Effective Emoticon Suggestion Technique Based on Active Emotional Input Using Facial Expressions and Heart Rate Signals

Abstract

The evolution of mobile communication technology has brought about significant changes in the way people communicate. However, the lack of nonverbal cues in computer-mediated communication can make the accurate interpretation of emotions difficult. This study proposes a novel approach for using emotions as active input in mobile systems. This approach combines psychological and neuroscientific principles to accurately and comprehensively assess an individual's emotions for use as input in mobile systems. The proposed technique combines facial and heart rate information to recognize users' five prime emotions, which can be implemented on mobile devices using a front camera and a heart rate sensor. A user evaluation was conducted to verify the efficacy and feasibility of the proposed technique, and the results showed that users could express emotions faster and more accurately, with average recognition accuracies of 90% and 82% for induced and intended emotional expression, respectively. The proposed technique has the potential to enhance the user experience and provide more personalized and dynamic interaction with mobile systems.