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Signal Processing to Drive Human-Computer Interaction : EEG and eye-controlled interfaces /

The book deals with the following subjects: signal processing for human-computer interaction; EEG and eye-controlled interfaces; EEG-based BCIs for communication and rehabilitation of people with motor impairment; brain-computer interfaces in a home environment for patients with motor impairment; pe...

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Bibliographic Details
Corporate Author: Institution of Engineering and Technology
Other Authors: Nikolopoulos, Spiros (Editor), Kumar, Chandan (Editor), Kompatsiaris, Ioannis (Editor)
Format: eBook
Language:English
Published: Stevenage : IET, 2020.
Series:Control, Robotics & Sensors.
Subjects:
Brain-computer interfaces.
Electroencephalography.
End-user computing.
Entertainment computing.
Human-computer interaction.
Machine learning.
Medical technology.
Signal processing.
brain-computer interfaces.
electroencephalography.
gaze tracking.
handicapped aids.
home computing.
human computer interaction.
learning (artificial intelligence)
medical signal processing.
multimedia computing.
patient rehabilitation.
visual evoked potentials.
NIRS signals
graph signal processing
sensorimotor rhythms
motor imagery
steady-state visual evoked potentials
machine learning
multimedia interface
eye tracking
user models
persuasive design
home environment
brain-computer interfaces
patient communication
patient rehabilitation
motor impairment
EEG-based BCIs
eye-controlled interfaces
EEG controlled interfaces
human-computer interaction
signal processing
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Summary:The book deals with the following subjects: signal processing for human-computer interaction; EEG and eye-controlled interfaces; EEG-based BCIs for communication and rehabilitation of people with motor impairment; brain-computer interfaces in a home environment for patients with motor impairment; persuasive design principles and user models for people with motor disabilities; eye tracking for interaction; multimedia interface adaptation; machine learning techniques for EEG data; BCIs using steady-state visual-evoked potentials; BCIs using motor imagery and sensorimotor rhythms; graph signal processing analysis of NIRS signals for brain-computer interfaces; and multimodal BCIs.
Physical Description:1 online resource (309 pages)
ISBN:9781785619205
DOI:10.1049/PBCE129E