Heart Rate Estimation From Facial Videos for Depression Analysis

Aamir Mustafa, Shalini Bhatia, Munawar Hayat, Roland Goecke

    Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

    3 Citations (Scopus)

    Abstract

    Automated facial video analysis is useful in numerous health care applications. For example, spatio-temporal analysis of such videos has been previously done for assisting clinicians in the diagnosis of depression. Physiological measures, such as an individual's heart rate, provide very important cues to understand a person's mental health. Unobtrusively estimated heart rate has not been previously used to analyse individuals' mental health. In this paper, we automatically estimate heart rate activity from facial videos. We then study the association of the estimated heart rate activity with the person's mental health, as diagnosed by clinicians. Specifically, from the heart rate activity in response to watching different movies, we classify individuals as either depressed or healthy. The efficacy of the proposed scheme is demonstrated by experimental evaluations on a clinically validated dataset. Our results suggest unobtrusively estimated heart rate to be very effective for depression analysis.

    Original languageEnglish
    Title of host publication2017 7th International Conference on Affective Computing and Intelligent Interaction, ACII 2017
    Place of PublicationSan Antonio, TX, USA
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages498-503
    Number of pages6
    ISBN (Electronic)9781538605639
    ISBN (Print)9781538605646
    DOIs
    Publication statusPublished - 2 Jul 2017

    Publication series

    Name2017 7th International Conference on Affective Computing and Intelligent Interaction, ACII 2017
    Volume2018-January

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