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

Dai Ling Hsieh, Hong Ming Ji, Tzu-Chien Hsiao*, Bak Sau Yip

*Corresponding author for this work

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)391-399
Number of pages9
JournalJournal of Medical Imaging and Health Informatics
Volume5
Issue number2
DOIs
StatePublished - 1 Apr 2015

Keywords

  • Autonomic nervous responses
  • Complementary Ensemble Empirical Mode Decomposition (CEEMD)
  • Emotion
  • Feature extraction
  • Internet Addiction (IA)
  • Respiration

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