The Resource Biomechatronics in medical rehabilitation : biomodelling, interface, and control, Shane Xie, Wei Meng
Biomechatronics in medical rehabilitation : biomodelling, interface, and control, Shane Xie, Wei Meng
Resource Information
The item Biomechatronics in medical rehabilitation : biomodelling, interface, and control, Shane Xie, Wei Meng represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.This item is available to borrow from 1 library branch.
Resource Information
The item Biomechatronics in medical rehabilitation : biomodelling, interface, and control, Shane Xie, Wei Meng represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.
This item is available to borrow from 1 library branch.
- Summary
- This book focuses on the key technologies in developing biomechatronic systems for medical rehabilitation purposes. It includes a detailed analysis of biosignal processing, biomechanics modelling, neural and muscular interfaces, artificial actuators, robot-assisted training, clinical setup/implementation and rehabilitation robot control. Encompassing highly multidisciplinary themes in the engineering and medical fields, it presents researchers? insights into the emerging technologies and developments that are being utilized in biomechatronics for medical purposes. Presenting a detailed analysis of five key areas in rehabilitation robotics: (i) biosignal processing; (ii) biomechanics modelling; (iii) neural and muscular interfaces; (iv) artificial actuators and devices; and (v) the use of neurological and muscular interfaces in rehabilitation robots control, the book describes the design of biomechatronic systems, the methods and control systems used and the implementation and testing in order to show how they fulfil the needs of that specific area of rehabilitation. Providing a comprehensive overview of the background of biomechatronics and details of new advances in the field, it is especially useful for researchers, academics and graduates new to the field of biomechatronics engineering, and is also of interest to researchers and clinicians in the medical field who are not engineers
- Language
- eng
- Extent
- 1 online resource (214 pages)
- Note
- 8.5.2 Robot Experiments and Results
- Contents
-
- Preface; Acknowledgements; Contents; Nomenclature; 1 Introduction; 1.1 Medical Background and Requirements; 1.2 BCI Systems; 1.3 EMG-Based Neuromuscular Interface; 1.4 Human-Robot Interaction Control; 1.5 Summary; References; 2 State of the Art; 2.1 EEG-Based BCI and Its Challenges; 2.1.1 Steady State Visual Evoked Potentials; 2.1.2 EEG Signal Processing: Improving the SNR; 2.1.3 EEG Signal Processing: Signal Translation and Classification; 2.1.4 Current Limitations; 2.2 EMG and the Neuromuscular Interface; 2.2.1 Applications of sEMG; 2.2.2 sEMG-Based Neuromuscular Interface
- 2.2.3 Current Challenges2.3 Neuromusculoskeletal Models for Gait Rehabilitation; 2.3.1 Musculoskeletal Model; 2.3.2 EMG-Driven Models; 2.4 Discussion; 2.5 Summary; References; 3 Signal Processing Methods for SSVEP-Based BCIs; 3.1 Introduction; 3.2 Adjacent Narrow Band Filter (ANBF) Algorithm; 3.2.1 Artefact Reduction; 3.2.2 Frequency Recognition Strategy; 3.3 Methods and Materials; 3.3.1 Experimental Protocol; 3.3.2 EEG Recording and Evaluation; 3.4 Results; 3.5 Discussion; 3.6 Summary; References; 4 SSVEP-Based BCI for Lower Limb Rehabilitation; 4.1 Introduction; 4.2 Methods and Materials
- 4.2.1 Subjects and Visual Stimulator4.2.2 SSVEP Signal Processing; 4.2.3 Robotic Exoskeleton Device; 4.2.4 Experimental Protocols; 4.2.5 Control Algorithm; 4.3 Results; 4.4 Discussion; 4.5 Summary; References; 5 A Hybrid BCI for Gaming; 5.1 Introduction; 5.2 BCI Setup; 5.2.1 Signal Recording and Processing; 5.2.2 Super Street Fighter Video Game; 5.3 Experimental Method and Results; 5.3.1 Experimental Protocol; 5.3.2 Results; 5.4 Discussion; 5.5 Summary; References; 6 EMG-Driven Physiological Model for Upper Limb; 6.1 Neuromusculoskeletal Model; 6.1.1 Musculoskeletal Geometry Model
- 6.1.2 Musculotendon Model6.1.3 Kinematic Model; 6.2 Model Sensitivity Analysis; 6.2.1 Model Parameters; 6.2.2 Sensitivity Analysis; 6.2.3 Results and Discussion; 6.3 Elbow Physiological Model Validation; 6.3.1 Experimental Setup; 6.3.2 Model Validation; 6.4 Summary; References; 7 Exoskeleton Control Based on Neural Interface; 7.1 Exoskeleton Development; 7.2 Exoskeleton Control; 7.2.1 Control System Design; 7.2.2 Control of the Elbow Joint; 7.3 Human-Robot Interface; 7.3.1 Interface Design and Parameter Tuning; 7.3.2 Graphical User Interface; 7.4 Summary; References
- 8 Muscle Force Estimation Model for Gait Rehabilitation8.1 Patient-Specific Muscle Force Estimation; 8.1.1 Patient-Specific Musculoskeletal Model; 8.1.2 Inverse Dynamic Modelling; 8.1.3 Static Optimisation; 8.2 PMFE Evaluation and Results; 8.2.1 PMFE Evaluation; 8.2.2 Simulation Results; 8.2.3 Discussion; 8.3 Human-Inspired Robotic Exoskeleton; 8.4 Biological Command Based Controller; 8.4.1 Dynamic Modelling; 8.4.2 Patient-Specific Muscle Force Estimation; 8.4.3 PMFE Based Feedforward Controller; 8.5 PSBc Evaluation and Results; 8.5.1 Computer Simulation and Results
- Isbn
- 9783319528847
- Label
- Biomechatronics in medical rehabilitation : biomodelling, interface, and control
- Title
- Biomechatronics in medical rehabilitation
- Title remainder
- biomodelling, interface, and control
- Statement of responsibility
- Shane Xie, Wei Meng
- Language
- eng
- Summary
- This book focuses on the key technologies in developing biomechatronic systems for medical rehabilitation purposes. It includes a detailed analysis of biosignal processing, biomechanics modelling, neural and muscular interfaces, artificial actuators, robot-assisted training, clinical setup/implementation and rehabilitation robot control. Encompassing highly multidisciplinary themes in the engineering and medical fields, it presents researchers? insights into the emerging technologies and developments that are being utilized in biomechatronics for medical purposes. Presenting a detailed analysis of five key areas in rehabilitation robotics: (i) biosignal processing; (ii) biomechanics modelling; (iii) neural and muscular interfaces; (iv) artificial actuators and devices; and (v) the use of neurological and muscular interfaces in rehabilitation robots control, the book describes the design of biomechatronic systems, the methods and control systems used and the implementation and testing in order to show how they fulfil the needs of that specific area of rehabilitation. Providing a comprehensive overview of the background of biomechatronics and details of new advances in the field, it is especially useful for researchers, academics and graduates new to the field of biomechatronics engineering, and is also of interest to researchers and clinicians in the medical field who are not engineers
- Cataloging source
- EBLCP
- http://library.link/vocab/creatorName
- Xie, Shane
- Dewey number
-
- 610.28
- 620
- Index
- no index present
- LC call number
-
- R856
- TA1-2040
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- http://library.link/vocab/relatedWorkOrContributorName
- Meng, Wei
- http://library.link/vocab/subjectName
-
- Medical electronics
- Mechatronics
- Electronics, Medical
- Engineering
- Biomedical Engineering
- Biomedical Engineering/Biotechnology
- Rehabilitation
- Label
- Biomechatronics in medical rehabilitation : biomodelling, interface, and control, Shane Xie, Wei Meng
- Note
- 8.5.2 Robot Experiments and Results
- Antecedent source
- file reproduced from an electronic resource
- Bibliography note
- Includes bibliographical references
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
-
- Preface; Acknowledgements; Contents; Nomenclature; 1 Introduction; 1.1 Medical Background and Requirements; 1.2 BCI Systems; 1.3 EMG-Based Neuromuscular Interface; 1.4 Human-Robot Interaction Control; 1.5 Summary; References; 2 State of the Art; 2.1 EEG-Based BCI and Its Challenges; 2.1.1 Steady State Visual Evoked Potentials; 2.1.2 EEG Signal Processing: Improving the SNR; 2.1.3 EEG Signal Processing: Signal Translation and Classification; 2.1.4 Current Limitations; 2.2 EMG and the Neuromuscular Interface; 2.2.1 Applications of sEMG; 2.2.2 sEMG-Based Neuromuscular Interface
- 2.2.3 Current Challenges2.3 Neuromusculoskeletal Models for Gait Rehabilitation; 2.3.1 Musculoskeletal Model; 2.3.2 EMG-Driven Models; 2.4 Discussion; 2.5 Summary; References; 3 Signal Processing Methods for SSVEP-Based BCIs; 3.1 Introduction; 3.2 Adjacent Narrow Band Filter (ANBF) Algorithm; 3.2.1 Artefact Reduction; 3.2.2 Frequency Recognition Strategy; 3.3 Methods and Materials; 3.3.1 Experimental Protocol; 3.3.2 EEG Recording and Evaluation; 3.4 Results; 3.5 Discussion; 3.6 Summary; References; 4 SSVEP-Based BCI for Lower Limb Rehabilitation; 4.1 Introduction; 4.2 Methods and Materials
- 4.2.1 Subjects and Visual Stimulator4.2.2 SSVEP Signal Processing; 4.2.3 Robotic Exoskeleton Device; 4.2.4 Experimental Protocols; 4.2.5 Control Algorithm; 4.3 Results; 4.4 Discussion; 4.5 Summary; References; 5 A Hybrid BCI for Gaming; 5.1 Introduction; 5.2 BCI Setup; 5.2.1 Signal Recording and Processing; 5.2.2 Super Street Fighter Video Game; 5.3 Experimental Method and Results; 5.3.1 Experimental Protocol; 5.3.2 Results; 5.4 Discussion; 5.5 Summary; References; 6 EMG-Driven Physiological Model for Upper Limb; 6.1 Neuromusculoskeletal Model; 6.1.1 Musculoskeletal Geometry Model
- 6.1.2 Musculotendon Model6.1.3 Kinematic Model; 6.2 Model Sensitivity Analysis; 6.2.1 Model Parameters; 6.2.2 Sensitivity Analysis; 6.2.3 Results and Discussion; 6.3 Elbow Physiological Model Validation; 6.3.1 Experimental Setup; 6.3.2 Model Validation; 6.4 Summary; References; 7 Exoskeleton Control Based on Neural Interface; 7.1 Exoskeleton Development; 7.2 Exoskeleton Control; 7.2.1 Control System Design; 7.2.2 Control of the Elbow Joint; 7.3 Human-Robot Interface; 7.3.1 Interface Design and Parameter Tuning; 7.3.2 Graphical User Interface; 7.4 Summary; References
- 8 Muscle Force Estimation Model for Gait Rehabilitation8.1 Patient-Specific Muscle Force Estimation; 8.1.1 Patient-Specific Musculoskeletal Model; 8.1.2 Inverse Dynamic Modelling; 8.1.3 Static Optimisation; 8.2 PMFE Evaluation and Results; 8.2.1 PMFE Evaluation; 8.2.2 Simulation Results; 8.2.3 Discussion; 8.3 Human-Inspired Robotic Exoskeleton; 8.4 Biological Command Based Controller; 8.4.1 Dynamic Modelling; 8.4.2 Patient-Specific Muscle Force Estimation; 8.4.3 PMFE Based Feedforward Controller; 8.5 PSBc Evaluation and Results; 8.5.1 Computer Simulation and Results
- Dimensions
- unknown
- Extent
- 1 online resource (214 pages)
- File format
- one file format
- Form of item
- online
- Isbn
- 9783319528847
- Level of compression
- unknown
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other control number
- 10.1007/978-3-319-52884-7
- Quality assurance targets
- unknown
- Reformatting quality
- unknown
- Specific material designation
- remote
- System control number
- ocn971365124
- Label
- Biomechatronics in medical rehabilitation : biomodelling, interface, and control, Shane Xie, Wei Meng
- Note
- 8.5.2 Robot Experiments and Results
- Antecedent source
- file reproduced from an electronic resource
- Bibliography note
- Includes bibliographical references
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
-
- Preface; Acknowledgements; Contents; Nomenclature; 1 Introduction; 1.1 Medical Background and Requirements; 1.2 BCI Systems; 1.3 EMG-Based Neuromuscular Interface; 1.4 Human-Robot Interaction Control; 1.5 Summary; References; 2 State of the Art; 2.1 EEG-Based BCI and Its Challenges; 2.1.1 Steady State Visual Evoked Potentials; 2.1.2 EEG Signal Processing: Improving the SNR; 2.1.3 EEG Signal Processing: Signal Translation and Classification; 2.1.4 Current Limitations; 2.2 EMG and the Neuromuscular Interface; 2.2.1 Applications of sEMG; 2.2.2 sEMG-Based Neuromuscular Interface
- 2.2.3 Current Challenges2.3 Neuromusculoskeletal Models for Gait Rehabilitation; 2.3.1 Musculoskeletal Model; 2.3.2 EMG-Driven Models; 2.4 Discussion; 2.5 Summary; References; 3 Signal Processing Methods for SSVEP-Based BCIs; 3.1 Introduction; 3.2 Adjacent Narrow Band Filter (ANBF) Algorithm; 3.2.1 Artefact Reduction; 3.2.2 Frequency Recognition Strategy; 3.3 Methods and Materials; 3.3.1 Experimental Protocol; 3.3.2 EEG Recording and Evaluation; 3.4 Results; 3.5 Discussion; 3.6 Summary; References; 4 SSVEP-Based BCI for Lower Limb Rehabilitation; 4.1 Introduction; 4.2 Methods and Materials
- 4.2.1 Subjects and Visual Stimulator4.2.2 SSVEP Signal Processing; 4.2.3 Robotic Exoskeleton Device; 4.2.4 Experimental Protocols; 4.2.5 Control Algorithm; 4.3 Results; 4.4 Discussion; 4.5 Summary; References; 5 A Hybrid BCI for Gaming; 5.1 Introduction; 5.2 BCI Setup; 5.2.1 Signal Recording and Processing; 5.2.2 Super Street Fighter Video Game; 5.3 Experimental Method and Results; 5.3.1 Experimental Protocol; 5.3.2 Results; 5.4 Discussion; 5.5 Summary; References; 6 EMG-Driven Physiological Model for Upper Limb; 6.1 Neuromusculoskeletal Model; 6.1.1 Musculoskeletal Geometry Model
- 6.1.2 Musculotendon Model6.1.3 Kinematic Model; 6.2 Model Sensitivity Analysis; 6.2.1 Model Parameters; 6.2.2 Sensitivity Analysis; 6.2.3 Results and Discussion; 6.3 Elbow Physiological Model Validation; 6.3.1 Experimental Setup; 6.3.2 Model Validation; 6.4 Summary; References; 7 Exoskeleton Control Based on Neural Interface; 7.1 Exoskeleton Development; 7.2 Exoskeleton Control; 7.2.1 Control System Design; 7.2.2 Control of the Elbow Joint; 7.3 Human-Robot Interface; 7.3.1 Interface Design and Parameter Tuning; 7.3.2 Graphical User Interface; 7.4 Summary; References
- 8 Muscle Force Estimation Model for Gait Rehabilitation8.1 Patient-Specific Muscle Force Estimation; 8.1.1 Patient-Specific Musculoskeletal Model; 8.1.2 Inverse Dynamic Modelling; 8.1.3 Static Optimisation; 8.2 PMFE Evaluation and Results; 8.2.1 PMFE Evaluation; 8.2.2 Simulation Results; 8.2.3 Discussion; 8.3 Human-Inspired Robotic Exoskeleton; 8.4 Biological Command Based Controller; 8.4.1 Dynamic Modelling; 8.4.2 Patient-Specific Muscle Force Estimation; 8.4.3 PMFE Based Feedforward Controller; 8.5 PSBc Evaluation and Results; 8.5.1 Computer Simulation and Results
- Dimensions
- unknown
- Extent
- 1 online resource (214 pages)
- File format
- one file format
- Form of item
- online
- Isbn
- 9783319528847
- Level of compression
- unknown
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other control number
- 10.1007/978-3-319-52884-7
- Quality assurance targets
- unknown
- Reformatting quality
- unknown
- Specific material designation
- remote
- System control number
- ocn971365124
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/portal/Biomechatronics-in-medical-rehabilitation-/Ggrj2IaCoqM/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/portal/Biomechatronics-in-medical-rehabilitation-/Ggrj2IaCoqM/">Biomechatronics in medical rehabilitation : biomodelling, interface, and control, Shane Xie, Wei Meng</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>
