Table Of ContentRehabilitation
Robotics
Rehabilitation
Robotics
Technology and Application
Edited by
Roberto Colombo
Vittorio Sanguineti
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Contributors
Dino Accoto
Università Campus Bio-medico di Roma, Rome, Italy
Angelo Basteris
Nanyang Technological University, Singapore
David T. Bundy
University of Kansas Medical Center, Kansas City, KS, United States
Etienne Burdet
Imperial College of Science, Technology, and Medicine, London, United
Kingdom; Nanyang Technological University, Singapore
Andrew J. Butler
Lewis College of Nursing and Health Professions, Georgia State University,
Atlanta, GA, United States
Domenico Campolo
Nanyang Technological University, Singapore
Maura Casadio
University of Genova; Italian Institute of Technology, Genova, Italy
Karen Sui-Geok Chua
Tan Tock Seng Hospital, Singapore
Roberto Colombo
IRCCS Istituti Clinici Scientifici Maugeri Spa SB, Pavia, Italy
Sara Contu
Nanyang Technological University, Singapore
Martina Coscia
Wyss Center for Bio- and Neuroengineering, Geneva; École Polytechnique
Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Kevin C. Elliott
University of Kansas Medical Center, Kansas City, KS, United States
Peter Feys
Hasselt University, Hasselt, Belgium
Joana Figueiredo
University of Minho, Guimarães, Portugal
Kathleen Fitzgerald
Lewis College of Nursing and Health Professions, Georgia State University,
Atlanta, GA, United States
Antonio Frisoli
Scuola Superiore Sant'Anna Via Alamanni, Pisa, Italy
xv
xvi Contributors
Roger Gassert
ETH Zurich, Zurich, Switzerland
David J. Guggenmos
University of Kansas Medical Center, Kansas City, KS, United States
Eugenio Guglielmelli
Università Campus Bio-medico di Roma, Rome, Italy
Stephen N. Housley
Lewis College of Nursing and Health Professions, Georgia State University,
Atlanta, GA, United States
Asif Hussain
Nanyang Technological University, Singapore
Riccardo Iandolo
University of Genova; Italian Institute of Technology, Genova, Italy
Nathanaël Jarrassé
Sorbonne University, UPMC, Paris, France
Simone Kager
Nanyang Technological University, Singapore
Dinh Binh Khanh
Nanyang Technological University, Singapore
Verena Klamroth-Marganska
ETH Zurich, Zürich; University of Zurich, Zurich, Switzerland
Hermano Igo Krebs
Massachusetts Institute of Technology, Cambridge, MA; University of Maryland
School of Medicine, Baltimore, MD, United States; Fujita Health University
School of Medicine, Nagoya, Japan; Newcastle University, Newcastle Upon
Tyne, United Kingdom; Osaka University, Osaka, Japan; Loughborough
University, Loughborough, United Kingdom
Olivier Lambercy
ETH Zurich, Zurich, Switzerland
Ilse Lamers
Hasselt University, Hasselt; Rehabilitation and MS center, Overpelt, Belgium
Yanan Li
Imperial College of Science, Technology, and Medicine, London; University of
Sussex, Brighton, United Kingdom
Laura Marchal-Crespo
Institute of Robotics and Intelligent Systems (IRIS), ETH; University of Zurich,
Zurich; University of Bern, Bern, Switzerland
Francesca Marini
Italian Institute of Technology, Genova, Italy
Lorenzo Masia
Nanyang Technological University, Singapore
Contributors xvii
Silvestro Micera
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne,
Switzerland; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
Matja Mihelj
ž
University of Ljubljana, Faculty of Electrical Engineering, Ljubljana, Slovenia
Vito Monaco
The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa; IRCSS Don Carlo
Gnocchi Foundation, Firenze, Italy
Pietro Morasso
Italian Institute of Technology, Genova, Italy
Juan C. Moreno
Cajal Institute, Madrid, Spain
Marko Munih
University of Ljubljana, Faculty of Electrical Engineering, Ljubljana, Slovenia
Sara Nataletti
University of Genova; Italian Institute of Technology, Genova, Italy
Domen Novak
University of Wyoming, Laramie, WY, United States
Randolph J. Nudo
University of Kansas Medical Center, Kansas City, KS, United States
Sandra W. Petersen
The University of Texas at Tyler, Tyler, TX, United States
Valentina Ponassi
University of Genova, Genova, Italy
José L. Pons
Cajal Institute, Madrid, Spain
Dejan B. Popovi
ć
Serbian Academy of Sciences and Arts, Belgrade, Serbia; Aalborg University,
Aalborg, Denmark
Raffaele Ranzani
ETH Zurich, Zurich, Switzerland
Robert Riener
Institute of Robotics and Intelligent Systems (IRIS), ETH; University of Zurich,
Zurich, Switzerland
Agnès Roby-Brami
Sorbonne University, UPMC, Paris, France
Vittorio Sanguineti
University of Genova, Genova, Italy
Robert A. Scheidt
Marquette University, Milwaukee, WI, United States
xviii Contributors
Giulia Sedda
University of Genova, Genova, Italy
Davide Simonetti
Università Campus Bio-medico di Roma, Rome, Italy
Susanna Summa
Bambino Gesù Children's Hospital IRCCS, Rome, Italy
Eva Swinnen
Vrije Universiteit Brussel, Brussel, Belgium
Nevio L. Tagliamonte
Università Campus Bio-medico di Roma; S. Lucia Foundation, Rome, Italy
Peppino Tropea
The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa; Casa Cura
Policlinico, Milano, Italy
Andrea Turolla
IRCCS San Camillo Hospital Foundation, Venice, Italy
Antuvan Chris Wilson
Nanyang Technological University, Singapore
Michele Xiloyannis
Nanyang Technological University, Singapore
Kim Giovanni Yongtae
Nanyang Technological University, Singapore
Loredana Zollo
Università Campus Bio-medico di Roma, Rome, Italy
Rehabilitation Robotics:
Technology and Applications
The last decades have seen major advances in interventions for neuromotor rehabili-
tation. Forms of treatment based on repetitive exercise of coordinated motor activi-
ties have been proved effective in improving gait and arm functions and ultimately
the patients' quality of life. Exercise-based treatments constitute a significant burden
for therapists and are heavy consumers of health-care resources. Technologies such
as robotics and virtual reality can make them more affordable.
Rehabilitation robotics specifically focuses on systems—devices, exercise sce-
narios, and control strategies—aimed at facilitating the recovery of impaired sensory,
motor, and cognitive skills. The field has a relatively long history, dating back to the
early 1990s. Early attempts were part of the general trend toward automating heavy
tasks by using “intelligent” machines, with minimal human intervention. The notion
of “artificial therapist” was common in early scientific papers and patent applications.
However, the most distinctive feature of these devices is not their ability to “automate”
treatment but, rather, that of precisely quantifying sensorimotor performance during
exercise, in terms of movement kinematics and exchanged forces. This resulted in a
gradual shift toward more evidence-based and data-driven forms of treatment. Present-
generation rehabilitation robots are designed as complements, rather than substitutes,
of the therapist's work. They support the recovery of functions by efficiently exploiting
structure and adaptive properties of the human sensorimotor systems and provide rich
information on sensorimotor performance and their evolution. Their design, implemen-
tation, and modalities of intervention incorporate findings from behavioral studies on
sensorimotor adaptation and motor skill learning and their neural substrates.
Rehabilitation robotics is therefore characterized by highly specific design ap-
proaches and technical solutions, with roots in both engineering and neurophysiology.
This book addresses both technology and application aspects of Rehabilitation
Robotics. Part I focuses on the state of the art and representative advancements in
the design, control, analysis, and implementation of rehabilitation robots and the
underlying neurophysiological principles. Part II addresses the existing applications
and the clinical validation of these systems, with a special emphasis on therapy ro-
bots, which support exercise-based treatments aimed at recovering sensorimotor or
cognitive functions.
PART I: BACKGROUND AND TECHNOLOGY
NEUROPHYSIOLOGY
Planning and execution of movements results from the coordinated activity of mul-
tiple interconnected sensory and motor areas in the cerebral cortex. When an area in
this specialized motor network is damaged—for example, through a traumatic brain
xix
xx Rehabilitation robotics: Technology and applications
injury or an ischemic event—the activity of the motor networks can be disrupted,
thus leading to functional deficits. How the surviving motor networks reorganize to
compensate for the injury depends on the location and extent of the lesion but may
be affected by sensorimotor exercise.
Chapter 1 summarizes how neuroplasticity modifies motor networks in response
to injury, by focusing on the changes after a cerebrovascular accident in the primary
motor cortex. Neuroanatomical and neurophysiological evidence in animal models
and human stroke survivors is reviewed to demonstrate how injuries functionally
impair motor networks, how motor networks compensate for the lesion to improve
motor function, and how selected therapies may facilitate recovery.
Chapter 2 focuses on the hierarchical architecture and synergistic functioning of
the motor system. These aspects are crucial for the development of successful robot-
ics applications with rehabilitation purposes. The same framework is used to discuss
the mechanisms underlying rehabilitation interventions with a potential to facilitate
the recovery process.
TECHNOLOGY AND DESIGN CONCEPTS
Devices for rehabilitation benefit from advances in robot technologies, including
sensors and actuators, mechanical architectures, and the corresponding control archi-
tectures. These devices are characterized by a continuous interaction with the human
body, which poses specific design constraints.
Chapter 3 summarizes the notion of “biomechatronic” design for systems for
robot-mediated rehabilitation, encompassing robot structure, musculoskeletal bio-
mechanics, and neural control. Robots for rehabilitation are typically conceived to
constantly work in constrained motion with the human body, which represents a
challenge for designers. This requires a top-down design approach, in which a model
of the human agent guides a concurrent, iterative design cycle of the robot's mechani-
cal, electronic, and multilayered control subsystems. Criteria for the identification
of functional and technical specifications and the selection of key components of
the robotic system are also derived. Two design case studies demonstrate how these
design principles are translated into practice.
Chapter 4 addresses how actuators play a critical role in defining the charac-
teristics of the robot-patient interaction. The different options for actuating and
controlling a rehabilitation device are discussed, considering the complex flow of
information between the user and the robot during a rehabilitation task. Strategies
for both high- and low-level control are presented. Impedance and admittance
control modalities are discussed as means of decoding human intention and/or
modulating the assistive forces delivered by the robot. Mathematical tools for
model-based compensation of nonlinear phenomena (backlash and friction) are
also presented.
The way robots are used to facilitate training is crucial for their application to
therapy and has important implications for their mechanical and control design.
Intensity and frequency of practice are major determinants of the recovery process,
