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Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder
Internet- and mobile-based approaches have become increasingly significant to psychological research in the field of bipolar disorders. While research suggests that emotional aspects of bipolar disorders are substantially related to the social and global functioning or the suicidality of patients, t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367525/ https://www.ncbi.nlm.nih.gov/pubmed/32618577 http://dx.doi.org/10.2196/14267 |
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author | Daus, Henning Bloecher, Timon Egeler, Ronny De Klerk, Richard Stork, Wilhelm Backenstrass, Matthias |
author_facet | Daus, Henning Bloecher, Timon Egeler, Ronny De Klerk, Richard Stork, Wilhelm Backenstrass, Matthias |
author_sort | Daus, Henning |
collection | PubMed |
description | Internet- and mobile-based approaches have become increasingly significant to psychological research in the field of bipolar disorders. While research suggests that emotional aspects of bipolar disorders are substantially related to the social and global 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 multiprofessional research team, we have developed a new and emotion-sensitive assistance system, which we have adapted to the needs of patients with bipolar disorder. Next to the analysis of self-assessments, third-party assessments, and sensor data, the new assistance system analyzes audio and video data of these patients regarding their emotional content or the presence of emotional cues. In this viewpoint, 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 patients with bipolar disorder. As a next step, the validity and feasibility of our emotion-sensitive approach must be evaluated. In the future, it might benefit diagnostic, prognostic, or even therapeutic purposes and complement existing systems with the help of new and intuitive interaction models. |
format | Online Article Text |
id | pubmed-7367525 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-73675252020-08-07 Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder Daus, Henning Bloecher, Timon Egeler, Ronny De Klerk, Richard Stork, Wilhelm Backenstrass, Matthias JMIR Ment Health Viewpoint Internet- and mobile-based approaches have become increasingly significant to psychological research in the field of bipolar disorders. While research suggests that emotional aspects of bipolar disorders are substantially related to the social and global 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 multiprofessional research team, we have developed a new and emotion-sensitive assistance system, which we have adapted to the needs of patients with bipolar disorder. Next to the analysis of self-assessments, third-party assessments, and sensor data, the new assistance system analyzes audio and video data of these patients regarding their emotional content or the presence of emotional cues. In this viewpoint, 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 patients with bipolar disorder. As a next step, the validity and feasibility of our emotion-sensitive approach must be evaluated. In the future, it might benefit diagnostic, prognostic, or even therapeutic purposes and complement existing systems with the help of new and intuitive interaction models. JMIR Publications 2020-07-03 /pmc/articles/PMC7367525/ /pubmed/32618577 http://dx.doi.org/10.2196/14267 Text en ©Henning Daus, Timon Bloecher, Ronny Egeler, Richard De Klerk, Wilhelm Stork, Matthias Backenstrass. Originally published in JMIR Mental Health (http://mental.jmir.org), 03.07.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Viewpoint Daus, Henning Bloecher, Timon Egeler, Ronny De Klerk, Richard Stork, Wilhelm Backenstrass, Matthias Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder |
title | Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder |
title_full | Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder |
title_fullStr | Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder |
title_full_unstemmed | Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder |
title_short | Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder |
title_sort | development of an emotion-sensitive mhealth approach for mood-state recognition in bipolar disorder |
topic | Viewpoint |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367525/ https://www.ncbi.nlm.nih.gov/pubmed/32618577 http://dx.doi.org/10.2196/14267 |
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