Signal Processing to Drive Human-Computer Interaction

Signal Processing to Drive Human-Computer Interaction
  • eBook:
    Signal Processing to Drive Human-Computer Interaction: EEG and eye-controlled interfaces
  • Author:
    Spiros Nikolopoulos, Chandan Kumar, Ioannis Kompatsiaris
  • Edition:
  • Categories:
  • Data:
    July 8, 2020
  • ISBN:
  • ISBN-13:
  • Language:
  • Pages:
    312 pages
  • Format:

Book Description
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.
Topics included in the book include a comprehensive overview of eye-mind interaction incorporating algorithm and interface developments; modeling the (dis)abilities of people with motor impairment and their computer use requirements and expectations from assistive interfaces; and signal processing aspects including acquisition, preprocessing, enhancement, feature extraction, and classification of eye gaze, EEG (Steady-state visual evoked potentials, motor imagery and error-related potentials) and near-infrared spectroscopy (NIRS) signals. Finally, the book presents a comprehensive set of guidelines, with examples, for conducting evaluations to assess usability, performance, and feasibility of multi-model interfaces combining eye gaze and EEG based interaction algorithms.
The contributors to this book are researchers, engineers, clinical experts, and industry practitioners who have collaborated on these topics, providing an interdisciplinary perspective on the underlying challenges of eye and mind interaction and outlining future directions in the field.


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
2. The added value of EEG-based BCIs for communication and rehabilitation of people with motor impairment
3. Brain–computer interfaces in a home environment for patients with motor impairment—the MAMEM use case
4. Persuasive design principles and user models for people with motor disabilities

Part II - Algorithms and interfaces for interaction control through eyes and mind
5. Eye tracking for interaction: adapting multimedia interfaces
6. Eye tracking for interaction: evaluation methods
7. Machine-learning techniques for EEG data
8. BCIs using steady-state visual-evoked potentials
9. BCIs using motor imagery and sensorimotor rhythms
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
11. Error-aware BCIs
12. Multimodal BCIs – the hands-free Tetris paradigm
13. Conclusions

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