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EEG-Based Brain-Computer Interfaces : Cognitive Analysis and Control Applications /
EEG-Based Brain-Computer Interface: Cognitive Analysis and Control Applications provides a technical approach to using brain signals for control applications, along with the EEG-related advances in BCI. The research and techniques in this book discuss time and frequency domain analysis on deliberate...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Academic Press,
[2019]
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| Edición: | First edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Front Cover; EEG-Based Brain-Computer Interfaces: Cognitive Analysis and Control Applications; Copyright; Contents; Preface; Acknowledgments; Chapter 1: Introduction; 1.1. Rationale; 1.1.1. BCI Success Stories; 1.1.2. BCI Market Analysis; 1.2. Technical Overview; 1.2.1. Brain Anatomy; 1.2.2. From Brain to Computer; 1.2.3. Previous Work Related to Voluntary Eyeblink-Based BCI and Control; 1.3. Objectives; References; Chapter 2: EEG-Based Brain-Computer Interfacing (BCI); 2.1. Introduction; 2.1.1. EEG-Based BCI Architecture; 2.1.1.1. Signal Acquisition; 2.1.1.2. Preprocessing
- 2.1.1.3. Feature Extraction2.1.1.4. Classification; 2.1.1.5. Translation Into Operative Control Signals; 2.2. Techniques in BCI; 2.2.1. Invasive and Partially-Invasive BCI Techniques; 2.2.1.1. Electrocorticography (ECoG); 2.2.1.2. Intracortical Neuron Recording; 2.2.2. Noninvasive BCI Techniques; 2.2.2.1. Magnetoencephalography (MEG); 2.2.2.2. Functional Magnetic Resonance Imaging; 2.2.2.3. Functional Near-Infrared Spectroscopy (fNIRS); 2.2.2.4. Electroencephalography (EEG); 2.3. Data Acquisition; 2.3.1. Brain Electric Potential; 2.3.2. EEG Electrode Positioning; 2.3.3. EEG Electrodes
- 2.3.4. EEG Signals and Rhythms2.3.5. Preamplification, Filtering and Analog-to-Digital Conversion; 2.4. Preprocessing; 2.4.1. EEG Artifacts; 2.4.1.1. Physiological Artifacts; 2.4.1.2. Nonphysiological Artifacts; 2.4.2. EEG Artifact Rejection; 2.4.2.1. Artifact Rejection Using Temporal Filtering; 2.4.2.2. Artifact Rejection Using Spatial Filtering; 2.5. Feature Extraction; 2.5.1. EEG Signal Representation in Time Domain; 2.5.1.1. Event-Related Synchronization/Desynchronization (ERS/ERD); 2.5.1.2. Evoked Potentials; 2.5.1.3. Slow Cortical Potentials
- 2.5.2. EEG Signal Representation in Frequency Domain2.5.2.1. Band Power Features; 2.5.2.2. PSD Features; 2.5.3. EEG Signal Representation in Time-Frequency Domain; 2.5.3.1. Short-Time Fourier Transform; 2.5.3.2. Wavelet Transform; 2.5.4. EEG Signal Representation in Spatial Domain; 2.6. Classification; 2.6.1. Linear Classifiers; 2.6.2. Nonlinear Classifiers; 2.6.3. BCI Performance; 2.7. BCI Applications; 2.7.1. BCI: Clinical Applications; 2.7.1.1. BCI-Based Assistive Devices for Communication; 2.7.1.2. BCI-Based Assistive Devices for Locomotion and Movement
- 2.7.1.3. BCI for Neurorehabilitation2.7.1.4. BCI for Cognitive State Analysis; 2.7.1.5. BCI for Medical Diagnostics; 2.7.2. BCI: Nonclinical Applications; 2.7.2.1. BCI in Neuroergonomics; 2.7.2.2. BCI for Smart Home; 2.7.2.3. BCI in Neuromarketing and Advertising; 2.7.2.4. BCI for Games and Entertainment; 2.7.2.5. BCI for Security and Validation; 2.8. Conclusion; References; Further Reading; Chapter 3: Real-Time EEG Acquisition; 3.1. Introduction; 3.2. Overview of Acquisition Units; 3.2.1. Selection Criteria in Terms of Specifications; 3.2.2. EEG Devices; 3.2.2.1. Emotive Epoc/Epoc+ Headset