Neurorehabilitation Technology

David J. Reinkensmeyer • Volker Dietz Editors

Neurorehabilitation Technology

Second Edition

ISBN 978-3-319-28601-3 ISBN 978-3-319-28603-7 (eBook) DOI 10.1007/978-3-319-28603-7

Library of Congress Control Number: 2016948440

© Springer International Publishing 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifi cally the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfi lms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specifi c statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made.

Printed on acid-free paper

This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland

Editors David J. Reinkensmeyer University of California at Irvine Irvine California USA

Volker Dietz Spinal Cord Injury Center University Hospital Balgrist Zürich Switzerland

v

When I want to discover something , I begin by reading up everything that has been done along that line in the past – that ’ s what all these books in the library are for. I see what has been accomplished at great labor and expense in the past. I gather data of many thousands of experiments as a starting point , and then I make thou-sands more .

Attributed to Thomas Edison

The aim of this book is to provide a current overview of the ongoing revo-lution in neurorehabilitation technology. This revolution began in the late 1980s when several research groups, apparently beginning with a group at MIT, made the observation that robotic technologies could enhance rehabili-tation movement training by automating parts of it. Seminal work in neuro-plasticity emerging at the same time observed for the fi rst time that the nervous system retains a highly distributed capacity to alter its connectivity in response to repetitive sensory motor input even following severe damage and aging. Partially automating repetitive movement training was thus imagined as a way to increase movement therapy dose, improving recovery without increasing health care costs.

Thirty years later, tens and perhaps hundreds of companies worldwide now sell rehabilitation robotic technology. The most successful company is likely the Swiss company Hocoma. With the development of the gait orthosis ‘Lokomat’ in the early 1990s, Hocoma emerged as a spin-off from the Balgrist University Hospital in Zürich. It is now established well with over 1000 installations of its Lokomat gait orthosis, Armeo arm orthoses, and other technologies (its products and their evaluation are necessarily the focus of several chapters in the book). The number of papers published in rehabili-tation robotics has increased from a few per year to over 1000 annually. Systematic reviews of tens of randomized controlled trials now affi rm robotic training as a benefi cial supplement to conventional training.

Yet the benefi ts provided by these devices are incremental for most patients and the cost high enough to limit their use mainly to fl agship rehabilitation facilities. We are perhaps at a stage of invention similar to that of the light bulb in 1878. The best light bulbs in 1878 lasted only 13 h, despite the light bulb having been invented in 1802 by Humphry Davy. It would take Thomas Edison several more years of experimental and theoretical work to increase the average light bulb life to over 1000 h, thus producing one of the most impactful technologies of all time.

Preface to the Second Edition

vi

This second edition of Neurorehabilitation Technology details what might be described as the ongoing Edisonian process of improving neurorehabilita-tion technology. World leaders in their fi elds have taken the time to step back from their work, evaluate the state of the art in their fi eld, and trace the devel-opment of their own work in creating this state of the art. In their chapters, they detail improved knowledge of motor impairment and neuroplasticity mechanisms; this knowledge is fundamental for a principled approach to neu-rorehabilitation technology design. They describe how they have not only incorporated robotic devices into their clinical practice, but then further refi ned these technologies based on their clinical experience. They highlight the potential of combination therapies with drugs, electrical stimulation, and brain-computer interfaces, to increase functional benefi ts achievable beyond hard limits set by neural destruction. And they describe the beginnings of the second wave of innovation in neurorehabilitation technology now occurring, this time driven by the worldwide emergence of wearable sensing, actuation, and computing for consumer health markets.

New chapters selected for the second edition include motor challenge in neurorehabilitation, neural coupling in neurorehabilitation after stroke, clini-cal application of robots for children, overground exoskeletons for locomo-tion recovery, virtual reality and computer gaming for rehabilitation, wearable sensors, and brain-computer interfaces for rehabilitation therapy. Chapters published in the fi rst edition have also been updated and reorganized to refl ect the ongoing revolution. Volker and I hope that this book will inspire the next generation of innovators—clinicians, neuroscientists, and engineers—to move neurorehabilitation technology forward, thus benefi tting the next gen-eration of people with a neurologic impairment.

The editors thank Barbara Lopez-Lucio for her excellent technical support editing this book.

Irvine , USA David Reinkensmeyer Zurich , Switzerland Volker Dietz

Preface to the Second Edition

vii

Contents

Preface to the Second Edition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Introduction: Rationale for Machine Use . . . . . . . . . . . . . . . . . . . . . . xvii

Part I Basic Framework: Motor Recovery, Learning, and Neural Impairment

1 Learning in the Damaged Brain/Spinal Cord: Neuroplasticity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Andreas Luft , Amy J. Bastian , and Volker Dietz

2 Movement Neuroscience Foundations of Neurorehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Robert L. Sainburg and Pratik K. Mutha

3 Designing Robots That Challenge to Optimize Motor Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 David A. Brown , Timothy D. Lee , David J. Reinkensmeyer , and Jaime E. Duarte

4 Multisystem Neurorehabilitation in Rodents with Spinal Cord Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Grégoire Courtine , Rubia van den Brand , Roland R. Roy , and V. Reggie Edgerton

5 Sensory-Motor Interactions and Error Augmentation . . . . . . . 79 James L. Patton and Felix C. Huang

6 Normal and Impaired Cooperative Hand Movements: Role of Neural Coupling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Miriam Schrafl -Altermatt and Volker Dietz

7 Clinical Assessment and Rehabilitation of the Upper Limb Following Cervical Spinal Cord Injury . . . . . . . . . . . . . . . . . . . 107 Michelle Louise Starkey and Armin Curt

Part II Human-Machine Interaction in Rehabilitation Practice

8 Application Issues for Robotics . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Markus Wirz and Rüdiger Rupp

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9 The Human in the Loop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Alexander C. Koenig and Robert Riener

10 Robotic and Wearable Sensor Technologies for Measurements/Clinical Assessments . . . . . . . . . . . . . . . . . . . 183 Olivier Lambercy , Serena Maggioni , Lars Lünenburger , Roger Gassert , and Marc Bolliger

11 Clinical Aspects for the Application of Robotics in Locomotor Neurorehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Volker Dietz

12 Clinical Application of Robotics and Technology in the Restoration of Walking . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Alberto Esquenazi , Irin C. Maier , Tabea Aurich Schuler , Serafi n M. Beer , Ingo Borggraefe , Katrin Campen , Andreas R. Luft , Dimitrios Manoglou , Andreas Meyer-Heim , Martina R. Spiess , and Markus Wirz

13 Standards and Safety Aspects for Medical Devices in the Field of Neurorehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 Burkhard Zimmermann

14 Clinical Application of Rehabilitation Technologies in Children Undergoing Neurorehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . 283 Hubertus J. A. van Hedel and Tabea Aurich (-Schuler)

Part III Robots for Upper Extremity Recovery

15 Restoration of Hand Function in Stroke and Spinal Cord Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Derek G. Kamper

16 Forging Mens et Manus: The MIT Experience in Upper Extremity Robotic Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 Hermano Igo Krebs , Dylan Edwards , and Neville Hogan

17 Three-Dimensional Multi-degree- of-Freedom Arm Therapy Robot (ARMin) . . . . . . . . . . . . . . . . . . . . . . . . . . . 351 Tobias Nef , Verena Klamroth-Marganska , Urs Keller , and Robert Riener

18 Implementation of Impairment- Based Neurorehabilitation Devices and Technologies Following Brain Injury . . . . . . . . . . . 375 Jules P. A. Dewald , Michael D. Ellis , Ana Maria Acosta , Jacob G. McPherson , and Arno H. A. Stienen

Part IV Robotics for Locomotion Recovery

19 Technology of the Robotic Gait Orthosis Lokomat . . . . . . . . . . 395 Robert Riener

Contents

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20 Beyond Human or Robot Administered Treadmill Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409 Hermano Igo Krebs , Konstantinos Michmizos , Tyler Susko , Hyunglae Lee , Anindo Roy , and Neville Hogan

21 Toward Flexible Assistance for Locomotor Training: Design and Clinical Testing of a Cable- Driven Robot for Stroke, Spinal Cord Injury, and Cerebral Palsy . . . . . . . . . . . . . . . . . . . 435 Ming Wu and Jill M. Landry

22 Robot-Aided Gait Training with LOPES . . . . . . . . . . . . . . . . . . 461 Edwin H. F. van Asseldonk and Herman van der Kooij

23 Robotic Devices for Overground Gait and Balance Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 Joseph M. Hidler , Arno H. A. Stienen , and Heike Vallery

24 Using Robotic Exoskeletons for Over-Ground Locomotor Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493 Arun Jayaraman , Sheila Burt , and William Zev Rymer

25 Functional Electrical Stimulation Therapy: Recovery of Function Following Spinal Cord Injury and Stroke . . . . . . . 513 Milos R. Popovic , Kei Masani , and Silvestro Micera

26 Passive Devices for Upper Limb Training . . . . . . . . . . . . . . . . . 533 Arthur Prochazka

27 Upper-Extremity Therapy with Spring Orthoses . . . . . . . . . . . 553 David J. Reinkensmeyer and Daniel K. Zondervan

28 Virtual Reality for Sensorimotor Rehabilitation Post Stroke: Design Principles and Evidence . . . . . . . . . . . . . . . . . . . 573 Sergi Bermúdez i Badia , Gerard G. Fluet , Roberto Llorens , and Judith E. Deutsch

29 Wearable Wireless Sensors for Rehabilitation . . . . . . . . . . . . . . 605 Andrew K. Dorsch , Christine E. King , and Bruce H. Dobkin

30 BCI-Based Neuroprostheses and Physiotherapies for Stroke Motor Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . 617 Colin M. McCrimmon , Po T. Wang , Zoran Nenadic , and An H. Do

Epilogue: What Lies Ahead? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 629

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633

Contents

xi

Ana Maria Acosta , PhD Departments of Physical Therapy and Human Movement Sciences , Northwestern University , Chicago , IL , USA

Tabea Aurich (-Schuler) , MSc Pediatric Rehab Research Group , Rehabilitation Center for Children and Adolescents, University Children’s Hospital Zürich , Zurich , Switzerland

Sergi Bermúdez i Badia , Eng, PhD Madeira Interactive Technologies Institute and Centro de Competências das Ciências Exatas e da Engenharia , Universidade da Madeira , Funchal , Portugal

Amy J. Bastian , MD Department of Neuroscience , The Johns Hopkins School of Medicine and Kennedy Krieger Institute , Baltimore , MD , USA

Serafi n M. Beer Department of Neurology and Neurorehabilitation , Rehabilitation Centre, Klinik Valens , Valens , Switzerland

Marc Bolliger , PhD Spinal Cord Injury Center , University of Zurich, Balgrist and University Clinic Balgrist , Zurich , Switzerland

Ingo Borggraefe Department of Pediatric Neurology and Developmental Medicine , University of Munich , Munich , Germany

David A. Brown , PT, PhD Departments of Physical Therapy and Occupational Therapy , University of Alabama at Birmingham , Birmingham , AL , USA

Sheila Burt , BS Center for Bionic Medicine , Rehabilitation Institute of Chicago , Chicago , IL , USA

Katrin Campen Quality Management arvato CRM Healthcare GmbH , Berlin , Germany

Grégoire Courtine , PhD Department of Neurology , Experimental Neurorehabilitation Laboratory , Zurich , Switzerland

Armin Curt , MD Spinal Cord Injury Research Lab, Spinal Cord Injury Centre , Balgrist University Hospital, University of Zurich , Zurich , Switzerland

Judith E. Deutsch , PT, PhD Rivers Lab: Department of Rehabilitation and Movement Sciences , Rutgers – The State University of New Jersey , Newark , NJ , USA

Contributors

xii

Jules P. A. Dewald , PT, PhD Department Physical Therapy and Human Movement Sciences , Feinberg School of Medicine, Northwestern University , Chicago , IL , USA

Volker Dietz , MD Spinal Cord Injury Center , University Hospital Balgrist , Zurich , Switzerland

An H. Do , MD Department of Neurology , University of California Irvine , Orange , CA , USA

Bruce H. Dobkin , MD Department of Neurology , Geffen School of Medicine, University of California Los Angeles , Los Angeles , CA , USA

Andrew K. Dorsch , MD Department of Neurology , UCLA Geffen School of Medicine , Los Angeles , CA , USA

Jaime E. Duarte , PhD Departments of Mechanical and Aerospace Engineering , University of California, Irvine , Irvine , CA , USA

V. Reggie Edgerton , PhD Departments of Integrative Biology and Physiology and Neurobiology and Brain Research Institute , University of California , Los Angeles , CA , USA

Dylan Edwards , PT, PhD Laboratory for Non-Invasive Brain Stimulation and Human Motor Control, Department of Neurology , Weill Cornell Medical College, Burk-Cornell Medical Research Institute , White Plains , NY , USA

Michael D. Ellis , PT, DPT Departments of Physical Therapy and Human Movement Sciences , Northwestern University , Chicago , IL , USA

Alberto Esquenazi , MD Department of Physical Medicine and Rehabilitation , MossRehab , Elkins Park , PA , USA

Gerard G. Fluet , DPT, PhD Departments of Rehabilitation and Movement Sciences , Rutgers – The State University of New Jersey , Newark , NJ , USA

Roger Gassert , PhD Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology , ETH Zurich , Zurich , Switzerland

Joseph M. Hidler , PhD Aratech, LLC , Ashburn , VA , USA

Neville Hogan , PhD Department of Mechanical Engineering, Brain and Cognitive Sciences , Massachusetts Institute of Technology , Cambridge , MA , USA

Felix C. Huang , PhD Sensory Motor Performance Program , Rehabilitation Institute of Chicago , Chicago , IL , USA

Department of Physical Medicine and Rehabilitation , The Rehabilitation Institute of Chicago and Northwestern University , Chicago , IL , USA

Arun Jayaraman , PT, PhD Max Näder Lab for Rehabilitation Technologies and Outcomes Research, Departments of Physical Medicine and Rehabilitation, Medical Social Sciences, Physical Therapy and Human Movement Sciences , The Rehabilitation Institute of Chicago, Northwestern University , Chicago , IL , USA

Contributors

xiii

Derek Kamper , PhD Department of Biomedical Engineering , Illinois Institute of Technology , Chicago , IL , USA

Urs Keller Sensory-Motor Systems Lab, Department of Health Sciences and Technology , Institute of Robotics and Intelligent Systems , Zurich , Switzerland

Rehabilitation Center , University Children’s Hospital Zurich , Zurich , Switzerland

Christine E. King , PhD Department of Neurology , University of California Los Angeles , Los Angeles , CA , USA

Verena Klamroth-Marganska , MD Sensory-Motor Systems Lab, Department of Health Sciences and Technology , Institute of Robotics and Intelligent Systems, ETH Zurich , Zurich , Switzerland

Spinal Cord Injury Center, Balgrist Campus , Zurich , Switzerland

Alexander C. Koenig , PhD Sensory-Motor Systems Lab, Institute of Robotics and Intelligent Systems, Department of Health Sciences and Technology , ETH Zurich , Zurich , Switzerland

Department of Physical Medicine and Rehabilitation , Spaulding Rehabilitation Hospital, Harvard Medical School , Zurich , Switzerland

Hermano Igo Krebs , PhD Department of Mechanical Engineering , MIT- Massachusetts Institute of Technology , Cambridge , MA , USA

Department of Neurology , University of Maryland, School of Medicine , Baltimore , MD , USA

Institute of Neuroscience , University of Newcastle , Newcastle Upon Tyne , UK

Department of Rehabilitation Medicine I , Fujita Health University, School of Medicine , Toyoake , Japan

Department of Mechanical Science and Bioengineering , Osaka University , Osaka , Japan

Olivier Lambercy , PhD Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology , ETH Zurich , Zurich , Switzerland

Jill M. Landry , PT Sensor Motor Performance Program , Rehabilitation Institute of Chicago , Chicago , IL , USA

Timothy D. Lee , PhD Department of Kinesiology , McMaster University , Hamilton , ON , Canada

Hyunglae Lee , PhD School for Engineering of Matter, Transport, and Energy , Arizona State University , Tempe , AZ , USA

Roberto Lloréns , PhD Instituto de Investigación e Innovación en Bioingeniería , Universitat Politècnica de València , Valencia , Spain

Andreas R. Luft , MD Department of Neurology , University Hospital Zurich , Zurich , Switzerland

Lars Lünenburger , PhD Hocoma AG , Zurich , Switzerland

Serena Maggioni , MSc Biomedical Engineering Hocoma AG , Zurich , Switzerland

Contributors

xiv

Sensory-Motor Systems (SMS) Lab, Department of Health Sciences and Technology , ETH Zürich , Zurich , Switzerland

Spinal Cord Injury Center , University of Zurich, Balgrist University Hospital , Zurich , Switzerland

Irin C. Maier Clinical Research and Clinical Application , Hocoma AG , Volketswil , Switzerland

Dimitrios Manoglou Department of Neurology and Neurorehabilitation , Rehabilitation Centre, Klinik Valens , Valens , Switzerland

Kei Masani , PhD Lyndhurst Centre , Toronto Rehabilitation Institute – University Health Network , Toronto , Ontario , Canada

Colin M. McCrimmon Department of Biomedical Engineering , University of California Irvine , Irvine , CA , USA

Jacob G. McPherson , PhD Department of Biomedical Engineering , Florida International University , Miami , FL , USA

Andreas Meyer-Heim Rehabilitation Center , Children’s University Hospital Zurich , Zurich , Switzerland

Silvestro Micera , PhD Ecole Polytechnmique Federale de Lausanne , Lausanne , Switzerland

Scuola Superiore Sant’Anna , Pisa , Italy

Konstantinos Michmizos , MEng, PhD Department of Computer Science , Rutgers University , Piscataway , NJ , USA

Pratik K. Mutha , PhD Department of Biological Engineering and Centre for Cognitive Science , Indian Institute of Technology Gandhinagar , Ahmedabad , Gujarat , India

Tobias Nef , PhD Gerontechnologoy and Rehabilitation Group, ARTORG Center for Biomedical Engineering Research , University of Bern , Bern , Switzerland

Zoran Nenadic , DSc Department of Biomedical Engineering , University of California Irvine , Irvine , CA , USA

James L. Patton , PhD Sensory Motor Performance Program , Rehabilitation Institute of Chicago , Chicago , IL , USA

Department of Physical Medicine Rehabilitation , Northwestern University , Chicago , IL , USA

Department of Bioengineering , Universities of Illinois at Chicago , Chicago , IL , USA

Milos R. Popovic , PhD, Dipl El Eng Institute of Biomaterials and Biomedical Engineering , University of Toronto and Toronto Rehabilitation Institute – University Health Network , Toronto , ON , Canada

Arthur Prochazka , BEng, MSc, PhD Centre for Neuroscience , University of Alberta , Edmonton , AB , Canada

Department of Physiology , University of Alberta , Edmonton , AB , Canada

Contributors

xv

David J. Reinkensmeyer , PhD Department of Mechanical and Aerospace Engineering , University of California at Irvine , Irvine , CA , USA

Department of Anatomy and Neurobiology , University of California at Irvine , Irvine , CA , USA

Department of Biomedical Engineering , University of California at Irvine , Irvine , CA , USA

Department of Physical Medicine and Rehabilitation , University of California at Irvine , Irvine , CA , USA

Robert Riener , Dr.-Ing Sensory-Motor Systems Lab, Department of Health Sciences and Technology, Institute of Robotics and Intelligent Systems , ETH Zurich , Zurich , Switzerland

Spinal Cord Injury Center , Balgrist Campus , Zurich , Switzerland

Roland R. Roy , BS, MS, PhD Department of Integrative Biology and Physiology and Brain Research Institute , University of California , Los Angeles , CA , USA

Anindo Roy , PhD Department of Neurology , University of Maryland School of Medicine , Baltimore , MD , USA

Rüdiger Rupp , PhD Spinal Cord Injury Center , Heidelberg University Hospital , Heidelberg , Germany

William Zev Rymer , MD, PhD Sensory Motor Performance Program, Department of Research , Rehabilitation Institute of Chicago , Chicago , IL , USA

Robert L. Sainburg , PhD Departments of Kinesiology and Neurology , The Pennsylvania State University and Penn State College of Medicine , University Park , PA , USA

Miriam Schrafl -Altermatt , PhD Spinal Cord Injury Center , Balgrist University Hospital , Zurich , Switzerland

Martina R. Spiess , PhD, PT Clinical Research and Clinical Application , Hocoma AG , Volketswil , Switzerland

Michelle Louise Starkey , MA, MSc, PhD Spinal Cord Injury Research Lab, Spinal Cord Injury Centre , Balgrist University Hospital, University of Zurich , Zurich , Switzerland

Arno H. A. Stienen , BSc, MSc, PhD Department of Biomechanical Engineering , University of Twente , Enschede , The Netherlands

Tyler Susko , PhD Department of Mechanical Engineering , University of California Santa Barbara , Santa Barbara , CA , USA

Heike Vallery , Dr – Ing Faculty of Mechanical, Maritime and Materials Engineering , Delft University of Technology , Delft , The Netherlands

Edwin H. F. van Asseldonk , PhD Department of Biomechanical Engineering , University of Twente , Enschede , The Netherlands

Hubertus J. A. van Hedel , PhD, PT Pediatric Rehab Research Group , Rehabilitation Center for Children and Adolescents, University Children’s Hospital Zürich , Zurich , Switzerland

Contributors

xvi

Rubia van den Brand , MSc Department of Neurology , Experimental Neurorehabilitation Laboratory , Zurich , Switzerland

Herman van der Kooij , ir, PhD Department of Biomechanical Engineering , University of Twente , Enschede , The Netherlands

Po T. Wang , PhD Department of Biomedical Engineering , University of California Irvine , Irvine , CA , USA

Markus Wirz , PT, PhD Health Department, Institute of Physiotherapy , Zurich University of Applied Sciences , Winterthur , Switzerland

Ming Wu , PhD Sensor Motor Performance Program , Rehabilitation Institute of Chicago , Chicago , IL , USA

Burkhard Zimmermann Department of Quality Management , Hocoma AG , Zurich , Switzerland

IISART , Zurich , Switzerland

Daniel K. Zondervan , PhD Flint Rehabilitation Devices, LLC , Irvine , CA , USA

Contributors

xvii

Introduction: Ration ale for Machine Use

Neurorehabilitation technology, which includes robotics, wearable sensors, virtual reality, and functional electrical stimulation, is a rapidly expanding fi eld in research and clinical applications. This second edition book discusses the state of art in this fi eld and also examines evolving developments in related basic research and in therapeutic applications. A key question we seek to answer is “What is the rationale for machine use in neurorehabilitation?”

During the last 25 years, it has become evident that the effi cacy of conven-tional physio- or occupational therapy applied during neurorehabilitation of stroke and spinal-cord-injured (SCI) patients can hardly be demonstrated in the context of evidence-based medicine. Conventional physio- or occupa-tional therapy has usually been conducted on limited populations, with little objective and standardized assessments of its effects on outcomes over the course of rehabilitation and without a sound scientifi c basis. Different thera-peutic “schools” (e.g., Bobath/Vojta) that emerged based on individual thera-pist experiences were not based on a rational approach driven by knowledge of the pathophysiological basis of impairment.

Relatively few, large studies have been performed to evaluate the effects of a given therapy or to compare the effects of different therapeutic interven-tions. Of course, in neurorehabilitation, the optimal approaches, such as the use of full randomized controlled trials, are diffi cult to implement rigorously, because of the confounding effects of spontaneous recovery of function. Furthermore, comparisons with “controls,” i.e., patients without any treat-ment, are not feasible to perform. Thus, the quantitative effects of conven-tional physio- and occupational therapies still remain an open question. Some investigators have even argued that conventional therapy provides no real benefi t for impairment reduction beyond that offered by spontaneous biologi-cal recovery alone, except in teaching patients compensatory strategies through motor learning [1, 2].

Key Developments Leading to the Emergence of Machines for Neurorehabilitation

From the late 1980s to the early 1990s, several key basic and clinical research developments led to profound changes in neurorehabilitation interventions and the emergence of machines for neurorehabilitation.

xviii

First, research performed in animal models showed the ability of rehabili-tation training to alter both neural connectivity and movement function after injury. For example, experiments with cats with a transected spinal cord showed that a locomotor training approach, in which the cat walked on a treadmill with body weight support, was effective in promoting gait restora-tion [3]. This fi nding renewed interest in the notion of locomotion pattern generators in the mammalian spinal cord and indicated that they could poten-tially be harnessed for restoration of locomotion in the injured human as well [4, 5]. Recent studies using epidural spinal cord stimulation in animals and humans show that such stimulation heightens the responsivity of spinal net-works, potentially further enhancing the gains possible with locomotor train-ing [6].

For the upper extremity, seminal experiments conducted with monkeys that had received a focal ischemic infarct showed how rehabilitative training of skilled hand function prevented loss of cortical representation of the hand and was accompanied by functional behavioral gains [7]. Intense, skilled hand training formed a theoretical framework for constraint-induced therapy, which in turn was validated in one of the few large randomized clinical trials of neurorehabilitation that was successful [8]. Thus, one key change that began in the 1980s was that basic science studies began to verify that intense rehabilitation training applied in a physiologically appropriate way produced verifi able and benefi cial changes even in the chronically injured nervous system.

Second, approaches to successfully induce axonal regeneration in animals with severe neural damage began to be introduced. For example, antibodies can be used to block the effects of myelin products on neuronal growth after spinal cord injury [9]. Neural stem cells engrafted into the damaged spinal cord promote new synapse formation and locomotor recovery [10]. Although these interventions hold great promise, in order to translate these approaches into practical therapies for humans, a standardization of assessments and con-ventional therapies is required [11]. These developments have forced reha-bilitation centers in Europe [11] and in the United States to begin to build collaborative research networks, to introduce and establish standardized clin-ical and functional assessments, and to monitor therapeutic effects over the course of rehabilitation.

Third, we know today that elderly patients can also profi t from rehabilita-tion procedures, a fi nding of key importance given the changing demograph-ics of many industrialized nations. For example, it was demonstrated that the neurological defi cit after an SCI recovers to a similar extent as in young sub-jects. However, elderly patients have diffi culties to translate this gain in motor function into activities of daily living [12,13]. Therefore, age-specifi c reha-bilitation approaches are required and should be applied as far as possible in a home environment of the patient.

Thus, in summary, three changes that have occurred are (1) increased sci-entifi c evidence for effectiveness of intensive neurorehabilitation therapy originating from studies in animal models; (2) new promise of neuroregen-erative treatments, necessitating greater standardization and better outcome monitoring in rehabilitation practice; and (3) the opportunity and need to treat

Introduction: Rationale for Machine Use

xix

the increasing number of elderly patients with neurologic injury, in the clinic as well as at home. All three of these changes contributed to the realization that appropriately designed robotic devices and other machines could be use-ful for rehabilitation therapy, both scientifi cally and clinically.

The First Robots for Rehabilitation Training

The use of body-weight-supported, treadmill-based manual locomotor train-ing of stroke/SCI subjects began in the early 1990s, relying on the aforemen-tioned observations in the spinalized cat as motivation [3]. This training, primarily applied in SCI subjects, was associated with considerable addi-tional costs and only short training periods because of the need for multiple physiotherapists to assist the leg movements on both sides during the step cycle [14], as well as the need for additional therapists to substitute for the treating therapists, because the intervention is demanding on both therapist and patients. The cyclic nature of repetitive movements to be assisted over longer time periods led to the idea that a robotic device could take over the physically demanding training [15].

However, successful implementation of the fi rst robotic device for provid-ing locomotor training of SCI/stroke subjects—the Lokomat—still required that several other problems be solved, and in fact the development of the Lokomat has been an ongoing process of refi nement. Safety constraints had to be established, mainly related to the forces that could be applied to the legs and prevention of skin ulcers. In the beginning, position-controlled fi xed physiological stepping movements, which had been prerecorded from healthy subjects, were imposed on the legs of SCI subjects using an exoskeleton robot [15]. However, in subsequent years, it has become evident that merely impos-ing fi xed movements on paretic limbs is not suffi cient to achieve optimal training effects. Leg movements should only be assisted insofar as it is required by the severity of paresis of an individual subject. Therefore, ongo-ing developmental advances have focused on patient-cooperative and assist- as- needed controllers, as well as providing feedback information to both the patient and therapists about the patient’s contribution to the locomotor move-ments [16], increased degrees of freedom for the pelvis, and quantitative assessments that assay the impairments contributing to locomotor dysfunc-tion, as reviewed in chapters in this book and in [17].

For the upper extremity, the fi rst robotic therapy device, MIT-MANUS, which was developed starting in the 1980s, targeted a simple functional arm movement—reaching to targets in the horizontal plane [18]. In this case, the device again provided a tool for therapists and patients to extend the number of practice movements the patient could make and also provided a consistent, standardized form of assistance during practice, which was useful for scien-tifi c studies of rehabilitation therapy. But MIT-MANUS also then has under-gone a continual process of refi nement and testing, including adding degrees of freedom to make the practice movements more functional, involving devices for the hand and wrist, and changing the way assistance is provided so that it progressively challenges the patient, as described in chapters in this

Introduction: Rationale for Machine Use

xx

book. In addition, the most widely used upper extremity robotic technology now appears to be ArmeoSpring, in use in over 700 facilities. ArmeoSpring is based on the T-WREX arm exoskeleton [19] and is technically not even a robot, because it lacks programmable actuators.

The Rationale for Machine Use in Rehabilitation Therapy

In light of the above history, it is now reasonable to ask: What is the rationale for applying a robotic device or other machine for rehabilitation therapy in patients with a neurologic injury such as stroke or SCI? At present, the main potential advantages are:

• Machines allow standardized training sessions that simultaneously pro-vide objective measures and feedback information to the patient/therapist about the physical aspects of the training performed (e.g., applied forces, velocity, duration of training, joint excursions) and about the training effects (i.e., the progress of recovery can be monitored). This is important both for improving decision-making in clinical practice and for improving clinical trial design and execution.

• Machines enable longer training times and, in some cases, more repeti-tions to be achieved per unit of time.

• Machines relieve therapists from physically demanding work, allowing them to optimize other aspects of the individual therapy and care.

What Is Needed for a Successful Training?

Systematic reviews of clinical studies of both lower and upper extremity robotic therapy devices now support their effectiveness as adjuncts to conven-tional therapy, yet the therapeutic benefi ts these devices help deliver are still modest [20, 21]. Robotic devices can assist to exploit neuroplasticity after a damage of the CNS. However, restoration of function is limited depending on the individual condition [22]. There are many essential questions that have to be answered in order to optimize training effects and advance the fi eld of rehabilitation technology. We conclude this Introduction by posing some of these questions (for more questions, see also [23]):

• What are the essential sensory cues [24] and appropriate forms of mechan-ical assistance/control laws [25] to optimize the training by a machine?

• What is the best type of feedback information for the patient during a machine training episode, and how should it best be delivered to reinforce training effects?

• With a machine, longer training sessions become feasible. How long should a training session last per day to achieve optimal effects? How do the indi-vidual’s health condition, needs, and capabilities affect this determination?

• What types of movements and speeds of movements are appropriate to achieve the best effects? How should movement type and speed be varied

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during a training session? How “physiological” must the training condi-tions be? When should compensatory movements be allowed?

• How early after a neurologic injury should a patient start machine training and how strongly should the patient be challenged by the training?

• How can technologies be developed that are appropriate and viable for home use?

• How does optimal technology design vary with patient subgroups, e.g., children or elderly patients?

• To what extent can other emerging interventions, such as virtual reality, brain-computer interfaces, and functional electrical stimulation, enhance the effectiveness of machine-based training?

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