Wearable Robots. Biomechatronic Exoskeletons

  • ID: 2170897
  • Book
  • 358 Pages
  • John Wiley and Sons Ltd
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A wearable robot is a mechatronic system that is designed around the shape and function of the human body, with segments and joints corresponding to those of the person it is externally coupled with. Teleoperation and power amplification were the first applications, but after recent technological advances the range of application fields has widened. Increasing recognition from the scientific community means that this technology is now employed in telemanipulation, man–amplification, neuromotor control research and rehabilitation, and to assist with impaired human motor control.

Logical in structure and original in its global orientation, this volume gives a full overview of wearable robotics, providing the reader with a complete understanding of the key applications and technologies suitable for its development. The main topics are demonstrated through two detailed case studies; one on a lower limb active orthosis for a human leg, and one on a wearable robot that suppresses upper limb tremor. These examples highlight the difficulties and potentialities in this area of technology, illustrating how design decisions should be made based on these.

As well as discussing the cognitive interaction between human and robot, this comprehensive text also covers: 

- the mechanics of the wearable robot and it s biomechanical interaction with the user, including state–of–the–art technologies that enable sensory and motor interaction between human (biological) and wearable artificial (mechatronic) systems;
- the basis for bioinspiration and biomimetism, general rules for the development of biologically–inspired designs, and how these could serve recursively as biological models to explain biological systems;
- the study on the development of networks for wearable robotics.

Wearable Robotics: Biomechatronic Exoskeletons will appeal to lecturers, senior undergraduate students, postgraduates and other researchers of medical, electrical and bio engineering who are interested in the area of assistive robotics. Active system developers in this sector of the engineering industry will also find it an informative and welcome resource.
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Foreword xv

Preface xvii

List of Contributors xix

1 Introduction to wearable robotics 1J. L. Pons, R. Ceres and L. Calderón

1.1 Wearable robots and exoskeletons 1

1.1.1 Dual human robot interaction in wearable robotics 3

1.1.2 A historical note 4

1.1.3 Exoskeletons: an instance of wearable robots 5

1.2 The role of bioinspiration and biomechatronics in wearable robots 6

1.2.1 Bioinspiration in the design of biomechatronic wearable robots 8

1.2.2 Biomechatronic systems in close interaction with biological systems 9

1.2.3 Biologically inspired design and optimization procedures 9

1.3 Technologies involved in robotic exoskeletons 9

1.4 A classification of wearable exoskeletons: application domains 10

1.5 Scope of the book 12

References 15

2 Basis for bioinspiration and biomimetism in wearable robots 17A. Forner–Cordero, J. L. Pons and M. Wisse

2.1 Introduction 17

2.2 General principles in biological design 18

2.2.1 Optimization of objective functions: energy consumption 19

2.2.2 Multifunctionality and adaptability 21

2.2.3 Evolution 22

2.3 Development of biologically inspired designs 23

2.3.1 Biological models 24

2.3.2 Neuromotor control structures and mechanisms as models 24

2.3.3 Muscular physiology as a model 27

2.3.4 Sensorimotor mechanisms as a model 29

2.3.5 Biomechanics of human limbs as a model 31

2.3.6 Recursive interaction: engineering models explain biological systems 31

2.4 Levels of biological inspiration in engineering design 31

2.4.1 Biomimetism: replication of observable behaviour and structures 32

2.4.2 Bioimitation: replication of dynamics and control structures 32

2.5 Case Study: limit–cycle biped walking robots to imitate human gait and to inspire the design of wearable exoskeletons 33M. Wisse

2.5.1 Introduction 33

2.5.2 Why is human walking efficient and stable? 33

2.5.3 Robot solutions for efficiency and stability 34

2.5.4 Conclusion 36

Acknowledgements 36

2.6 Case Study: MANUS–HAND, mimicking neuromotor control of grasping 36J. L. Pons, R. Ceres and L. Calderón

2.6.1 Introduction 37

2.6.2 Design of the prosthesis 37

2.6.3 MANUS–HAND control architecture 39

2.7 Case Study: internal models, CPGs and reflexes to control bipedal walking robots and exoskeletons: the ESBiRRo project 40A. Forner–Cordero

2.7.1 Introduction 40

2.7.2 Motivation for the design of LC bipeds and current limitations 41

2.7.3 Biomimetic control for an LC biped walking robot 41

2.7.4 Conclusions and future developments 43

References 43

3 Kinematics and dynamics of wearable robots 47A. Forner–Cordero, J. L. Pons, E. A. Turowska and A. Schiele

3.1 Introduction 47

3.2 Robot mechanics: motion equations 48

3.2.1 Kinematic analysis 48

3.2.2 Dynamic analysis 53

3.3 Human biomechanics 57

3.3.1 Medical description of human movements 57

3.3.2 Arm kinematics 59

3.3.3 Leg kinematics 61

3.3.4 Kinematic models of the limbs 64

3.3.5 Dynamic modelling of the human limbs 68

3.4 Kinematic redundancy in exoskeleton systems 70

3.4.1 Introduction to kinematic redundancies 70

3.4.2 Redundancies in human exoskeleton systems 71

3.5 Case Study: a biomimetic, kinematically compliant knee joint modelled by a four–bar linkage 74J. M. Baydal–Bertomeu, D. Garrido and F. Moll

3.5.1 Introduction 74

3.5.2 Kinematics of the knee 75

3.5.3 Kinematic analysis of a four–bar linkage mechanism 75

3.5.4 Genetic algorithm methodology 77

3.5.5 Final design 77

3.5.6 Mobility analysis of the optimal crossed four–bar linkage 78

3.6 Case Study: design of a forearm pronation supination joint in an upper limb exoskeleton 79J. M. Belda–Lois, R. Poveda, R. Barberà and J. M. Baydal–Bertomeu

3.6.1 The mechanics of pronation supination control 79

3.7 Case Study: study of tremor characteristics based on a biomechanical model of the upper limb 80E. Rocon and J. L. Pons

3.7.1 Biomechanical model of the upper arm 81

3.7.2 Results 83

References 83

4 Human robot cognitive interaction 87L. Bueno, F. Brunetti, A. Frizera and J. L. Pons

4.1 Introduction to human robot interaction 87

4.2 cHRI using bioelectrical monitoring of brain activity 89

4.2.1 Physiology of brain activity 90

4.2.2 Electroencephalography (EEG) models and parameters 92

4.2.3 Brain–controlled interfaces: approaches and algorithms 93

4.3 cHRI through bioelectrical monitoring of muscle activity (EMG) 96

4.3.1 Physiology of muscle activity 97

4.3.2 Electromyography models and parameters 98

4.3.3 Surface EMG signal feature extraction 99

4.3.4 Classification of EMG activity 102

4.3.5 Force and torque estimation 104

4.4 cHRI through biomechanical monitoring 104

4.4.1 Biomechanical models and parameters 105

4.4.2 Biomechanically controlled interfaces: approaches and algorithms 108

4.5 Case Study: lower limb exoskeleton control based on learned gait patterns 109J. C. Moreno and J. L. Pons

4.5.1 Gait patterns with knee joint impedance modulation 109

4.5.2 Architecture 109

4.5.3 Fuzzy inference system 110

4.5.4 Simulation 110

4.6 Case Study: identification and tracking of involuntary human motion based on biomechanical data 111E. Rocon and J. L. Pons

4.7 Case Study: cortical control of neuroprosthetic devices 115J. M. Carmena

4.8 Case Study: gesture and posture recognition using WSNs 118E. Farella and L. Benini

4.8.1 Platform description 119

4.8.2 Implementation of concepts and algorithm 119

4.8.3 Posture detection results 121

4.8.4 Challenges: wireless sensor networks for motion tracking 121

4.8.5 Summary and outlook 122

References 122

5 Human robot physical interaction 127E. Rocon, A. F. Ruiz, R. Raya, A. Schiele and J. L. Pons

5.1 Introduction 127

5.1.1 Physiological factors 128

5.1.2 Aspects of wearable robot design 129

5.2 Kinematic compatibility between human limbs and wearable robots 130

5.2.1 Causes of kinematic incompatibility and their negative effects 130

5.2.2 Overcoming kinematic incompatibility 133

5.3 Application of load to humans 134

5.3.1 Human tolerance of pressure 134

5.3.2 Transmission of forces through soft tissues 135

5.3.3 Support design 138

5.4 Control of human robot interaction 138

5.4.1 Human robot interaction: human behaviour 139

5.4.2 Human robot interaction: robot behaviour 140

5.4.3 Human robot closed loop 143

5.4.4 Physically triggered cognitive interactions 146

5.4.5 Stability 147

5.5 Case Study: quantification of constraint displacements and interaction forces in nonergonomic pHR interfaces 149A. Schiele

5.5.1 Theoretical analysis of constraint displacements, d 150

5.5.2 Experimental quantification of interaction force, Fd 151

5.6 Case Study: analysis of pressure distribution and tolerance areas for wearable robots 154J. M. Belda–Lois, R. Poveda and M. J. Vivas

5.6.1 Measurement of pressure tolerance 155

5.7 Case Study: upper limb tremor suppression through impedance control 156E. Rocon and J. L. Pons

5.8 Case Study: stance stabilization during gait through impedance control 158J. C. Moreno and J. L. Pons

5.8.1 Knee ankle foot orthosis (exoskeleton) 159

5.8.2 Lower leg exoskeleton system 159

5.8.3 Stance phase stabilization: patient test 160

References 161

6 Wearable robot technologies 165J. C. Moreno, L. Bueno and J. L. Pons

6.1 Introduction to wearable robot technologies 165

6.2 Sensor technologies 166

6.2.1 Position and motion sensing: HR limb kinematic information 166

6.2.2 Bioelectrical activity sensors 171

6.2.3 HR interface force and pressure: human comfort and limb kinetic information 175

6.2.4 Microclimate sensing 179

6.3 Actuator technologies 181

6.3.1 State of the art 181

6.3.2 Control requirements for actuator technologies 183

6.3.3 Emerging actuator technologies 185

6.4 Portable energy storage technologies 189

6.4.1 Future trends 189

6.5 Case Study: inertial sensor fusion for limb orientation 190J. C. Moreno, L. Bueno and J. L. Pons

6.6 Case Study: microclimate sensing in wearable devices 192J. M. Baydal–Bertomeu, J. M. Belda–Lois, J. M. Prat and R. Barberà

6.6.1 Introduction 192

6.6.2 Thermal balance of humans 192

6.6.3 Climate conditions in clothing and wearable devices 193

6.6.4 Measurement of thermal comfort 194

6.7 Case Study: biomimetic design of a controllable knee actuator 194J. C. Moreno, L. Bueno and J. L. Pons

6.7.1 Quadriceps weakness 195

6.7.2 Functional analysis of gait as inspiration 195

6.7.3 Actuator prototype 197

References 198

7 Communication networks for wearable robots 201F. Brunetti and J. L. Pons

7.1 Introduction 201

7.2 Wearable robotic networks, from wired to wireless 203

7.2.1 Requirements 203

7.2.2 Network components: configuration of a wearable robotic network 205

7.2.3 Topology 206

7.2.4 Wearable robatic network goals and profiles 208

7.3 Wired wearable robotic networks 209

7.3.1 Enabling technologies 209

7.3.2 Network establishment, maintenance, QoS and robustness 213

7.4 Wireless wearable robotic networks 214

7.4.1 Enabling technologies 214

7.4.2 Wireless sensor network platforms 216

7.5 Case Study: smart textiles to measure comfort and performance 218J. Vanhala

7.5.1 Introduction 218

7.5.2 Application description 220

7.5.3 Platform description 221

7.5.4 Implementation of concepts 222

7.5.5 Results 222

7.5.6 Discussion 223

7.6 Case Study: ExoNET 224F. Brunetti and J. L. Pons

7.6.1 Application description 224

7.6.2 Network structure 224

7.6.3 Network components 224

7.6.4 Network protocol 225

7.7 Case Study: NeuroLab, a multimodal networked exoskeleton for neuromotor and biomechanical research 226A. F. Ruiz and J. L. Pons

7.7.1 Application description 226

7.7.2 Platform description 227

7.7.3 Implementation of concepts and algorithms 227

7.8 Case Study: communication technologies for the integration of robotic systems and sensor networks at home: helping elderly people 229J. V. Martí, R. Marín, J. Fernández, M. Nuñez, O. Rajadell, L. Nomdedeu, J. Sales, P. Agustí, A. Fabregat and A. P. del Pobil

7.8.1 Introduction 230

7.8.2 Communication systems 230

7.8.3 IP–based protocols 232

Acknowledgements 233

References 233

8 Wearable upper limb robots 235E. Rocon, A. F. Ruiz and J. L. Pons

8.1 Case Study: the wearable orthosis for tremor assessment and suppression (WOTAS) 236E. Rocon and J. L. Pons

8.1.1 Introduction 236

8.1.2 Wearable orthosis for tremor assessment and suppression (WOTAS) 236

8.1.3 Experimental protocol 239

8.1.4 Results 240

8.1.5 Discussion and conclusions 241

8.2 Case Study: the CyberHand 242L. Beccai, S. Micera, C. Cipriani, J. Carpaneto and M. C. Carrozza

8.2.1 Introduction 242

8.2.2 The multi–DoF bioinspired hand prosthesis 242

8.2.3 The neural interface 245

8.2.4 Conclusions 247

8.3 Case Study: the ergonomic EXARM exoskeleton 248A. Schiele

8.3.1 Introduction 248

8.3.2 Ergonomic exoskeleton: challenges and innovation 250

8.3.3 The EXARM implementation 251

8.3.4 Summary and conclusion 254

8.4 Case Study: the NEUROBOTICS exoskeleton (NEUROExos) 255S. Roccella, E. Cattin, N. Vitiello, F. Vecchi and M. C. Carrozza

8.4.1 Exoskeleton control approach 257

8.4.2 Application domains for the NEUROExos exoskeleton 258

8.5 Case Study: an upper limb powered exoskeleton 259J. C. Perry and J. Rosen

8.5.1 Exoskeleton design 259

8.5.2 Conclusions and discussion 268

8.6 Case Study: soft exoskeleton for use in physiotherapy and training 269N. G. Tsagarakis, D. G. Caldwell and S. Kousidou

8.6.1 Soft arm exoskeleton design 270

8.6.2 System control 272

8.6.3 Experimental results 275

8.6.4 Conclusions 277

References 278

9 Wearable lower limb and full–body robots 283J. Moreno, E. Turowska and J. L. Pons

9.1 Case Study: GAIT ESBiRRo: lower limb exoskeletons for functional compensation of pathological gait 283J. C. Moreno and J. L. Pons

9.1.1 Introduction 283

9.1.2 Pathological gait and biomechanical aspects 284

9.1.3 The GAIT concept 285

9.1.4 Actuation 286

9.1.5 Sensor system 286

9.1.6 Control system 286

9.1.7 Evaluation 287

9.1.8 Next generation of lower limb exoskeletons: the ESBiRRo project 289

9.2 Case Study: an ankle foot orthosis powered by artificial pneumatic muscles 289D. P. Ferris

9.2.1 Introduction 289

9.2.2 Orthosis construction 290

9.2.3 Artificial pneumatic muscles 291

9.2.4 Muscle mounting 291

9.2.5 Orthosis mass 292

9.2.6 Orthosis control 292

9.2.7 Performance data 292

9.2.8 Major conclusions 295

9.3 Case Study: intelligent and powered leg prosthesis 295K. De Roy

9.3.1 Introduction 296

9.3.2 Functional analysis of the prosthetic leg 297

9.3.3 Conclusions 303

9.4 Case Study: the control method of the HAL (hybrid assistive limb) for a swinging motion 304J. Moreno, E. Turouska and J. L. Pons

9.4.1 System 305

9.4.2 Actuator control 305

9.4.3 Performance 306

9.5 Case Study: Kanagawa Institute of Technology power–assist suit 308K. Yamamoto

9.5.1 The basic design concepts 308

9.5.2 Power–assist suit 308

9.5.3 Controller 310

9.5.4 Physical dynamics model 310

9.5.5 Muscle hardness sensor 310

9.5.6 Direct drive pneumatic actuators 311

9.5.7 Units 311

9.5.8 Operating characteristics of units 312

9.6 Case Study: EEG–based cHRI of a robotic wheelchair 314T. F. Bastos–Filho, M. Sarcinelli–Filho, A. Ferreira, W. C. Celeste, R. L. Silva, V. R. Martins, D. C. Cavalieri, P. N. S. Filgueira and I. B. Arantes

9.6.1 EEG acquisition and processing 315

9.6.2 The PDA–based graphic interface 317

9.6.3 Experiments 317

9.6.4 Results and concluding remarks 318

Acknowledgements 319

References 319

10 Summary, conclusions and outlook 323J. L. Pons, R. Ceres and L. Calderón

10.1 Summary 323

10.1.1 Bioinspiration in designing wearable robots 324

10.1.2 Mechanics of wearable robots 326

10.1.3 Cognitive and physical human robot interaction 327

10.1.4 Technologies for wearable robots 328

10.1.5 Outstanding research projects on wearable robots 329

10.2 Conclusions and outlook 330

References 332

Index 335

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