Wearable Robots

Jose L. Pons, is currently a Scientist for the Bioengineering Group of the Spanish Council for Scientific Research. He has previously written journal articles including for Humanoids and personal robots: Design and experiments, for the Journal of Robotic Systems, (Volume 18, Issue 12, Pages 673-690,4/12/2001). Pons has also written Emerging Actuator Technologies: A Micromechatronic Approach (0470091975) a book on the design and control of novel actuators for applications in micro nanosystems.

• Foreword xvPreface xviiList of Contributors xix1 Introduction to wearable robotics 1J. L. Pons, R. Ceres and L. Calderón1.1 Wearable robots and exoskeletons 11.1.1 Dual human–robot interaction in wearable robotics 31.1.2 A historical note 41.1.3 Exoskeletons: an instance of wearable robots 51.2 The role of bioinspiration and biomechatronics in wearable robots 61.2.1 Bioinspiration in the design of biomechatronic wearable robots 81.2.2 Biomechatronic systems in close interaction with biological systems 91.2.3 Biologically inspired design and optimization procedures 91.3 Technologies involved in robotic exoskeletons 91.4 A classification of wearable exoskeletons: application domains 101.5 Scope of the book 12References 152 Basis for bioinspiration and biomimetism in wearable robots 17A. Forner-Cordero, J. L. Pons and M. Wisse2.1 Introduction 172.2 General principles in biological design 182.2.1 Optimization of objective functions: energy consumption 192.2.2 Multifunctionality and adaptability 212.2.3 Evolution 222.3 Development of biologically inspired designs 232.3.1 Biological models 242.3.2 Neuromotor control structures and mechanisms as models 242.3.3 Muscular physiology as a model 272.3.4 Sensorimotor mechanisms as a model 292.3.5 Biomechanics of human limbs as a model 312.3.6 Recursive interaction: engineering models explain biological systems 312.4 Levels of biological inspiration in engineering design 312.4.1 Biomimetism: replication of observable behaviour and structures 322.4.2 Bioimitation: replication of dynamics and control structures 322.5 Case Study: limit-cycle biped walking robots to imitate human gait and to inspire the design of wearable exoskeletons 33M. Wisse2.5.1 Introduction 332.5.2 Why is human walking efficient and stable? 332.5.3 Robot solutions for efficiency and stability 342.5.4 Conclusion 36Acknowledgements 362.6 Case Study: MANUS-HAND, mimicking neuromotor control of grasping 36J. L. Pons, R. Ceres and L. Calderón2.6.1 Introduction 372.6.2 Design of the prosthesis 372.6.3 MANUS-HAND control architecture 392.7 Case Study: internal models, CPGs and reflexes to control bipedal walking robots and exoskeletons: the ESBiRRo project 40A. Forner-Cordero2.7.1 Introduction 402.7.2 Motivation for the design of LC bipeds and current limitations 412.7.3 Biomimetic control for an LC biped walking robot 412.7.4 Conclusions and future developments 43References 433 Kinematics and dynamics of wearable robots 47A. Forner-Cordero, J. L. Pons, E. A. Turowska and A. Schiele3.1 Introduction 473.2 Robot mechanics: motion equations 483.2.1 Kinematic analysis 483.2.2 Dynamic analysis 533.3 Human biomechanics 573.3.1 Medical description of human movements 573.3.2 Arm kinematics 593.3.3 Leg kinematics 613.3.4 Kinematic models of the limbs 643.3.5 Dynamic modelling of the human limbs 683.4 Kinematic redundancy in exoskeleton systems 703.4.1 Introduction to kinematic redundancies 703.4.2 Redundancies in human–exoskeleton systems 713.5 Case Study: a biomimetic, kinematically compliant knee joint modelled by a four-bar linkage 74J. M. Baydal-Bertomeu, D. Garrido and F. Moll3.5.1 Introduction 743.5.2 Kinematics of the knee 753.5.3 Kinematic analysis of a four-bar linkage mechanism 753.5.4 Genetic algorithm methodology 773.5.5 Final design 773.5.6 Mobility analysis of the optimal crossed four-bar linkage 783.6 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-Bertomeu3.6.1 The mechanics of pronation–supination control 793.7 Case Study: study of tremor characteristics based on a biomechanical model of the upper limb 80E. Rocon and J. L. Pons3.7.1 Biomechanical model of the upper arm 813.7.2 Results 83References 834 Human–robot cognitive interaction 87L. Bueno, F. Brunetti, A. Frizera and J. L. Pons4.1 Introduction to human–robot interaction 874.2 cHRI using bioelectrical monitoring of brain activity 894.2.1 Physiology of brain activity 904.2.2 Electroencephalography (EEG) models and parameters 924.2.3 Brain-controlled interfaces: approaches and algorithms 934.3 cHRI through bioelectrical monitoring of muscle activity (EMG) 964.3.1 Physiology of muscle activity 974.3.2 Electromyography models and parameters 984.3.3 Surface EMG signal feature extraction 994.3.4 Classification of EMG activity 1024.3.5 Force and torque estimation 1044.4 cHRI through biomechanical monitoring 1044.4.1 Biomechanical models and parameters 1054.4.2 Biomechanically controlled interfaces: approaches and algorithms 1084.5 Case Study: lower limb exoskeleton control based on learned gait patterns 109J. C. Moreno and J. L. Pons4.5.1 Gait patterns with knee joint impedance modulation 1094.5.2 Architecture 1094.5.3 Fuzzy inference system 1104.5.4 Simulation 1104.6 Case Study: identification and tracking of involuntary human motion based on biomechanical data 111E. Rocon and J. L. Pons4.7 Case Study: cortical control of neuroprosthetic devices 115J. M. Carmena4.8 Case Study: gesture and posture recognition using WSNs 118E. Farella and L. Benini4.8.1 Platform description 1194.8.2 Implementation of concepts and algorithm 1194.8.3 Posture detection results 1214.8.4 Challenges: wireless sensor networks for motion tracking 1214.8.5 Summary and outlook 122References 1225 Human–robot physical interaction 127E. Rocon, A. F. Ruiz, R. Raya, A. Schiele and J. L. Pons5.1 Introduction 1275.1.1 Physiological factors 1285.1.2 Aspects of wearable robot design 1295.2 Kinematic compatibility between human limbs and wearable robots 1305.2.1 Causes of kinematic incompatibility and their negative effects 1305.2.2 Overcoming kinematic incompatibility 1335.3 Application of load to humans 1345.3.1 Human tolerance of pressure 1345.3.2 Transmission of forces through soft tissues 1355.3.3 Support design 1385.4 Control of human–robot interaction 1385.4.1 Human–robot interaction: human behaviour 1395.4.2 Human–robot interaction: robot behaviour 1405.4.3 Human–robot closed loop 1435.4.4 Physically triggered cognitive interactions 1465.4.5 Stability 1475.5 Case Study: quantification of constraint displacements and interaction forces in nonergonomic pHR interfaces 149A. Schiele5.5.1 Theoretical analysis of constraint displacements, d 1505.5.2 Experimental quantification of interaction force, Fd 1515.6 Case Study: analysis of pressure distribution and tolerance areas for wearable robots 154J. M. Belda-Lois, R. Poveda and M. J. Vivas5.6.1 Measurement of pressure tolerance 1555.7 Case Study: upper limb tremor suppression through impedance control 156E. Rocon and J. L. Pons5.8 Case Study: stance stabilization during gait through impedance control 158J. C. Moreno and J. L. Pons5.8.1 Knee–ankle–foot orthosis (exoskeleton) 1595.8.2 Lower leg–exoskeleton system 1595.8.3 Stance phase stabilization: patient test 160References 1616 Wearable robot technologies 165J. C. Moreno, L. Bueno and J. L. Pons6.1 Introduction to wearable robot technologies 1656.2 Sensor technologies 1666.2.1 Position and motion sensing: HR limb kinematic information 1666.2.2 Bioelectrical activity sensors 1716.2.3 HR interface force and pressure: human comfort and limb kinetic information 1756.2.4 Microclimate sensing 1796.3 Actuator technologies 1816.3.1 State of the art 1816.3.2 Control requirements for actuator technologies 1836.3.3 Emerging actuator technologies 1856.4 Portable energy storage technologies 1896.4.1 Future trends 1896.5 Case Study: inertial sensor fusion for limb orientation 190J. C. Moreno, L. Bueno and J. L. Pons6.6 Case Study: microclimate sensing in wearable devices 192J. M. Baydal-Bertomeu, J. M. Belda-Lois, J. M. Prat and R. Barberà6.6.1 Introduction 1926.6.2 Thermal balance of humans 1926.6.3 Climate conditions in clothing and wearable devices 1936.6.4 Measurement of thermal comfort 1946.7 Case Study: biomimetic design of a controllable knee actuator 194J. C. Moreno, L. Bueno and J. L. Pons6.7.1 Quadriceps weakness 1956.7.2 Functional analysis of gait as inspiration 1956.7.3 Actuator prototype 197References 1987 Communication networks for wearable robots 201F. Brunetti and J. L. Pons7.1 Introduction 2017.2 Wearable robotic networks, from wired to wireless 2037.2.1 Requirements 2037.2.2 Network components: configuration of a wearable robotic network 2057.2.3 Topology 2067.2.4 Wearable robatic network goals and profiles 2087.3 Wired wearable robotic networks 2097.3.1 Enabling technologies 2097.3.2 Network establishment, maintenance, QoS and robustness 2137.4 Wireless wearable robotic networks 2147.4.1 Enabling technologies 2147.4.2 Wireless sensor network platforms 2167.5 Case Study: smart textiles to measure comfort and performance 218J. Vanhala7.5.1 Introduction 2187.5.2 Application description 2207.5.3 Platform description 2217.5.4 Implementation of concepts 2227.5.5 Results 2227.5.6 Discussion 2237.6 Case Study: ExoNET 224F. Brunetti and J. L. Pons7.6.1 Application description 2247.6.2 Network structure 2247.6.3 Network components 2247.6.4 Network protocol 2257.7 Case Study: NeuroLab, a multimodal networked exoskeleton for neuromotor and biomechanical research 226A. F. Ruiz and J. L. Pons7.7.1 Application description 2267.7.2 Platform description 2277.7.3 Implementation of concepts and algorithms 2277.8 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 Pobil7.8.1 Introduction 2307.8.2 Communication systems 2307.8.3 IP-based protocols 232Acknowledgements 233References 2338 Wearable upper limb robots 235E. Rocon, A. F. Ruiz and J. L. Pons8.1 Case Study: the wearable orthosis for tremor assessment and suppression (WOTAS) 236E. Rocon and J. L. Pons8.1.1 Introduction 2368.1.2 Wearable orthosis for tremor assessment and suppression (WOTAS) 2368.1.3 Experimental protocol 2398.1.4 Results 2408.1.5 Discussion and conclusions 2418.2 Case Study: the CyberHand 242L. Beccai, S. Micera, C. Cipriani, J. Carpaneto and M. C. Carrozza8.2.1 Introduction 2428.2.2 The multi-DoF bioinspired hand prosthesis 2428.2.3 The neural interface 2458.2.4 Conclusions 2478.3 Case Study: the ergonomic EXARM exoskeleton 248A. Schiele8.3.1 Introduction 2488.3.2 Ergonomic exoskeleton: challenges and innovation 2508.3.3 The EXARM implementation 2518.3.4 Summary and conclusion 2548.4 Case Study: the NEUROBOTICS exoskeleton (NEUROExos) 255S. Roccella, E. Cattin, N. Vitiello, F. Vecchi and M. C. Carrozza8.4.1 Exoskeleton control approach 2578.4.2 Application domains for the NEUROExos exoskeleton 2588.5 Case Study: an upper limb powered exoskeleton 259J. C. Perry and J. Rosen8.5.1 Exoskeleton design 2598.5.2 Conclusions and discussion 2688.6 Case Study: soft exoskeleton for use in physiotherapy and training 269N. G. Tsagarakis, D. G. Caldwell and S. Kousidou8.6.1 Soft arm–exoskeleton design 2708.6.2 System control 2728.6.3 Experimental results 2758.6.4 Conclusions 277References 2789 Wearable lower limb and full-body robots 283J. Moreno, E. Turowska and J. L. Pons9.1 Case Study: GAIT–ESBiRRo: lower limb exoskeletons for functional compensation of pathological gait 283J. C. Moreno and J. L. Pons9.1.1 Introduction 2839.1.2 Pathological gait and biomechanical aspects 2849.1.3 The GAIT concept 2859.1.4 Actuation 2869.1.5 Sensor system 2869.1.6 Control system 2869.1.7 Evaluation 2879.1.8 Next generation of lower limb exoskeletons: the ESBiRRo project 2899.2 Case Study: an ankle–foot orthosis powered by artificial pneumatic muscles 289D. P. Ferris9.2.1 Introduction 2899.2.2 Orthosis construction 2909.2.3 Artificial pneumatic muscles 2919.2.4 Muscle mounting 2919.2.5 Orthosis mass 2929.2.6 Orthosis control 2929.2.7 Performance data 2929.2.8 Major conclusions 2959.3 Case Study: intelligent and powered leg prosthesis 295K. De Roy9.3.1 Introduction 2969.3.2 Functional analysis of the prosthetic leg 2979.3.3 Conclusions 3039.4 Case Study: the control method of the HAL (hybrid assistive limb) for a swinging motion 304J. Moreno, E. Turouska and J. L. Pons9.4.1 System 3059.4.2 Actuator control 3059.4.3 Performance 3069.5 Case Study: Kanagawa Institute of Technology power-assist suit 308K. Yamamoto9.5.1 The basic design concepts 3089.5.2 Power-assist suit 3089.5.3 Controller 3109.5.4 Physical dynamics model 3109.5.5 Muscle hardness sensor 3109.5.6 Direct drive pneumatic actuators 3119.5.7 Units 3119.5.8 Operating characteristics of units 3129.6 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. Arantes9.6.1 EEG acquisition and processing 3159.6.2 The PDA-based graphic interface 3179.6.3 Experiments 3179.6.4 Results and concluding remarks 318Acknowledgements 319References 31910 Summary, conclusions and outlook 323J. L. Pons, R. Ceres and L. Calderón10.1 Summary 32310.1.1 Bioinspiration in designing wearable robots 32410.1.2 Mechanics of wearable robots 32610.1.3 Cognitive and physical human–robot interaction 32710.1.4 Technologies for wearable robots 32810.1.5 Outstanding research projects on wearable robots 32910.2 Conclusions and outlook 330References 332Index 335