An automated framework for depression analysis

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Abstract

This project aims at developing an automated framework for depression detection. During a depressive episode, patients suffer from psychomotor retardation and this phenomenon is not only limited to facial activity. In this PhD work, it is hypothesized that such complex affective state can be better represented by integrating information from various uni-modal channels to form a multimodal affective sensing system. The project explores facial dynamics, body expressions such as head movement, relative body part movement etc. in patients with major depressive disorders. The contribution of various channels is assessed and as a final objective, a framework combining discriminative channels for automatic depression analysis is proposed.

Original languageEnglish
Title of host publicationProceedings - 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction, ACII 2013
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages630-635
Number of pages6
ISBN (Print)9780769550480
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 5th Humaine Association Conference on Affective Computing and Intelligent Interaction, ACII 2013 - Geneva, Switzerland
Duration: 2 Sep 20135 Sep 2013

Conference

Conference2013 5th Humaine Association Conference on Affective Computing and Intelligent Interaction, ACII 2013
CountrySwitzerland
CityGeneva
Period2/09/135/09/13

Keywords

  • Automatic depression detection
  • Bag of words
  • Body movement analysis
  • Facial dynamics

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