Neurorehabilitation Technology

Introduction to the Third Edition
Contents
Basic Framework: Motor Recovery, Learning, and Neural Impairment
1 Learning in the Damaged Brain/Spinal Cord: Neuroplasticity
Abstract
1.1 Learning in the CNS
1.2 Mechanisms of Neuroplasticity in Learning and After Lesions
1.2.1 Gene Expression
1.2.2 Cellular Plasticity
1.2.3 Systems Plasticity in the Brain
1.2.4 Plasticity in Spinal Cord
1.2.4.1 Spinal Reflex Plasticity
1.2.4.2 Task-Specific Neural Plasticity
1.2.5 Subcortical Contributions to Movement Learning
1.3 Learning and Plasticity During Rehabilitation Therapy
1.3.1 Lesions of Cortex and &!blank;Descending Pathways
1.3.2 Cerebellar Lesions
1.3.3 Spinal Lesions
1.3.3.1 Plasticity of Spinal Neuronal Circuits: Rehabilitation Issues
1.3.3.2 Functional Training in Persons with a Spinal Cord Injury
1.3.3.3 Prerequisites for a Successful Training
1.4 Conclusion
Acknowledgements
References
2 Movement Neuroscience Foundations of Neurorehabilitation
Abstract
2.1 Introduction
2.2 Principle 1: Optimal Control
2.3 Principle 2: Impedance Control
2.4 Principle 3: Motor Lateralization
2.5 Principle 4: Motor Learning
2.6 Summary and Conclusions
References
3 Recovery of Sensorimotor Functions After Stroke and SCI: Neurophysiological Basis of Rehabilitation Technology
Abstract
3.1 Introduction
3.2 Implications for Rehabilitation Technology Design
3.3 Conclusion
Disclosure
References
From Movement Physiology to Technology Application
4 Use of Technology in the Assessment and Rehabilitation of the Upper Limb After Cervical Spinal Cord Injury
Abstract
4.1 Introduction
4.2 Significance of the Upper Limb and Distinctions of the Tetraplegic Upper Extremity
4.2.1 Importance of the Upper Limb
4.2.2 Distinctions of the Tetraplegic Upper Limb
4.3 Assessment Frameworks and Psychometric Properties
4.3.1 Outcome Measure Frameworks
4.3.2 Measurement Properties
4.4 Measures of Body Functions and Structures After Cervical Spinal Cord Injury
4.4.1 Electrophysiology
4.4.1.1 Somatosensory Evoked Potentials (SSEP)
4.4.1.2 Contact Heat Evoked Potential (CHEP)
4.4.1.3 Motor Evoked Potential (MEP)
4.4.1.4 Nerve Conduction Study (NCS)
4.4.1.5 Electromyography (EMG)
4.4.2 Biomechanical (Kinetic, Kinematic) Measures
4.4.2.1 Assessment of Muscle Strength
4.4.2.2 Assessment of Angles, Range of Motion (ROM) and Trajectories
Optical Motion Capture
Body-Worn Sensors
Robotic Systems
4.5 Measures of Activity After Cervical Spinal Cord Injury
4.5.1 Role of Wearable Technology in Measuring Performance
4.6 Measures of Participation After Cervical Spinal Cord Injury
4.7 Therapeutic Approaches for the Rehabilitation of Upper Extremity Function
4.7.1 Robotic Systems for Upper Limb Training
4.7.2 Passive Workstations and Interactive Platforms for Upper Limb Training
4.7.3 Neuromodulation Systems for Upper Limb Training
4.8 Discussion
4.9 Conclusion
References
5 Implementation of Impairment-Based Neurorehabilitation Devices and Technologies Following Brain Injury
Abstract
5.1 Introduction
5.2 Quantification of Impairment
5.2.1 Quantification of Abnormal Synergies and Weakness Using Instrumented Devices
5.2.2 Quantification of Spasticity Using Robotic Technologies
5.2.3 Development of Robotic Devices for Impairment Quantification
5.2.4 Development of SENSING Technologies for Home-Based Quantification of Arm Motor Deficits During Activities of Daily Living
5.3 Impairment-Based Robotic Interventions
5.3.1 Introduction to a Scientifically Underpinned Concept
5.3.2 Targeting the Loss of Independent Joint Control Using Robotic Technologies
5.4 Successful Translation to Clinical Practice
5.4.1 Device Design that Facilitates Successful Translation
5.4.2 Acceptance by the Rehabilitation Specialist
5.4.3 Motivation, Ease of Use, Practical Implications, and Translation into Rehabilitation Clinics
5.5 Conclusion
References
6 The Hand After Stroke and SCI: Restoration of Function with Technology
Abstract
6.1 Hand Neuromechanics
6.2 Pathophysiology
6.2.1 Stroke
6.2.2 Spinal Cord Injury
6.3 Rehabilitation Technology
6.3.1 Non-wearable Devices
6.3.1.1 Independent Robots
6.3.1.2 Hand-End-Effector Coupling
6.3.1.3 Fixed Base
6.3.2 Wearable Hand Robotics
6.3.2.1 Active Extension Assistance
6.3.2.2 Active Flexion Assistance
6.3.2.3 Active Assistance of Both Flexion and Extension
6.3.3 Control
6.4 Current State of Technology and Needs for Future Development
6.5 Conclusions
References
7 Neural Coordination of Cooperative Hand Movements: Implications for Rehabilitation Technology
Abstract
7.1 Introduction
7.2 Coordination of Bilateral Hand Movements by Neural Coupling
7.3 Defective Neural Coupling in Post-Stroke Subjects
7.4 Consequences for Conventional and Robotic Assisted Therapy
References
8 Robotic Gait Training in Specific Neurological Conditions: Rationale and Application
Abstract
8.1 General Introduction
8.2 The Neurophysiology Underlying Locomotion
8.2.1 Introduction
8.2.2 Training the Spinal Circuitry in Animals and Humans
8.2.2.1 Role of Cyclic Body Unloading and Loading
8.2.3 Spastic Muscle Tone
8.3 Clinical Application of Robotics and Technology in the Restoration of Walking
8.3.1 Robotic Devices
8.3.1.1 For Locomotor Training
8.3.1.2 For Daily Life Mobility
8.3.2 Why Robotic Locomotor Training?
8.3.3 Evolution of Motor Abilities During Rehabilitation
8.3.4 Effects of Locomotor Training
8.3.4.1 Specific Effects
8.3.4.2 Unspecific Effects
8.4 Specific Neurological Conditions
8.4.1 Introduction
8.4.2 Stroke
8.4.2.1 Introduction Stroke
8.4.2.2 Gait in Persons with Stroke
8.4.2.3 Evidence for Robotic Gait Training in Persons with Stroke
8.4.2.4 Practical Application of Robotic Gait Training in Persons with Stroke
8.4.3 Traumatic Brain Injury
8.4.3.1 Introduction Traumatic Brain Injury
8.4.3.2 Gait in Persons with Traumatic Brain Injury
8.4.3.3 Evidence for Robotic Gait Training in Persons with Traumatic Brain Injury
8.4.3.4 Practical Application of Robotic Gait Training in Persons with Traumatic Brain Injury
8.4.4 Spinal Cord Injury
8.4.4.1 Introduction Spinal Cord Injury
8.4.4.2 Gait in Persons with Spinal Cord Injury
8.4.4.3 Evidence for Robotic Gait Training in Persons with Spinal Cord Injury
8.4.4.4 Practical Application of Robotic Gait Training in Persons with Spinal Cord Injury
8.4.5 Multiple Sclerosis
8.4.5.1 Introduction Multiple Sclerosis
8.4.5.2 Gait in Persons with Multiple Sclerosis
8.4.5.3 Evidence of Robotic Gait Training in Persons with Multiple Sclerosis
8.4.5.4 Practical Application of Robotic Gait Training in Persons with Multiple Sclerosis
8.4.6 Parkinson’s Disease
8.4.6.1 Introduction Parkinson’s Disease
8.4.6.2 Gait in Persons with Parkinson’s Disease
8.4.6.3 Evidence for Robotic Gait Training in Persons with Parkinson’s Disease
8.4.6.4 Practical Application of Robotic Gait Training in Persons with Parkinson’s Disease
8.5 Conclusion
Acknowledgments
References
Principles for Interactive Rehabilitation Technology
9 Designing User-Centered Technologies for Rehabilitation Challenge that Optimize Walking and Balance Performance
Abstract
9.1 Frameworks of Promotion, Prevention, Motivation, and Attention and Their Relation to High Performance
9.1.1 The Regulatory Focus Theory
9.1.2 Optimizing Performance through Intrinsic Motivation and Attention for Learning Theory
9.2 Technology Considerations When Designing for High Performance
9.3 A User-Centered Approach for Future Technology Development
9.4 Final Thoughts
References
10 Psychophysiological Integration of Humans and Machines for Rehabilitation
Abstract
10.1 Introduction: Multimodal Human–Machine Interaction in Rehabilitation
10.2 Physiological Integration of Humans and Rehabilitation Technologies
10.2.1 Rationale
10.2.2 Model-Based Heart Rate Control
10.2.3 Heart Rate Control Using Treadmill Speed and Visual Stimuli
10.2.4 Further Examples of Physiological Integration
10.2.5 Implementing Physiological Integration into Daily Clinical Routine
10.3 Psychophysiological Integration
10.3.1 Rationale
10.3.2 Psychophysiological Integration in Arm Rehabilitation in the MIMICS Project
10.3.3 Psychophysiological Integration in Leg Rehabilitation in the MIMICS Project
10.3.4 Further Examples of Psychophysiological Integration
10.3.5 Implementing Psychophysiological Integration into Daily Clinical Routine
10.4 Conclusion
Acknowledgements
References
11 Sensory-Motor Interactions and the Manipulation of Movement Error
Abstract
11.1 Introduction
11.2 Neuroplasticity and Recovery
11.3 Multiple Functional Forms of Neuroplasticity
11.4 Augmentation of Feedback to Leverage Neuroplasticity
11.5 Movement Augmentation
11.6 Guidance Versus Error Augmentation
11.7 Error Augmentation for Enhanced Training
11.8 Combined Effects of the Forms of Error Augmentation
11.9 Challenges and Opportunities for Personalized Training
11.9.1 Statistical Approaches to Personalize Error Augmentation
11.9.2 Functional Error Augmentation
11.9.3 Conclusion
Acknowledgements
References
12 The Role of Haptic Interactions with Robots for Promoting Motor Learning
Abstract
12.1 Introduction
12.2 Haptic Training Methods
12.3 Assessing Motor Learning
12.4 Current Evidence of the Effectiveness of Haptic Methods on Motor (Re)Learning
12.5 Implications for Rehabilitation Technology Design
12.5.1 The Personal and Temporal Nature of Motor Learning Highlights the Need for Adaptive Haptic Training Paradigms
12.5.2 Appropriate Delivery of Task-Relevant Information Provided by Haptic Training Methods is Key to Enhance Motor Learning and Transfer
12.5.3 Long-Term Effects and Generalization of Learning of Haptic Training Need More Attention
12.5.4 More Research is Needed to Understand How Haptic Trainings Could Modulate Motor Variability to Stimulate Motor Learning
12.6 Conclusion
Acknowledgements
References
13 Implementation of Robots into Rehabilitation Programs: Meeting the Requirements and Expectations of Professional and End Users
Abstract
13.1 Introduction
13.2 Patients’ Requirements
13.2.1 Neurological Condition
13.2.2 Autonomic Nervous System
13.2.3 Musculoskeletal System and Skin
13.2.4 Cognition
13.3 Therapists’ Requirements
13.3.1 Instruction of Therapists
13.3.2 Implementation of Robots into Clinical Therapy Programs
13.4 Principles of Robotic Training
13.4.1 Training Parameters
13.4.2 Principles of Motor Learning
13.4.3 Feedback and Virtual Reality
13.5 Technical Aspects of Robots for Restorative Therapies
13.5.1 Complexity of Training Devices
13.5.2 End-Effector Devices Versus Exoskeletons
13.5.3 Body Weight Support Devices for Overground Training
13.5.4 Control Algorithms for Active Robotic Training Devices
13.5.5 Combinatory Robotic Training Approaches
13.5.6 User-Centered Design Process and Legal Challenges
13.5.7 Individually Tailored Training
13.5.8 Anthropometrics
13.5.8.1 Setup Time for a Robotic Training
13.5.8.2 Task Specificity
13.6 Human–Machine Interface
13.6.1 Mechanical Interfaces
13.6.2 Control and Feedback Interfaces
13.6.3 Automated Adaptation of Training Parameters
13.6.4 Selection of Feedback Parameters
13.6.5 Robotic Assessment and Therapy Documentation
13.6.6 Continuation of the Robotic Therapy at Home
13.6.7 Safety of Home-Based Robotic Systems
13.6.8 Conventional Gaming Consoles
13.7 Conclusion
References
14 Clinical Application of Rehabilitation Therapy Technologies to Children with CNS Damage
Abstract
14.1 Introduction
14.1.1 The Complementing Role of Rehabilitation Therapy Technologies
14.1.2 Focus of This Chapter and Definitions
14.2 General Considerations for Implementing Rehabilitation Technologies
14.2.1 Technologies
14.2.2 Therapists
14.2.3 Scheduling Robotic Therapies
14.2.4 Environment
14.2.5 Assessments
14.3 Applying Rehabilitation Therapy Technologies to Children
14.3.1 Patient Selection
14.3.1.1 Congenital Versus Acquired Neurological Lesions
14.3.2 Initial Consultation and Test Training
14.3.3 Increasing Therapy Intensity Over Time
14.4 Technology Supported Lower Extremity Rehabilitation in Children
14.4.1 Overview of Pediatric Lower Extremity Systems
14.4.2 Clinical Evidence
14.5 Technology Supported Upper Extremity Rehabilitation in Children
14.5.1 Overview of Pediatric Upper Extremity Systems
14.5.2 Clinical Evidence
14.6 Concerns about Using Rehabilitation Therapy Technologies
14.7 Outlook
14.7.1 Training the Central Core, the Trunk
14.7.2 From Rehabilitation Therapy to Assistive Technology
14.8 Conclusion
Acknowledgements
References
Assessment Technology and Predictive Modeling
15 Robotic Technologies and Digital Health Metrics for Assessing Sensorimotor Disability
Abstract
15.1 Introduction/Motivation
15.2 Clinical Assessments
15.3 Robotic Assessments and Digital Health Metrics
15.3.1 Robotic Assessments Based on Raw Sensor Data
15.3.2 Robotic Assessments Based on Advanced Digital Health Metrics
15.3.3 Non-Robotic Technology-Based Assessments
15.4 Challenges and Future Directions
15.4.1 Usability and Influence of Robotic Assessment Platforms
15.4.2 Selection and Validation of Digital Health Metrics
15.4.3 Interpretation of Digital Health Metrics
15.4.4 Computational Models for Predicting Neurorehabilitation Outcomes
15.4.5 Influencing Therapy Decisions with Digital Health Metrics and Prediction Models
15.5 Conclusions
References
16 Computational Neurorehabilitation
Abstract
16.1 The Computational Neurorehabilitation Framework
16.1.1 The Three Essential Characteristics of Computational Neurorehabilitation Models
16.1.2 Computational Neurorehabilitation Models as Dynamical System Models
16.1.3 Multiple Time Scales in Computational Neurorehabilitation Models
16.2 The Three Categories of Theoretical Learning Rules in Computational Neurorehabilitation Models
16.2.1 Learning without feedback: Unsupervised learning and homeoplastic processes
16.2.2 Learning from Errors: Supervised Learning
16.2.3 Learning from Rewards: Reinforcement Learning
16.3 The Two Types of Computational Neurorehabilitation Models: Qualitative and Quantitative
16.3.1 Qualitative “Biological” Models
16.3.2 Quantitative “Predictive” Models
16.4 Concluding Remarks and Future Directions
Acknowledgements
References
17 Precision Rehabilitation: Can Neurorehabilitation Technology Help Make It a Realistic Target?
Abstract
17.1 Introduction
17.2 Oncology—The Exemplary Case of Precision Medicine
17.3 Initial Attempts at Precision Rehabilitation
17.3.1 Genetic Markers
17.3.2 Stroke Etiology: Ischemia Versus Hemorrhage
17.3.3 Brain Structure and Function
17.3.4 Behavioral Approaches and the First Clinical Precision Rehabilitation Tools
17.4 Discussion
17.4.1 Summary
17.4.2 What Are the Bottlenecks and What Can We Do?
Acknowledgements
References
General Technological Approaches in Neurorehabilitation
18 Spinal Cord Stimulation to Enable Leg Motor Control and Walking in People with Spinal Cord Injury
Abstract
18.1 The Origins of SCS: From Pain to Motor Control
18.1.1 The Rise of SCS for Chronic Pain Management
18.1.2 First Evidence of Improved Motor Function During SCS: From Multiple Sclerosis to SCI
18.1.3 Standardization of SCS Location for Leg Motor Control Following Motor Disorders
18.2 Potential Mechanisms of SCS for Motor Control
18.2.1 General Principles
18.2.2 Electrically Activated Neural Structures
18.2.3 Evidence for Post-synaptic Activation of Neural Circuits
18.2.3.1 Recruitment of the Monosynaptic Reflex
18.2.3.2 Recruitment of Excitatory Spinal Circuits
18.2.3.3 Recruitment of Inhibitory Spinal Circuits
18.2.4 Lessons from Animal Studies
18.2.4.1 Recruitment of Different Reflex Circuits by SCS in Animal Studies
18.2.4.2 Recruitment of Locomotor Circuits by SCS in Animal Studies
18.3 The Evolution of SCS into a Neuroprosthetic Technology and a Neurorehabilitation Therapy
18.3.1 Tonic SCS for the Recovery of Voluntary Motor Control in People with SCI
18.3.1.1 The Initial Discovery that SCS Enables Voluntary Motor Control
18.3.1.2 SCS as a Tool to Trigger Movement Primitives
18.3.1.3 The Combination of SCS with Training and the Re-Discovery that SCS Enables Voluntary Motor Control
18.3.2 Spatiotemporal SCS for Neuroprosthetics and Neurorehabilitation in Animal Models of SCI
18.3.2.1 Spatiotemporal SCS Controlled by Residual Kinematics
18.3.2.2 Spatiotemporal SCS Controlled by Brain Signals
18.3.3 Tonic and Spatiotemporal SCS Combined with Intensive Rehabilitation Restore Independent Overground Walking in People with SCI
18.3.3.1 Tonic SCS
18.3.3.2 Spatiotemporal SCS
18.3.3.3 Limitations of Locomotor Rehabilitation Facilitated by SCS
18.3.4 Other Recent Studies of SCS for Improving Motor and Autonomic Functions After SCI
18.3.5 Comparison Between SCS and Functional Electrical Stimulation (FES)
18.3.5.1 Conceptual Differences: Stimulation of Muscles Versus Spinal Circuits
18.3.5.2 Practical Differences: Assistance Versus Therapy
18.3.6 Conclusion: SCS, a Promising Neuroprosthetic Technology and Neurorehabilitation Therapy After SCI
18.4 Transcutaneous SCS as a Non-Invasive Complement to Epidural SCS
18.4.1 Non-Invasive SCS: Stimulating Posterior Roots via Transcutaneous Electrodes
18.4.2 Transcutaneous SCS for Generating Locomotor-Like Movements
18.4.3 Stimulation Parameters for Transcutaneous SCS
18.4.4 Functional Recovery by Long-Term Transcutaneous SCS and Activity-Based Training
18.4.5 Recent Advances to Improve Muscle Recruitment Selectivity in Transcutaneous SCS
18.4.6 Conclusion: Transcutaneous SCS is Less Specific Than Epidural SCS but Provides an Inclusive Access to Advanced Healthcare
References
19 Functional Electrical Stimulation Therapy: Mechanisms for Recovery of Function Following Spinal Cord Injury and Stroke
Abstract
19.1 Introduction
19.2 Functional Electrical Stimulation (FES)
19.2.1 Definitions
19.2.2 Physiology
19.2.3 Technology
19.3 FES Therapy (FET)
19.3.1 Definition
19.3.2 Neuroplasticity and Carry-Over Effect After FET
19.4 Current Evidence of FET Effectiveness
19.4.1 FET for Restoration of Lower Limb Function Following Stroke
19.4.2 FET for Restoration of Lower Limb Function Following SCI
19.4.3 FET for Restoration of Upper Limb Function Following Stroke
19.4.4 FET for Restoration of Upper Limb Function Following SCI
19.5 Hybrid FET
19.5.1 Hybrid FET with Orthoses or Robotic Devices
19.5.2 Comparison of FET and Robotic Therapies
19.6 Brain-Computer Interface (BCI) Controlled FET
19.6.1 Definition
19.6.2 Technology
19.6.3 BCI-FET for Restoration of Upper and Lower Limb Function Following Stroke and SCI
19.7 Potential Mechanisms of FET and How BCI-FET Enhances Neuroplasticity
19.7.1 How BCI Technology Enhances FET
19.8 Perspectives
Conflict of Interest Disclosure Statement
References
20 Basis and Clinical Evidence of Virtual Reality-Based Rehabilitation of Sensorimotor Impairments After Stroke
Abstract
20.1 Principles of Virtual Reality in Stroke Sensorimotor Neurorehabilitation
20.1.1 Immersion, Presence, and Embodiment in Virtual Reality
20.1.2 Immersion and Cybersickness
20.1.3 Motor Learning Principles
20.1.3.1 Enriched Environments
20.1.3.2 Intrinsic and Extrinsic Feedback
20.1.3.3 Task Specificity
20.1.3.4 Dosing
20.1.3.5 Adaptability
20.1.3.6 Motivation
20.1.4 Motivating Through Gaming Elements in Virtual Environments
20.1.4.1 Goal Setting
20.1.4.2 Feedback and Rewards
20.1.4.3 Challenge
20.1.4.4 Sense of Progress
20.1.4.5 Socialization
20.1.5 Summary
20.1.6 Visual Presentation
20.1.7 Point of View
20.1.8 Auditory Stimuli
20.1.9 Haptic, Tactile Stimuli and Their Interfaces
20.1.10 Brain-Computer Interfaces
20.1.11 Summary
20.2 Neuroscience of Virtual Reality
20.2.1 Brain Plasticity
20.2.2 Visuomotor Representations
20.2.3 Summary
20.3 Evidence Base: Impact of VR
20.3.1 Upper Extremities
20.3.1.1 Custom Systems
20.3.1.2 Non-Custom Systems
20.3.2 Balance and Gait
20.3.2.1 Custom Systems
20.3.2.2 Non-Custom Systems
20.3.3 Activity Promotion
20.3.4 Summary
20.4 Considerations for Future Research
20.5 Conclusions
References
21 Wearable Sensors for Stroke Rehabilitation
Abstract
21.1 Introduction
21.2 Wearable Sensors for Assessments Performed in the Clinic
21.2.1 Why Would One Want to Use Wearable Sensors for Assessments Performed in the Clinic?
21.2.2 Assessing Arm and Hand Movements of Stroke Survivors in the Clinic
21.2.2.1 Estimating Movement Kinematics
21.2.2.2 Estimating Clinical Scores
21.2.2.3 Wearable Sensors to Facilitate Upper Limb Training in the Clinic
21.2.3 Assessing and Treating Balance and Mobility of Stroke Survivors in the Clinic
21.2.3.1 Estimating Clinical Scores
21.2.3.2 Wearable Sensors to Facilitate Gait Training in the Clinic
21.2.4 Could Wearable Sensor-Based Evaluations Be Useful to Clinicians? A Possible Future Scenario
21.3 Wearable Sensors to Measure Movement in the Field
21.3.1 Why Would One Want to Measure Movement in the Field?
21.3.2 Monitoring Upper Limb Movements in the Field
21.3.3 Monitoring Lower Limb Movements in the Field
21.3.4 Critical Information Learned from Wearable Sensing in the Field that Would not Be Known Otherwise
21.4 Wearable Sensors to Motivate Movement and Exercise in the Community
21.4.1 Promoting Upper Limb (UL) Movement
21.4.1.1 Providing Feedback on UL Movement Amount
21.4.1.2 Reminders to Move
21.4.1.3 Providing Feedback on Exercise Activities
21.4.2 Providing Feedback on Lower Limb (LL) Movement Amount
21.4.3 Summary
21.5 Emerging Technologies and Their Potential Applications
21.5.1 E-textiles
21.5.2 E-Skin Sensors
21.5.3 Wearable Cameras
21.5.4 Radio Tags and Radar-Like Technologies to Gather Contextual Information
21.5.5 Modern Video Analysis Techniques
21.5.6 Collecting Non-motor Data
21.5.7 What Emerging Technologies Could Do that “Traditional” Technologies Do not …
21.6 Conclusions
References
22 BCI-Based Neuroprostheses and Physiotherapies for Stroke Motor Rehabilitation
Abstract
22.1 Introduction
22.2 How BCIs Work
22.3 Neuroprosthetic BCI Systems
22.4 BCI Systems for Physiotherapy
22.4.1 Review of Existing BCI Systems for Stroke Rehabilitation and Underlying Mechanisms
22.4.2 BCI-Based Stroke Physiotherapy in Clinical Applications
22.5 Conclusion and Future Directions
References
23 Passive Devices for Upper Limb Training
Abstract
23.1 Introduction
23.2 Mechanisms of Functional Recovery: The Significance of Compensatory Strategies
23.3 The Role of Rehabilitation to Restore Arm and Hand Function
23.4 Robotic Exercise Devices
23.5 Passive Gravity Support Systems
23.6 Tabletop Therapy Devices
23.7 Linear Track System
23.8 Tone Compensating Orthoses
23.9 Serious Games for Home Use
23.10 Therapeutic and Functional Electrical Stimulation
23.11 Telerehabilitation
23.12 Clinical Adoption of Passive Devices
23.13 Perspectives and Conclusions
References
24 Mobile Technology for Cognitive Rehabilitation
Abstract
24.1 Introduction
24.2 Cognitive Rehabilitation
24.3 Mobile Technology for Rehabilitation
24.4 Ethical Considerations
24.5 Mobile Technology for Cognitive Assessment
24.6 Mobile Technology for Cognitive Rehabilitative Treatments
24.7 Future Directions
References
25 Telerehabilitation Technology
Abstract
25.1 Introduction
25.1.1 Benefits
25.1.2 Interaction from a Distance
25.1.3 Synchronous and Asynchronous Therapy
25.1.4 Acceptance of Telerehabilitation
25.1.5 Effectiveness of Telerehabilitation
25.1.6 Stroke
25.2 Upper Extremity
25.2.1 Assessment of Motor Functioning
25.2.1.1 Clinical Assessment
Observation-based Clinical Assessment
Technology-Based Clinical Assessment
25.2.1.2 Tele-Assessment
25.2.2 Teletherapy
25.2.2.1 Feedback Systems
25.2.2.2 VR Systems
25.2.2.3 Robotic Systems
25.3 Lower Extremity
25.3.1 Assessment of Motor Function
25.3.1.1 Clinical Assessment
Observation-Based Clinical Assessment
Technology-Based Clinical Assessment
25.3.1.2 Tele-Assessment
25.3.2 Teletherapy
25.4 Communication
25.4.1 Assessment of Speech and Language Functions
25.4.1.1 Clinical Assessment
Observation-Based Clinical Assessment
Technology-Based Clinical Assessments
Voice Analysis
Speech and Language Analysis
25.4.2 Tele-Assessments
25.4.3 Teletherapy
25.4.3.1 Synchronous Therapy
25.4.3.2 Asynchronous Therapy
25.5 Final Remarks
References
Robotic Technologies for Neurorehabilitation: Upper Extremity
26 Forging Mens et Manus: The MIT Experience in Upper Extremity Robotic Therapy
Abstract
26.1 Introduction
26.1.1 The State of the Art
26.1.2 An Upper Extremity Gym of Robots
26.1.2.1 Modularity
26.1.2.2 Gravity-Compensated Shoulder-And-Elbow Robot
26.1.2.3 Gravity-Compensated Shoulder-Elbow-And-Wrist Exoskeletal Robot
26.1.2.4 Gravity Non-compensated Shoulder-And-Elbow Robot
26.1.2.5 Wrist Robot
26.1.2.6 Hand Robot
26.2 Harnessing Plasticity to Augment Recovery
26.2.1 Clinical Evidence for Inpatient Care
26.2.2 Clinical Evidence for Chronic Care
26.2.3 Impairment-Based or Functionally-Based Robotic Therapy: Transition-to-Task
26.2.4 Clinical Evidence Contrary to Common Clinical Perceptions
26.2.5 Bilateral Versus Unilateral Motor Learning and Rehabilitation Interventions
26.2.6 Augmenting Robotic-Mediated Therapy: Neuro-modulation
26.2.7 Which Processes Underlie Neuro-Recovery?
26.2.8 Robot-Mediated Assay
26.3 Discussion
Acknowledgements and Disclosures
References
27 Three-Dimensional Multi-Degree-of-Freedom Arm Therapy Robot (ARMin)
Abstract
27.1 State of the Art
27.1.1 Rationale for Application of Current Technology
27.1.2 Therapeutic Actions and Mechanism
27.1.2.1 Mechanical Structure: End-Effector-Based Robots and Exoskeleton Robots
27.1.2.2 Number and Type of Actuated Joints
27.1.2.3 Actuation Principle: Nonmotorized Robots and Motorized Robots
27.2 Review of Experience and Evidence for the Application of the Armin Robot System
27.2.1 Technical Evaluation of the ARMin Robot System
27.2.2 Mechanical Setup of the ARMin III Robot
27.2.3 Therapy Modes
27.2.3.1 Passive and Active Mobilization
27.2.3.2 Game Therapy
27.2.3.3 Training of Activities of Daily Living
27.2.4 Measurement Functionality of the ARMin Robot
27.2.5 From ARMin for Adults to ChARMin for Children
27.2.6 Armeo Power®—Commercial Version of the ARMin Robot
27.2.7 Evaluation of the ARMin Technology
27.2.7.1 Technical Tests with Healthy Subjects
27.2.7.2 Technical Tests with Stroke Patients
27.2.7.3 Clinical Pilot Studies with Stroke Patients
27.2.7.4 Clinical Trials with Stroke Patients
27.2.7.5 Clinical Trials with Spinal Cord Injured Patients
27.2.7.6 Perspectives for Future Clinical Testing
27.3 Current Developments and Ongoing Testing
27.3.1 Technical Developments for Improving the Human-Robot Interaction
27.3.2 When Music Meets Robotics—An Innovative Approach to Increase Training Motivation
27.3.3 Multiplayer Games—How to Increase Training Motivation
27.3.4 A Novel Neuro-Animation Experience to Facilitate High-Dosage and High-Intensity Training
27.4 Conclusions
Acknowledgements
References
28 Upper-Extremity Movement Training with Mechanically Assistive Devices
Abstract
28.1 Introduction: A Case Study of the Development of a Mechanically Assistive Device
28.1.1 From Traditional Mechanically Assistive Devices to Robotic Rehabilitation
28.1.2 From Robotics Back to Mechanically Assistive Devices
28.2 Summary of Clinical Evidence for the Effectiveness of Mechanically Assistive Devices
28.2.1 Effect of Movement Training Provided by T-WREX
28.2.2 Further Clinical Validation of the Mechanically Assistive Approach with ArmeoSpring
28.2.3 Other Mechanically Assistive Approaches
28.3 Why is Mechanical Assistance Beneficial for Promoting Motor Recovery?
28.3.1 The Motivational Effect
28.3.2 The Strengthening Effect
28.3.3 The Proprioceptive Effect
28.4 Democratizing Mechanically Assistive Devices
28.4.1 Resonating Arm Exerciser (RAE)
28.4.2 Lever-Assisted Rehabilitation for the Arm (LARA)
28.4.3 Boost
28.5 Conclusion
Disclosure
References
Robotic Technologies for Neurorehabilitation: Gait and Balance
29 Technology of the Robotic Gait Orthosis Lokomat
Abstract
29.1 Introduction
29.2 Orthosis Design
29.2.1 Mechanical Aspects
29.2.2 Drives
29.2.3 Safety
29.4 Control Strategies
29.5 Assessment Tools
29.5.1 Mechanical Stiffness
29.5.2 Voluntary Force
29.5.3 Range of Motion and Lower Limb Proprioception
29.6 Biofeedback
29.7 Clinical Outcomes
29.8 Conclusion
Acknowledgements
References
30 Using Robotic Exoskeletons for Overground Locomotor Training
Abstract
30.1 Introduction and Brief History of Exoskeletons
30.2 Currently Available Devices
30.3 Rigid Lower-Body Exoskeletons
30.6 Considerations for Clinical Use
30.7 Regulatory Status and Future Expectations
30.8 Conclusions
References
31 Beyond Human or Robot Administered Treadmill Training
Abstract
31.1 Introduction
31.2 A Competent Model for Walking
31.2.1 Anklebot
31.2.2 Translating to Practice: Training in Seated Position
31.2.3 MIT-Skywalker
31.2.4 Translating to Practice: MIT-Skywalker
31.2.4.1 Rhythmic Training Mode
31.2.4.2 Speed Enhancing Programs
31.2.4.3 Asymmetric Speed Programs
31.2.4.4 Vision Distortion Programs
31.2.4.5 Discrete Training Mode
31.2.4.6 Balance Training
31.2.5 From Traditional Anklebots to Soft Exosuits for Restoration of Walking for Individuals Post Stroke
31.2.6 Translating to Practice: The Robotic Exosuit Augmented Locomotion (REAL)
31.3 Extending the MIT-Skywalker to Variable-Friction Cadense Shoes: An Accessible New Technology for Disabled Gait
31.4 Conclusion
Acknowledgements and Disclosures
References
32 A Flexible Cable-Driven Robotic System: Design and Its Clinical Application for Improving Walking Function in Adults with Stroke, SCI, and Children with CP
Abstract
32.1 Introduction
32.1.1 Relevant Pathophysiology Background
32.1.1.1 Stroke
32.1.1.2 Spinal Cord Injury
32.1.1.3 Children with Cerebral Palsy (CP)
32.1.2 Rationale for Application of Current Technology (The Role of Neural plasticity)
32.1.2.1 Neuroplasticity of Adults with Stroke and SCI, and Children with CP
32.1.3 Therapeutic Action/Mechanisms and Efficacy
32.1.3.1 Task-Oriented Practice in Individuals Post-Stroke
32.1.3.2 Task-Oriented Practice in Humans With SCI
32.1.3.3 Task-Oriented Practice in Children with CP
32.1.4 Review of Experience and Evidence for the Application of Specific Technology
32.1.5 Robotic Gait Training in Individuals Post-Stroke
32.1.6 Robotic Gait Training in Humans with SCI
32.1.7 Robotic BWSTT in Children with CP
32.1.7.1 Limitations of Current Robotic Systems
32.2 Current Developments and Ongoing Testing
32.2.1 Locomotor Training in Individuals Post-Stroke
32.2.1.1 Introduction
32.2.1.2 Constraint Induced Forced Use of the Paretic Leg During Walking
32.2.2 Locomotor Training in Human with Incomplete SCI
32.2.2.1 Introduction
32.2.2.2 Results
32.2.2.3 Results
32.2.3 Locomotor Training in Children With CP
32.2.3.1 Introduction
32.2.3.2 Results
32.2.3.3 Discussion
32.2.4 Improved Walking Function in Individuals Post-Stroke
32.2.5 Improved Walking Function in Humans with SCI
32.2.6 Improved Walking Function in Children with CP
32.2.7 Other Advantages of the Cable-Driven Robotic System
32.3 Conclusion
Acknowledgements
References
33 Body Weight Support Devices for Overground Gait and Balance Training
33.1 Clinical Rationale for Body Weight Supported Training
33.1.1 Origins and Evolution
33.1.2 Target Groups
33.2 Overground Training Devices
33.2.1 Robotic Devices
33.2.2 Non-Robotic Devices
33.3 Device Characteristics
33.3.1 Transparency
33.3.2 Vertical Support Forces
33.3.3 Longitudinal Forces
33.3.4 Lateral Forces
33.3.5 Harness and Attachment
33.4 Outcomes of Overground Gait Training
33.5 Future Directions
References
34 Epilogue: Robots for Neurorehabilitation—The Debate
Abstract
Disclosure
References
Index