Emotion and Attention Recognition Based on Biological Signals and Images
Seyyed Abed Hosseini
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. The book Emotion and Attention Recognition Based on Biological Signals and Images 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. The 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.