Emotion recognition from haptic touch on android device screens

Abstract

The recognition of the emotional state of an individual at a given time point provides valuable information that can find numerous health-related applications, e.g., interventions treating mental or physiological health problems. However, efficient emotion recognition remains a difficult task, often attempted subjectively, with obtrusive means and/or using specialized hardware. The present work uses haptic touch data acquired from Android smartphones to takes the first step towards the development of an objective, unobtrusive and real-life emotion recognition method that exploits the association between emotion and haptic touch. Focusing on four basic emotions (Excitement, Relaxation, Boredom and Frustration) the proposed method achieves very promising classification accuracy using a mixture of feature extraction and machine learning based classification techniques. A well-sized haptic touch dataset has been collected to support the method development and performance evaluation.