dc.contributor.author |
Nadanamainthan, Sarvetha |
|
dc.date.accessioned |
2022-12-23T05:06:38Z |
|
dc.date.available |
2022-12-23T05:06:38Z |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Nadanamainthan, Sarvetha (2022) Depression Analysis Through Facial and Vocal Expressions. BEng. Dissertation, Informatics Institute of Technology |
en_US |
dc.identifier.issn |
2018427 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/1223 |
|
dc.description.abstract |
"Major Depressive Disorder is a mood illness that affects how you behave, think and feel with
the behavioural change of a person. In Sri Lanka, nearly 7% of adults are diagnosed with
depression every year. A person can diagnose with depression at any time and it can lead to
improper behaviour or performance in their life. Sometimes it might lead them to take their
own life. Traditionally it is diagnosed by interviewing the person with Beck Depression
Inventory, Beck Hopelessness Scale, Patient Health Questionnaire. These methods are
difficult and time consuming. Also, it requires full support from the patient.
In this paper an automatic early depression identification using machine learning is proposed using facial and vocal expressions. This will increase the quality of treatment and reduce the impact on patients’ real life." |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
Depression |
en_US |
dc.subject |
Major Depressive Disorder |
en_US |
dc.subject |
Machine Learning |
en_US |
dc.subject |
Audio and Video Modal |
en_US |
dc.title |
Depression Analysis Through Facial and Vocal Expressions |
en_US |
dc.type |
Thesis |
en_US |