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Biophysical signal based emotion detection for technology enabled affective learning

Recent neurological study specifies that role of emotion in human cognition is of lot of importance. Human Computer Interaction (HCI) aims for recognizing the learner's emotional state in order to provide a horizontal interface between human and computer. Our work focuses on emotion detection from physiological signals; this study explores how emotion evolves during learning process and how emotion feedback absolves to improve learning experiences. We propose a learner emotion detection method using biophysical signals and achieved an efficient model for affective learning system, which obtained sound classification rate. Our research shows reasonable results in comparison with the existing systems. The result proves that the recognizer system is efficient.