Reflects on developments in noninvasive electromyography, and includes advances and applications in signal detection, processing and interpretation
- Addresses EMG imaging technology together with the issue of decomposition of surface EMG
- Includes advanced single and multi-channel techniques for information extraction from surface EMG signals
- Presents the analysis and information extraction of surface EMG at various scales, from motor units to the concept of muscle synergies.
Author(s): Farina, Dario; Merletti, Roberto
Series: IEEE Press series in biomedical engineering
Edition: 1
Publisher: IEEE Press, Wiley
Year: 2016
Language: English
Pages: 731
City: Hoboken, NJ
Tags: Медицинские дисциплины;Клинические методы диагностики, лабораторная диагностика;Функциональная диагностика;
Content: Series Page
Title Page
Copyright
Introduction
Acknowledgments
Contributors
Chapter 1: Physiology of Muscle Activation and Force Generation
1.1 Introduction
1.2 Anatomy of a Motor Unit
1.3 Motor Neuron
1.4 Muscle Unit
1.5 Recruitment and Rate Coding
1.6 Summary
References
Chapter 2: Biophysics of the Generation of EMG Signals
2.1 Introduction
2.2 EMG Signal Generation
2.3 Anatomical, Physical, and Detection System Parameters Influencing EMG Features
2.4 Crosstalk
2.5 EMG Amplitude and Force
2.6 Conclusion/Summary
References Chapter 3: Detection and Conditioning of Surface EMG Signals3.1 Introduction
3.2 The Electrode-Skin Interface and the Front-End Amplifier Stage
3.3 State of the Art on EMG Signal Conditioning and Interfacing Solutions
3.4 ASIC Solutions on the Market
3.5 Perspectives for the Future
References
Chapter 4: Single-Channel Techniques for Information Extraction from the Surface EMG Signal
4.1 Introduction
4.2 Spectral Estimation of Deterministic Signals and Stochastic Processes
4.3 Basic Surface EMG Signal Models
4.4 Surface EMG Amplitude Estimation 4.5 Extraction of Information in the Frequency Domain from Surface EMG Signals4.6 Conclusions
References
Chapter 5: Techniques for Information Extraction from the Surface EMG Signal: High-Density Surface EMG
5.1 Introduction
5.2 Spatial Distribution of EMG Potential and EMG Features in Muscles with Fibers Parallel to the Skin
5.3 Spatial Distribution of EMG Potential and Features in Pinnate Muscles
5.4 Current Applications and Future Perspectives of HDsEMG
References
Chapter 6: Muscle Coordination, Motor Synergies, and Primitives from Surface EMG
6.1 Introduction 6.2 Muscle Synergies and Spinal Maps6.3 Muscle Synergies in Posture Control
6.4 Modular Control of Arm Reaching Movements
6.5 Motor Primitives in Human Locomotion
6.6 Conclusions
References
Chapter 7: Surface EMG Decomposition
7.1 Introduction
7.2 EMG Mixing Process
7.3 EMG Decomposition Techniques
7.4 Validation of Decomposition
References
Chapter 8: EMG Modeling and Simulation
8.1 Introduction
8.2 Principles of Modeling and Simulation
8.3 Phenomenological Surface EMG Models
8.4 Structure-Based Surface EMG Models
8.5 Modeling the Action Potential Source 8.6 Models of Volume Conduction and Detection Systems8.7 Models of the Surface EMG Signal
8.8 Model Validation
8.9 Applications of Modeling
8.10 Conclusions
References
Chapter 9: Electromyography-Driven Modeling for Simulating Subject-Specific Movement at the Neuromusculoskeletal Level
9.1 Introduction
9.2 Motion Capturing and Biomechanical Modeling of the Human Body
9.3 Musculoskeletal Modeling
9.4 EMG-Driven Musculoskeletal Modeling and Simulation
9.5 Experimental Results and Applications
9.6 Conclusions
Acknowledgment
References
