an engineering degree from Ecole Nationale Superieure d'Electronique, Hydrolique, Informatique et Automatique de Toulouse, France in 1973 In 1974, he received a M.S degree in Biomedical Engineering from CWRU in Cleveland OH., worked several years and in 1982 received a Ph.D in Electrical Engineering from the University of Toronto in the Institute of Biomedical Engineering He received an NSF Young Investigator Presidential Award as well as the Diekhoff and Wittke awards for graduate and undergraduate teaching and the Mortar board top-prof awards at CWRU He is an IEEE Fellow and also Fellow of the American Institute for Medical and Biomedical Engineering and Fellow of the Institute of Physics He serves on many editorial boards of peer-reviewed scientific journals and he is the editor-in-chief and founding editor of the Journal of Neural Engineering His research interests are in neural engineering and include computational neuroscience, neurophysiology and control of epilepsy, neural prostheses and applied magnetic and electrical field interactions with neural tissue Title: Interfacing with Nervous System for Selective Stimulation and Recording Abstract—Neural engineers have made significant breakthroughs in several areas such as the brain machine interface for locked-in patients, the retinal prosthesis for blind patients and deep brain stimulation for Parkinson’s patients Progress has also been made in the area of neural interfacing with the peripheral nervous system By reshaping or maintaining the nerve into an elongated shape, nerve interface electrodes have been designed that are capable of generating selective stimulation, and selective recording This Flat Interface Nerve Electrode (FINE) has been shown to be safe in animal experiments and has now been tested in human patients Computer simulations and experiments can activate selectively various fascicles Moreover, selective recording of fascicular activity can be achieved and activity in fascicles separated by distances greater that 1.5mm can be recovered with a cross-correlation coefficient greater than 0.85 Using this multi-contact cuff electrode controllers have been designed to activate joint dynamics with errors less than 5% for a frequency range less that 2Hz Therefore this FINE technology can provide a method to selectively recover and stimulate fascicular signals to restore neural function I will also present new technology for interfacing with the peripheral nervous system that takes advantage of nanotechnology for a stealthy implant Financial support for this work was provided by the National Institutes of Health (NINDS), US department of Education and the Lindseth endowed chair Nitish Thakor Johns Hopkins University, USA National University of Singapore, Singapore Biography: Nitish V Thakor (‘F 1994) is a Professor of Biomedical Engineering at Johns Hopkins University in the USA as well as the Director the Singapore Institute for Neurotechnology (SINAPSE) at the National University of Singapore Dr Thakor’s technical expertise is in the field of Neuroengineering, including neural instrumentation, nuromorphic engineering, neural microsystems, neural signal processing, optical imaging of the nervous system, neural control of prosthesis and brain machine interface He has pioneered many technologies for brain monitoring to prosthetic arms and neuroprosthesis He is an author of more than 270 refereed journal papers, more than a dozen patents, and co-founder of companies He is currently the Editor in Chief of Medical and Biological Engineering and Computing, and was the Editor in Chief of IEEE TNSRE from 2005-2011 and presently the EIC of Medical and Biological Engineering and Computing Dr Thakor is a recipient of a Research Career Development Award from the National Institutes of Health and a Presidential Young Investigator Award from the National Science Foundation, and is a Fellow of the American Institute of Medical and Biological Engineering, IEEE, Founding Fellow of the Biomedical Engineering Society, and Fellow of International Federation of Medical and Biological Engineering He is a recipient of the award of Technical Excellence in Neuroengineering from IEEE Engineering in Medicine and Biology Society, Distinguished Alumnus Award from Indian Institute of Technology, Bombay, India, and a Centennial Medal from the University of Wisconsin School of Engineering Title: Decoding Brain Machine Interface: Semi-invasive ECoG Approaches Abstract: Noninvasive, EEG-based, brain machine interfaces (BMIs) suffer from lower frequency and spatial resolution as well as low signal to noise ratio Implanted microelectrode arrays provide very fine spatial and temporal resolutions but may not be suitable for chronic stimulation at this time due to the unsolved problems of electrode-tissue reactivity and stability of recording “Semiinvasive” approach of Electrocorticograph (ECoG) recording provides a compromise of improved spatial (sub-mm range) and signal frequency resolution (in high-gamma range), and potentially less trauma as the electrodes are non-penetrating ECoG signals carry information in both low frequency (local motor potential) and high frequency (high gamma bands) These signals can be decoded by conventional spectral methods to derive control of individual fingers, grasps and reaches However, network based approaches provide better understanding of the connectivity of different regions of the brain involved in dexterous movements Limitations of purely cortical BMI encouraged us to develop a hybrid system, HARMONIE, which combines external visual and spatial information from sensors with the internal cortical control signals to generate a more practical BMI system for control of dexterous prosthesis Future challenges include improving the electrode and completely indwelling technology, generating a better temporal resolution, and incorporating sensory feedback Dario Farina University Medical Center Göttingen, Germany Biography: Dario Farina received the M.Sc degree in electronics engineering from Politecnico di Torino, Torino, Italy, in 1998, and the Ph.D degrees in automatic control and computer science and in electronics and communications engineering from the Ecole Centrale de Nantes, Nantes, France, and Politecnico di Torino, respectively, in 2002 During 2002–2004, he was a Research Assistant Professor at Politecnico di Torino and in 2004–2008 an Associate Professor in Biomedical Engineering at Aalborg University, Aalborg, Denmark From 2008 to 2010, he was Full Professor in Motor Control and Biomedical Signal Processing and Head of the Research Group on Neural Engineering and Neurophysiology of Movement at Aalborg University In 2010, he was appointed Full Professor and Founding Chair of the Department of Neurorehabilitation Engineering, University Medical Center Göttingen, Georg-August University, Germany, within the Bernstein Center for Computational Neuroscience He is also the Chair for Neuroinformatics of the Bernstein Focus Neurotechnology Göttingen His research focuses on biomedical signal processing, modeling, neurorehabilitation technology, and neural control of movement Within these areas, he has (co)-authored approximately 300 papers in peer-reviewed journals and over 300 among conference papers/abstracts, book chapters, and encyclopedia contributions He is also an Editor of the book “Introduction to Neural Engineering for Motor Rehabilitation” (IEEE/Wiley) He is an Associate Editor of Medical & Biological Engineering & Computing and of the Journal of Electromyography and Kinesiology and member of the Editorial Board of the Journal of Neuroscience Methods Dr Farina has been the Vice-President of the International Society of Electrophysiology and Kinesiology (ISEK) from 2010 to 2012 and is currently President of ISEK Among other recognitions and awards, he has been the recipient of the 2010 IEEE Engineering in Medicine and Biology Society Early Career Achievement Award for his contributions to biomedical signal processing and to electrophysiology and has been elected IEEE Engineering in Medicine and Biology Distinguished Lecturer for the term 2014-2015 He is an Associate Editor of IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING and of IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING Title: Decoding the Neural Drive to Muscles for Prosthetic Control Abstract: Classic methods of active prosthesis control, in both industry and academia, are based on the extraction of global features from the EMG signals recorded from remnant muscles, such as the signal amplitude In these approaches, the information extracted from the EMG is limited to the signal power and, in some cases, the spectral bandwidth However, the EMG, recorded invasively or non-invasively, contains much richer information since it is the sum of the electrical activities of muscle fibers triggered by the action potentials discharged by the motor neuron pool In this view, the EMG can be modeled as the convolutive mixture of spike trains, filtered by impulse responses that correspond to the muscle fiber action potentials Theoretically, it is possible to separate from the EMG the individual sources and therefore to estimate the timings of activation of the motor neurons innervating the muscle The ensemble of these timings is referred to as the neural drive to the muscle We show that this convolutive blind source separation problem can be practically solved, with the possibility of accurately extracting the activity of tens of motor neurons concurrently during voluntary activity (decoding the neural drive to muscles) This information provides a decoding of the ultimate neural code for movement generation and therefore can be used for a very precise prosthesis control We show results of this innovative approach in patients that underwent targeted muscle reinnervation David Liebetanz Georg-August-University, Germany Biography: David Liebetanz is Board certified Neurologist and Associate Professor at the Department of Clinical Neurophysiology of the Georg-August-University, Goettingen, where heheads the laboratory of experimental neuroplasticity He isclinical director of the Neurological Department at the der Rehabilitation Hospital in Bad Karlshafen, Germany, Member of the Bernstein Centre for Computational Neuroscience (BMBF) and a leading expert in non-invasive brain stimulation in animals and humans He received his medical education at the Universities of Marburg, Goettingen and Copenhagen He obtained his Doctoral graduation at the MPI for Biophysical Chemistry, Department of Neurobiology, Goettingen He received grants from various funding organizations, including the German Research Foundation Fields of interest include non-invasive brain stimulation (tDCS, TMS), neuroprosthetics and neurorehabilitation, neuromuscular disorders and botulinum toxin He filed patents for an alternative control system of rehabilitation devices using auricular muscles in tetraplegia and for the TH-Electrode, a novel transcutaneous H-electrode for chronic high density EMG recording in humans He received the Interlake Leadership Award and the Award Action Beny and Co for is work on neuromuscular diseases Title: Steer by Ear: Myoelectric Auricular Control of Powered Wheelchairs for Individuals with Spinal Cord Injury Abstract: Providing mobility solutions for individuals with tetraplegia remains challenging Up to now, control systems for wheelchair users with tetraplegia present severe shortcomings (e.g in signal quality, utility and interference with daily life activities), which render independent mobility often impossible for individuals with high-level tetraplegia To overcome these limitations, we present a novel myoelectric auricular control system (ACS) based on a bilateral activation of the posterior auricular muscles (PAMs), which are fully functional even in high-level tetraplegia Using a wireless EMG-recording interface, ten able-bodied subjects and two individuals with tetraplegia practiced PAM activation over four days using visual feedback and software-based training for h/day Half of these subjects were not able to voluntarily activate their PAMs Performance of the ACS was assessed by eight tests, including lateralized activation, reaction times, contraction rate, and speed and path length in a virtual obstacle course All parameters improved significantly over the training period By day five, all subjects successfully generated basic steering commands using the ACS in a powered wheelchair Subjects with tetraplegia were moreover able to navigate the wheelchair through a complex real-world obstacle course with the ACS This study shows for the first time that voluntary PAM activation can be learned, trained, lateralized and, most importantly, employed for wheelchair control With the ACS we can exploit the untapped potential of the PAMs by assigning them a new, complex function The inherent advantages of the ACS –non-interference with oral communication, robustness, stability over time, proportional and continuous signal generation – meet the specific needs of wheelchair users and render it a promising alternative to other human machine interfaces with application fields whenever hands-free control is advantageous Levi Hargrove Rehabilitation Institution of Chicago, USA Biography: Levi Hargrove, PhD, graduated from the University of New Brunswick in Fredericton, Canada His research focuses on developing clinically robust control systems for robotic arm and leg prostheses Dr Hargrove is currently the director of the Neural Engineering for Prosthetics and Orthotics Laboratory at the Rehabilitation Institution of Chicago’s prestigious Center for Bionic Medicine His team has applied neural-decoding techniques to provide intuitive control of prosthetics arms When coupled with a novel surgical technique, called targeted muscle reinnervation also pioneered at the Center for Bionic Medicine, proximal level amputees can naturally control a robotic elbow, wrist, and hand multi-articulating hand More recently, Dr Hargrove has been leading the development of a control system for a robotic leg prosthesis The goal of this research is to incorporate electromyographic (EMG) signals into the control system and allow patients to ambulate safely spontaneously over a broad range of terrains Dr Hargrove will be discussing the principles behind targeted muscle reinnervation and how it has been used in combination with advanced prosthetic limb technologies to provide unprecedented control for individuals with lower limb amputations Although a relatively young researcher, Dr Hargrove has authored over 45 peer-reviewed journal articles in top academic journals His research group has received significant media attention resulting in articles published in National Geographic Magazine, Wired Magazine, Engadget, Popular Mechanics, Discover Magazine, O-the Oprah magazine in addition to many daily newspapers His research efforts are currently sponsored by the Department of Defense, the National Institutes of Health and the National Science Foundation Dr Hargrove also has an Assistant Professor appointment in the Department of Physical Medicine and Rehabilitation at Northwestern University’s Feinberg School of Medicine, is a member of the IEEE society, the International Society of Electromyography and Kinesiology, and is a registered Professional Engineer in the province of New Brunswick Canada Title: Development of a Neural Interface for Lower Limb Prostheses Abstract: Amputation is a major cause of disability across the globe and is treated most effectively with a prosthetic limb Recent advances in robotics have allowed for the creating of strong, lightweight and energy-efficient prosthetics We, at the Center for Bionic Medicine, part of the Rehabilitation Institute of Chicago, have developed a technique called targeted muscle reinnervation, which rewires the nerves of amputee patients and provides a rich source of neural information that can be used to control prosthetic limbs Originally developed for controlling upper-limb prostheses we have now been working to extend this neural interface for powered legs, an emerging class of prosthetic limbs that are now reaching the market In this talk, I will describe the targeted muscle reinnervation procedure for lower-limbs, provide an overview of our control algorithms, and provide quantitative data supporting the use of EMG signals to improve ambulation Finally, I will show preliminary data showing how EMG signals may be incorporated into an adaptive control framework so that the signals can be used in a clinically viable manner Max Ortiz Catalan Chalmers University of Technology, Sweden Biography: Dr Max Ortiz Catalan received his Electronics Engineering degree in 2005 by the ITEMS Campus Toluca, Mexico He spent one year of his engineering formation at the Université de Technologie de Compiègne, France He worked years in industrial automation before joining the M.Sc.programin Complex Adaptive System, at Chalmers University of Technology (CTH), Sweden, graduating in 2009 In 2014, he obtained his PhD in Biomedical Engineering from CTH in collaboration with the Centre of Orthopaedic Osseointegration at Sahlgrenska University Hospital (COO-SUH), and Integrum AB, Sweden During his PhD, he was invited researcher at Neural Rehabilitation Engineering Lab in the Université chatolique de Louvain, Belgium, and Research Engineer at Integrum AB He is currently Research Scientist at CTH and COO-SUH, as well as R&D Manager at Integrum AB His research interests include bioelectric signals acquisition electronics (analog and digital); signal processing and artificial intelligence algorithms for pattern recognition and control; neuromuscular interfaces; bone-anchored prostheses and osseointegration; as well as virtual and augmented reality for neuromuscular rehabilitation and the treatment of phantom limb pain He has won several academic and industrial awards such as “Leadership and Academic Excellence” by ITESM, Mexico; the “Young Scientist Forum Scholarship” by GöteborgBio, Sweden; the youngest recipient of the “You Can Make a Difference Award” by one of the world’s largest transnational companies; and the “European Youth Award” by the European Council Title: Towards Natural Control of Artificial Limbs using Neuromuscular Electrodes via an Osseointegrated Implant Abstract: Although bionic limb replacement was devised since the 1960’s, artificial limbs are still far from the functionality of their biological counterpart Furthermore, the technology used back then is still the state-of-art in clinical practice Current prosthetic devices not purposely provide sensory feedback and are known for their poor functionality, mainly due to the use of superficial electrodes Implanted neuromuscular electrodes have been long-thought as a solution to provide a more natural control of prosthetic limbs However, their clinical utilization has been hindered by the lack of a long-term stable trans-/per-cutaneous interface It is therefore important to stress that regardless of the sophistication of the neural electrodes and robotic prostheses, a realistic clinically implementation is not possible if implanted and external devices cannot safely and reliably communicate As a solution for this problem, our group at Chalmers University of Technology, the Centre of Orthopaedic Osseointegration at Sahlgrenska University Hospital (COO-SUH), and Integrum AB, has developed an osseointegrated bidirectional interface into the human body This development made possible, for the first time, that a patient utilizes implanted neuromuscular electrodes for the daily control of his prosthetic arm outside controlled environments (video 1, 2) This patient is the first person in the world to have permanently implanted electrodes in nerves and muscles to control a robotic prosthesis at home and work, but more importantly, he has done so for two years without complications, thus demonstrating the feasibility of this novel technology The prosthesis is directly attach to the skeleton via orthopaedic osseointegration, a technology pioneered by our group, and long-term stable appropriate sensory perception has been also demonstrated using direct neurostimulation This talk will focus on the bidirectional osseointegrated interface, neural and muscular electrodes, neurostimulation for sensory feedback, and pattern recognition algorithms for control (video 3), as well as our latest work on a novel treatment of phantom limb pain using virtual and augmented reality (video 4) ... technology pioneered by our group, and long-term stable appropriate sensory perception has been also demonstrated using direct neurostimulation This talk will focus on the bidirectional osseointegrated... IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING and of IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING Title: Decoding the Neural Drive to Muscles for Prosthetic Control Abstract:... new, complex function The inherent advantages of the ACS –non-interference with oral communication, robustness, stability over time, proportional and continuous signal generation – meet the specific