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74467-01 - Masterprojekt: Automated Investigation of the Symptomatology and Indicators of Affective Disorders (4 KP)
| Semester | Frühjahrsemester 2025 |
| Angebotsmuster | einmalig |
| Dozierende | Eric Marcel Mayor (ericmarcel.mayor@unibas.ch, BeurteilerIn) |
| Inhalt | Advances in computer science have afforded many benefits to clinical psychology and psychiatry. Some of these are related to the delivery of psychotherapy, in the case of internet based cognitive therapy for instance. Other forms of benefits include the automated assessement of individuals’ mental state, for instance from their tone of voice, or textal productions. A main aim of the Research Domain Criteria framework (see Cuthbert, 2014) is to extend the modalities of investigation in mental health and well-being research. The proposed master thesis topic is grounded in such an approach and aims at exploring the opportunities of automated assessment through voice (recordings of participants) or text (e.g., social media or reddit posts), in this area, focusing on the symptomatology and indicators of affective disorders. Enrolled students will first acquire knowledge on related topics and will participate in developing research questions. They will also participate in empirical research. Their tasks might include: study preparation, participant recruitment, as well as collection, preparation and analysis of data. It is planned that students will work together until this stage. They are each encouraged to start searching for and reading the relevant literature early on. Then they will work on their master thesis independently. |
| Literatur | Elzeiny, S., & Qaraqe, M. (2018, October). Machine learning approaches to automatic stress detection: A review. In 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA) (pp. 1-6). IEEE. Guntuku, S. C., Yaden, D. B., Kern, M. L., Ungar, L. H., & Eichstaedt, J. C. (2017). Detecting depression and mental illness on social media: an integrative review. Current Opinion in Behavioral Sciences, 18, 43-49. Kurniawan, H., Maslov, A. V., & Pechenizkiy, M. (2013, June). Stress detection from speech and galvanic skin response signals. In Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems (pp. 209-214). IEEE. |
| Bemerkungen | Dates by arrangement with the lecturer. |
| Teilnahmevoraussetzungen | Abgeschlossenes Bachelorstudium Psychologie (StO15). |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
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Keine Einzeltermine verfügbar, bitte informieren Sie sich direkt bei den Dozierenden.
| Module |
Modul: Masterprojekt Klinische Psychologie und Neurowissenschaften (Masterstudium: Psychologie (Studienbeginn vor 01.08.2024)) |
| Prüfung | Lehrveranst.-begleitend |
| Hinweise zur Prüfung | For the master's project 4 KP can be acquired. For the regular obligatory participation in the master's colloquium an additional 1KP is acquired (StO15). |
| An-/Abmeldung zur Prüfung | Anm.: Belegen Lehrveranstaltung; Abm.: stornieren |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | Pass / Fail |
| Belegen bei Nichtbestehen | nicht wiederholbar |
| Zuständige Fakultät | Fakultät für Psychologie, studiendekanat-psychologie@unibas.ch |
| Anbietende Organisationseinheit | Fakultät für Psychologie |