"Emotion and Attention Recognition Based on Biological Signals and Images" ed. by Seyyed Abed Hosseini

This book basic idea is to present a common framework for the neuroscientists from diverse backgrounds in the cognitive neuroscience to illustrate their theoretical and applied research findings in emotion, stress, and attention. The book attempts to introduce the different soft computing approaches and technologies for recognition of emotion, stress, and attention, from a historical development, focusing particularly on the recent development of the field and its specialization within neuropsychology, cognitive science, neuroscience, and engineering.

Emotion, stress, and attention recognition are the most important aspects in neuropsychology, cognitive science, neuroscience, and engineering. Biological signals and images processing such as galvanic skin response (GSR), electrocardiography (ECG), heart rate variability (HRV), electromyography (EMG), electroencephalography (EEG), event-related potentials (ERP), eye tracking, functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI) have a great help in understanding the mentioned cognitive processes. Emotion, stress, and attention recognition systems based on different soft computing approaches have many engineering and medical applications.

Contents
Preface
1 Introductory Chapter: Emotion and Attention Recognition Based on Biological Signals and Images
2 Human Automotive Interaction: Affect Recognition for Motor Trend Magazine's Best Driver Car of the Year
3 Affective Valence Detection from EEG Signals Using Wrapper Methods
4 Tracking the Sound of Human Affection: EEG Signals Reveal Online Decoding of Socio-Emotional Expression in Human Speech and Voice
5 Multimodal Affect Recognition: Current Approaches and Challenges