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
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
10:30 ~ 11:00
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
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
16:00 ~ 16:30
Tea Break
16:30 ~ 17:30
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.
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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 3 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.
“Semi-invasive” 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.
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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
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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
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training for 1 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
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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
re-wires 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 2 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
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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 do 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).
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