Neuro-Rehabilitation with Brain Interface
In recent years, major results were reported on Brain-Computer Interface / Brain-Machine Interface (BCI/BMI) applied to rehabilitation in scientific reports and papers. This subject received much attention within the Society on Communication, Navigation, Sensing and Services (CONASENSE) during the p...
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| Main Author | |
|---|---|
| Format | eBook |
| Language | English |
| Published |
Aalborg
River Publishers
2015
|
| Edition | 1 |
| Series | River Publishers Series in Communications |
| Subjects | |
| Online Access | Get full text |
| ISBN | 9788793237438 879323743X |
Cover
Table of Contents:
- Forword ix List of Abbreviations xiii List of Figures xv List of Tables xix 1 Overview on BCI/BMI Applied to Rehabilitation 1 Silvano Pupolin and Leo P. Ligthart 1.1 Introduction 1 References 6 2 ICT for Neurorehabilitation 9 Junichi Ushiba and Shoko Kasuga 2.1 Introduction 9 2.2 Plasticity and Rehabilitation of the Brain 10 2.3 Attempts at Neural Rehabilitation with BMI 12 2.4 Conclusions 15 References 16 3 ICT for New-Generation Prostheses 21 Roberto Bortoletto and Luca Tonin, Enrico Pagello, Emanuele Menegatti 3.1 Introduction 21 3.2 Neuromusculoskeletal Modelling: Its Role in the Design of New-Generation Prostheses 23 3.2.1 Musculotendon Models and Parameters 23 3.2.2 Musculoskeletal Kinematics 25 3.2.3 Neuromuscular Control of Musculoskeletal Systems 26 3.2.4 Patient-Specific Neuromusculoskeletal Modelling 27 3.3 Catching the Intention to Move: Brain.Machine Interfaces 28 3.4 Kinematic Reconstruction and Goal-Directed BMI Approaches 31 3.5 The Hybrid Architecture and the Role of Shared-Control in BMI-Driven Devices 33 3.6 Future Challenges for New-Generation Prostheses 36 References 38 4 Gaze Tracking, Facial Orientation Determination, Face and Emotion Recognition in 3D Space for Neurorehabilitation Applications 51 Krasimir Tonchev, Stanislav Panev, Agata Manolova, Nikolay Neshov, Ognian Boumbarov and Vladimir Poulkov 4.1 Introduction 51 4.2 Gaze Tracking and Face Orientation Determination with an Active Multicamera System with Kinect Sensor 55 4.2.1 System Overview 56 4.2.2 System Geometrical Model and Calibration 57 4.2.2.1 Modelling the pan.tilt unit 59 4.2.2.2 Estimating the transformation {G} {K} 61 4.2.3 Facial Extraction and Tracking 63 4.2.4 Gaze Direction Estimation 64 4.2.5 Experimental Results 66 4.3 3D Face and Emotion Recognition with Multiple Kernel Learning 66 4.3.1 Preprocessing and Feature Extraction 67 4.3.1.1 Point cloud filtering 67 4.3.1.2 Surface normal feature extraction 69 4.3.1.3 Locally adaptive regression kernels(LARK) feature extraction 70 4.3.1.4 Shape operator 72 4.3.2 Multiple Kernel Learning for 3D Face and Emotion Recognition 74 4.3.3 3D Face Recognition 75 4.3.4 3D Facial Expression Recognition 77 4.4 Conclusion and Comments 78 References 79 5 An Integrated Perspective for FutureWidespread Integration of Neuro-motor Rehabilitation 89 Giulia Cisotto and Silvano Pupolin 5.1 Introduction 89 5.2 Overview of Motor Diseases and Their Rehabilitation 93 5.3 Two Main Approaches to Rehabilitation 96 5.4 Rehabilitative Basic Principles 102 5.5 Optimization of Current Rehabilitative Methods 106 5.5.1 Virtual Reality 107 5.5.2 EMG Feedback 108 5.6 Future Perspective 110 5.7 Conclusions 112 References 113 6 Ethical Issues in the Use of Information and Communication Technologies in the Health Care of Patients with Neurological Disorders 121 Matteo De Marco and Annalena Venneri 6.1 Introduction 121 6.2 ICT for Health Care 122 6.3 Ethical Issues Associated with ICT for Health Care 123 6.3.1 State of the Art on ICT for Health Care 125 6.4 Ethical Aspects in Relation to ICT Robotics 127 6.5 Ethical Aspects of Telemedicine 128 6.6 ICT for Improving Patients’ Cognitive Functions 129 6.7 Ethical Aspects on ICT for Rehabilitation 130 6.8 Conclusions 132 References 133 Index 143 Editor’s Biographies 145
- Cover -- Title Page -- RIVER PUBLISHERS SERIES IN COMMUNICATIONS -- Title - Brain-Computer Interface/Brain-Machine Interface (BCI/BMI)Applied to Neuro-Rehabilitation -- Copyright -- Contents -- Foreword -- List of Abbreviations -- List of Figures -- List of Tables -- 1. Overview on BCI/BMI Applied -- 1.1 Introduction -- References -- Biographies -- 2. ICT for Neurorehabilitation -- 2.1 Introduction -- 2.2 Plasticity and Rehabilitation of the Brain -- 2.3 Attempts at Neural Rehabilitation with BMI -- 2.4 Conclusions -- References -- Biographies -- 3. ICT for New-Generation Prostheses -- 3.1 Introduction -- 3.2 Neuromusculoskeletal Modelling: Its Role in the Design of New-Generation Prostheses -- 3.2.1 Musculotendon Models and Parameters -- 3.2.2 Musculoskeletal Kinematics -- 3.2.3 Neuromuscular Control of Musculoskeletal Systems -- 3.2.4 Patient-Specific Neuromusculoskeletal Modelling -- 3.3 Catching the Intention to Move: Brain-Machine Interfaces -- 3.4 Kinematic Reconstruction and Goal-Directed BMI Approaches -- 3.5 The Hybrid Architecture and the Role of Shared-Control in BMI-Driven Devices -- 3.6 Future Challenges for New-Generation Prostheses -- References -- Biographies -- 4. Gaze Tracking, Facial Orientation Determination, Face and Emotion Recognition in 3D Space for Neurorehabilitation Applications -- Abstract -- 4.1 Introduction -- 4.2 Gaze Tracking and Face Orientation Determination with an Active Multicamera System with Kinect Sensor -- 4.2.1 System Overview -- 4.2.2 System Geometrical Model and Calibration -- 4.2.2.1 Modelling the pan-tilt unit -- 4.2.2.2 Estimating the transformation {G} ↔ {K} -- 4.2.3 Facial Extraction and Tracking -- 4.2.4 Gaze Direction Estimation -- 4.2.5 Experimental Results -- 4.3 3D Face and Emotion Recognition with Multiple Kernel Learning -- 4.3.1 Preprocessing and Feature Extraction
- 4.3.1.1 Point cloud filtering -- 4.3.1.2 Surface normal feature extraction -- 4.3.1.3 Locally adaptive regression kernels (LARK) feature extraction -- 4.3.1.4 Shape operator -- 4.3.2 Multiple Kernel Learning for 3D Face and Emotion Recognition -- 4.3.3 3D Face Recognition -- 4.3.4 3D Facial Expression Recognition -- 4.4 Conclusion and Comments -- Acknowledgment -- References -- Biographies -- 5. An Integrated Perspective for Future Widespread Integration of Neuro-motor Rehabilitation -- 5.1 Introduction -- 5.2 Overview of Motor Diseases and Their Rehabilitation -- 5.3 Two Main Approaches to Rehabilitation -- 5.4 Rehabilitative Basic Principles -- 5.5 Optimization of Current Rehabilitative Methods -- 5.5.1 Virtual Reality -- 5.5.2 EMG Feedback -- 5.6 Future Perspective -- 5.7 Conclusions -- References -- Biographies -- 6. Ethical Issues in the Use of Information and Communication Technologies in the Health Care of Patients with Neurological Disorders -- 6.1 Introduction -- 6.2 ICT for Health Care -- 6.3 Ethical Issues Associated with ICT for Health Care -- 6.3.1 State of the Art on ICT for Health Care -- 6.4 Ethical Aspects in Relation to ICT Robotics -- 6.5 Ethical Aspects of Telemedicine -- 6.6 ICT for Improving Patients' Cognitive Functions -- 6.7 Ethical Aspects on ICT for Rehabilitation -- 6.8 Conclusions -- References -- Biographies -- Index -- Editor's Biographies
- 4.3.1.4 Shape operator -- 4.3.2 Multiple Kernel Learning for 3D Face and Emotion Recognition -- 4.3.3 3D Face Recognition -- 4.3.4 3D Facial Expression Recognition -- 4.4 Conclusion and Comments -- Acknowledgment -- References -- 5: An Integrated Perspective for Future Widespread Integration of Neuro-Motor Rehabilitation -- 5.1 Introduction -- 5.2 Overview of Motor Diseases and Their Rehabilitation -- 5.3 Two Main Approaches to Rehabilitation -- 5.4 Rehabilitative Basic Principles -- 5.5 Optimization of Current Rehabilitative Methods -- 5.5.1 Virtual Reality -- 5.5.2 EMG Feedback -- 5.6 Future Perspective -- 5.7 Conclusions -- References -- 6: Ethical Issues in the Use of Information and Communication Technologies in the Health Care of Patients with Neurological Disorders -- 6.1 Introduction -- 6.2 ICT for Health Care -- 6.3 Ethical Issues Associated with ICT for Health Care -- 6.3.1 State of the Art on ICT for Health Care -- 6.4 Ethical Aspects in Relation to ICT Robotics -- 6.5 Ethical Aspects of Telemedicine -- 6.6 ICT for Improving Patients' Cognitive Functions -- 6.7 Ethical Aspects on ICT for Rehabilitation -- 6.8 Conclusions -- References -- Index -- Editor's Biographies
- Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Foreword -- List of Abbreviations -- List of Figures -- List of Tables -- 1: Overview on BCI/BMI Applied -- 1.1 Introduction -- References -- 2: ICT for Neurorehabilitation -- 2.1 Introduction -- 2.2 Plasticity and Rehabilitation of the Brain -- 2.3 Attempts at Neural Rehabilitation with BMI -- 2.4 Conclusions -- References -- 3: ICT for New-Generation Prostheses -- 3.1 Introduction -- 3.2 Neuromusculoskeletal Modelling: Its Role in the Design of New-Generation Prostheses -- 3.2.1 Musculotendon Models and Parameters -- 3.2.2 Musculoskeletal Kinematics -- 3.2.3 Neuromuscular Control of Musculoskeletal Systems -- 3.2.4 Patient-Specific Neuromusculoskeletal Modelling -- 3.3 Catching the Intention to Move: Brain-Machine Interfaces -- 3.4 Kinematic Reconstruction and Goal-Directed BMI Approaches -- 3.5 The Hybrid Architecture and the Role of Shared-Control in BMI-Driven Devices -- 3.6 Future Challenges for New-Generation Prostheses -- References -- 4: Gaze Tracking, Facial Orientation Determination, Face and Emotion Recognition in 3D Space for Neurorehabilitation Applications -- Abstract -- 4.1 Introduction -- 4.2 Gaze Tracking and Face Orientation Determination with an Active Multicamera System with Kinect Sensor -- 4.2.1 System Overview -- 4.2.2 System Geometrical Model and Calibration -- 4.2.2.1 Modelling the Pan-Tilt Unit -- 4.2.2.2 Estimating the Transformation {G} ↔ {K} -- 4.2.3 Facial Extraction and Tracking -- 4.2.4 Gaze Direction Estimation -- 4.2.5 Experimental Results -- 4.3 3D Face and Emotion Recognition with Multiple Kernel Learning -- 4.3.1 Preprocessing and Feature Extraction -- 4.3.1.1 Point cloud filtering -- 4.3.1.2 Surface normal feature extraction -- 4.3.1.3 Locally adaptive regression kernels (LARK) feature extraction