International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Emotion Recognition Using Physiological Signals and Different Datasets

Author : Emily Joy ¹ Willson Joseph ² Dr. M. Rajeswari ³ Dr. R. Sunder ⁴

Date of Publication :20th May 2021

Abstract: Now a dayâ€™s emotion recognition has an important role in day-to-day life. Because emotions have greater value in human life. From the emotions, we can check whether the person is healthy or not and also the mental stability. For this mainly 8 basic emotions are fear, disgust, anger, happiness, sadness, acceptance, expectancy, and surprise. It also includes emotions like interest, guilt, shame, and neglect. To recognize these emotions mainly face recognition methods and speech recognition methods are used. But they are mainly in attention to facial expressions, speech, and gestures. By using visible signs of emotions cannot achieve the actual emotions of people. To gain true emotions, we are using Emotion Recognition using Physiological signals. In this paper, we use photoplethysmography (PPG), and galvanic skin response (GSR) signals as the data for recognizing the emotions and for classification. We use different classification methods to acquire the best accuracy. By this, we obtain emotions like sad, happy, and neutral. Using a modified random forest method, we achieve high accuracy of 97% for classification.

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