Depression analysis: a multimodal approach

Jyoti Joshi

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

6 Citations (Scopus)

Abstract

Depression is a severe mental health disorder causing high societal costs. Current clinical practice depends almost exclusively on self report and clinical opinion, risking a range of subjective biases. It is therefore useful to design a diagnostic aid to assist clinicians. This project aims at developing a novel multimodal framework for depression analysis. In this PhD work, it is hypothesized that a multimodal affective sensing system can better capture what characterises a person's affective state than single modality systems. The project will explore facial dynamics, head movements, upper body gestures, EEG measures and speech characteristics related to affect, in subjects with major depressive disorders. Integrating the individual sensing modalities, a multimodal approach that show improved performance characteristics over single modality approaches will be developed.

Original languageEnglish
Title of host publicationICMI'12 - Proceedings of the ACM International Conference on Multimodal Interaction
PublisherAssociation for Computing Machinery (ACM)
Pages321-324
Number of pages4
ISBN (Print)9781450314671
DOIs
Publication statusPublished - 2012
Externally publishedYes
EventInternational Conference on Multimodal Interfaces 2012 - Santa Monica, United States of America
Duration: 22 Oct 201226 Oct 2012
Conference number: 14th
https://dl.acm.org/doi/proceedings/10.1145/2388676 (Proceedings)

Conference

ConferenceInternational Conference on Multimodal Interfaces 2012
Abbreviated titleICMI 2012
Country/TerritoryUnited States of America
CitySanta Monica
Period22/10/1226/10/12
Internet address

Keywords

  • Affective computing
  • Depression analysis
  • Multimodal framework

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