| Acknowledgement | 第4-6页 |
| Abstract | 第6-7页 |
| 摘要 | 第8-16页 |
| Chapter (1): Upper Limb Amputation and the Need for Prostheses | 第16-24页 |
| 1.1 Introduction | 第16-17页 |
| 1.2 Status of residual limb | 第17-18页 |
| 1.3 Multifunctional upper limb prostheses | 第18-19页 |
| 1.4 Contribution of the dissertation | 第19-21页 |
| 1.4.1 Resolving the adverse impact of mobility on upper prostheses | 第19-20页 |
| 1.4.2 Novel feature extraction methods for improved myo control | 第20页 |
| 1.4.3 Towards an efficient multifunctional neuroprosthesis | 第20-21页 |
| 1.5 Organization of dissertation | 第21-24页 |
| CHAPTER (2): Advances in Upper Limb Prostheses and Challenges | 第24-34页 |
| 2.1 Introduction | 第24页 |
| 2.2 Evolutionary trends in upper limb prostheses | 第24-25页 |
| 2.3 Mechanically powered and myoelectrically powered prostheses | 第25-30页 |
| 2.3.1 Body-powered prostheses | 第26页 |
| 2.3.2 Motorized prostheses | 第26页 |
| 2.3.3 Non-pattern recognition based controls | 第26-28页 |
| 2.3.4 Pattern recognition based control | 第28-30页 |
| 2.4 Non EMG-PR based prosthetic technologies | 第30-34页 |
| CHAPTER (3): Investigating and Resolving the Impact of Mobility of EMG-PR Systems | 第34-59页 |
| 3.1 Introduction | 第34-35页 |
| 3.2 Material and Methods | 第35-46页 |
| 3.2.1 Subjects’ information | 第35-36页 |
| 3.2.2 Equipment setup and data collection | 第36-38页 |
| 3.2.3 Data preprocessing and segmentation | 第38-40页 |
| 3.2.4 Feature extraction and classification | 第40-43页 |
| 3.2.5 Resolving the effect of mobility | 第43-44页 |
| 3.2.6 Statistical analyses | 第44-46页 |
| 3.3 Experimental Results | 第46-54页 |
| 3.3.1 Effect of mobility on the amputated limb | 第46-48页 |
| 3.3.2 Effect of mobility on the intact limb | 第48-49页 |
| 3.3.3 Strategies to minimize the effect of mobility | 第49-51页 |
| 3.3.4 Sensitivity of individual arm motion to mobility | 第51-54页 |
| 3.4 Discussion | 第54-58页 |
| 3.5 Conclusion | 第58-59页 |
| CHAPTER (4): Novel Feature Extraction Methods for Improved Myo Control | 第59-75页 |
| 4.1 Introduction | 第59-60页 |
| 4.2 Material and Methods | 第60-67页 |
| 4.2.1 Subject information | 第60-61页 |
| 4.2.2 Equipment and data collection | 第61-62页 |
| 4.2.3 Data preprocessing | 第62-63页 |
| 4.2.4 Feature extraction and arm movement classification | 第63-66页 |
| 4.2.4.1 Newly proposed time-domain feature extraction methods | 第63-64页 |
| 4.2.4.2 Conventionally used time-domain features | 第64-66页 |
| 4.2.5 Arm movement classification and performance measures | 第66-67页 |
| 4.2.6 Statistical analyses | 第67页 |
| 4.3 Results and Discussion | 第67-74页 |
| 4.3.1 Classification performance of the newly proposed features | 第67-70页 |
| 4.3.2 Ratio of correctly classified to misclassified samples | 第70-71页 |
| 4.3.3 Execution time of EMG-PR for movement classification | 第71-73页 |
| 4.3.4 Quantifying the memory size for feature storage | 第73-74页 |
| 4.4 Conclusion | 第74-75页 |
| CHAPTER (5): Towards an Efficient Multifunctional EEG based Prostheses | 第75-93页 |
| 5.1 Introduction | 第75-77页 |
| 5.2 Method and Materials | 第77-84页 |
| 5.2.1 Participant information | 第77页 |
| 5.2.2 Equipment setup and experimental protocol | 第77-78页 |
| 5.2.3 EEG Data collection and preprocessing | 第78-79页 |
| 5.2.4 EEG feature extraction methods | 第79-82页 |
| 5.2.5 EEG pattern classification and feature evaluation | 第82-83页 |
| 5.2.6 Evaluation metrics | 第83-84页 |
| 5.3 Results and Discussion | 第84-92页 |
| 5.3.1 Performance of individual EEG feature method | 第84-88页 |
| 5.3.2 Recognition of individual motor imagery task | 第88-89页 |
| 5.3.3 Performance of EEG features across different frequency band | 第89-90页 |
| 5.3.4 Robust multiple EEG feature set | 第90-92页 |
| 5.4 Conclusion | 第92-93页 |
| CHAPTER (6): Conclusion of dissertation and Future research directions | 第93-96页 |
| 6.1 Conclusion of dissertation | 第93-94页 |
| 6.2 Future research directions | 第94-96页 |
| References | 第96-103页 |
| Author’s biography | 第103-107页 |
