Respiratory feature extraction in emotion of internet addiction abusers using complementary ensemble empirical mode decomposition

Background: Internet addiction can be generally conceptualized as excessive computer and Internet use which results in negative consequences in physical or mental functions. In recent years, Internet addiction is a growing problem around the world, and should be studied through scientific methods. Some studies indicated that Internet addiction was correlated to physical responses including heart rate, respiration, and psychological reactions including emotion, social interaction. This study assumed that emotion was one of significant roles in Internet addiction, and emotion can be observed by subjective self-report and objective autonomic nervous responses. Respiration can be a type of biofeedback to regulate respiratory rate and amplitude which affects autonomic nervous responses. The respiratory features in emotion states of Internet addiction abusers were investigated by Complementary Ensemble Empirical Mode Decomposition. Results: The results showed that the respiratory features of Internet addiction abusers differed from normal Internet users among different emotions. Such results could be expected to monitor or assist to treat Internet addiction.