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Accepted for/Published in: JMIR Mental Health

Date Submitted: Apr 5, 2019
Open Peer Review Period: Apr 8, 2019 - Jun 3, 2019
Date Accepted: Jan 26, 2020
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder

Daus H, Bloecher T, Egeler R, De Klerk R, Stork W, Backenstrass M

Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder

JMIR Ment Health 2020;7(7):e14267

DOI: 10.2196/14267

PMID: 32618577

PMCID: 7367525

An emotion-sensitive approach for mood state recognition in bipolar disorder

  • Henning Daus; 
  • Timon Bloecher; 
  • Ronny Egeler; 
  • Richard De Klerk; 
  • Wilhelm Stork; 
  • Matthias Backenstrass

ABSTRACT

Internet- and mobile-based approaches have become more and more significant to psychological research in the field of bipolar disorders. While research suggests that emotional aspects of bipolar disorders are related to the overall functioning or the suicidality of patients, these aspects have so far not sufficiently been considered within the context of mobile-based disease management approaches. As a multi-professional research team, we have developed a new and emotion-sensitive assistance system, which we have adapted to the needs of bipolar patients. Next to the analysis of self-assessments, third party assessments and sensor data, the new assistance system analyzes video data of bipolar patients regarding its emotional content or the presence of emotional cues. In this article, we describe the theoretical and technological basis of our emotion-sensitive approach and do not present empirical data or a proof of concept. To our knowledge, the new assistance system incorporates the first mobile-based approach to analyze emotional expressions of bipolar patients. As a next step, the validity and feasibility of our emotion-sensitive approach must be evaluated. In the future, it might benefit diagnostic or prognostic purposes and complement existing systems with the help of new and intuitive interaction models.


 Citation

Please cite as:

Daus H, Bloecher T, Egeler R, De Klerk R, Stork W, Backenstrass M

Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder

JMIR Ment Health 2020;7(7):e14267

DOI: 10.2196/14267

PMID: 32618577

PMCID: 7367525

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