Signal Processing to Drive Human-Computer Interaction: EEG and eye-controlled interfaces
Signal Processing to Drive Human-Computer Interaction: EEG and eye-controlled interfaces
edited by Spiros Nikolopoulos, Chandan Kumar and Ioannis Kompatsiaris
The Institution of Engineering and Technology, 2020 eISBN: 978-1-78561-920-5 | Cloth: 978-1-78561-919-9 Library of Congress Classification TK5102.9.S5488 2020 Dewey Decimal Classification 621.3822
ABOUT THIS BOOK | TOC
ABOUT THIS BOOK
The evolution of eye tracking and brain-computer interfaces has given a new perspective on the control channels that can be used for interacting with computer applications. In this book leading researchers show how these technologies can be used as control channels with signal processing algorithms and interface adaptations to drive a human-computer interface.
TABLE OF CONTENTS
Chapter 1: Introduction
Part I: Reviewing existing literature on the benefits of BCIs, studying the computer use requirements and modeling the (dis)abilities of people with motor impairment
Chapter 2: The added value of EEG-based BCIs for communication and rehabilitation of people with motor impairment
Chapter 3: Brain-computer interfaces in a home environment for patients with motor impairment - the MAMEM use case
Chapter 4: Persuasive design principles and user models for people with motor disabilities
Part II: Algorithms and interfaces for interaction control through eyes and mind
Chapter 5: Eye tracking for interaction: adapting multimedia interfaces
Chapter 6: Eye tracking for interaction: evaluation methods
Chapter 7: Machine-learning techniques for EEG data
Chapter 8: BCIs using steady-state visual-evoked potentials
Chapter 9: BCIs using motor imagery and sensorimotor rhythms
Chapter 10: Graph signal processing analysis of NIRS signals for brain-computer interfaces
Part III: Multimodal prototype interfaces that can be operated through eyes and mind
Chapter 11: Error-aware BCIs
Chapter 12: Multimodal BCIs - the hands-free Tetris paradigm