Examining Human-Horse Interaction by Means of Affect Recognition via Physiological Signals

Emotion Recognition from Physiological Signals for User Modeling of Affect

In this paper, we describe algorithms developed to analyze physiological signals associated with emotions, in order to recognize the affective states of users via noninvasive technologies. We propose a framework for modeling user's emotions from the sensory inputs and interpretations of our multi-modal system. We also describe examples of circumstances that these systems can

Experimental Transmission of African Horse-Sickness by Means of Mosquitoes

Detection and Classification of Emotions Using Physiological Signals and Pattern Recognition Methods

Introduction: Emotions play an important role in health, communication, and interaction between humans. The ability to recognize the emotional status of people is an important indicator of health and natural relationships. In DEAP database, electroencephalogram (EEG) signals as well as environmental physiological signals related to 32 volunteers are registered. The participants in each video we...

Emotion recognition from physiological signals.

Emotion recognition is one of the great challenges in human-human and human-computer interaction. Accurate emotion recognition would allow computers to recognize human emotions and therefore react accordingly. In this paper, an approach for emotion recognition based on physiological signals is proposed. Six basic emotions: joy, sadness, fear, disgust, neutrality and amusement are analysed using...

Emotion Recognition from Physiological Signals

Nowadays keeping healthy has become one of the most important topics in our daily life. Keeping good mood is very helpful to one’s health. A lot of smart sensing systems have been designed and developed to detect human emotions. The physiological parameters obtained from the sensing system are then received and analyzed by computers. The physiological dataset collected by computers is then proc...