A Model of Normality Inspired Deep Learning Framework for Depression Relapse Prediction Using Audiovisual Data.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND: Depression (Major Depressive Disorder) is one of the most common mental illnesses. According to the World Health Organization, more than 300 million people in the world are affected. A first depressive episode can be solved by a spontaneous remission within 6 to 12 months. It has been shown that depression affects speech production and facial expressions. Although numerous studies are proposed in the literature for depression recognition using audiovisual cues, depression relapse using audiovisual cues has not been studied in the literature.

Authors

  • Alice Othmani
    Université Paris-Est Créteil (UPEC), LISSI, Vitry sur Seine 94400, France. Electronic address: alice.othmani@u-pec.fr.
  • Assaad-Oussama Zeghina
    Université Paris-Est Créteil (UPEC), LISSI, Vitry sur Seine 94400, France.
  • Muhammad Muzammel
    Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.