Authors :
V. Jyothi; Khyati S Desai; T Nihal Reddy; V Lakshmi Sruthi
Volume/Issue :
Volume 8 - 2023, Issue 3 - March
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://bit.ly/40BlFld
DOI :
https://doi.org/10.5281/zenodo.7789089
Abstract :
The majority of people deal with depression
on a daily basis, which is a prevalent and seriousmental
illness. Depression has an impact on a person's physical,
psychological, and mental health in addition to their
emotional state. In contrast to other illnesses, depression
cannot be diagnosed through laboratory testing, goes
unnoticed due to a lack of knowledge and awareness,
and can deteriorate to the point of suicide. Physicians
are currently using self-reported questionnaires and inperson interactions as part of their diagnostic process for
identifying depression. A psychiatricevaluation of social
interactions and human behaviour is required for the
diagnosis of depression. The patient's audio and video
recordings show how people with depression behave
differently than average people do. The user and the
admin are the two different user categories that can
interact with the application. The user has two choices:
the PHQ-9 exam or an evaluation that consists of three
components-a questionnaire, a video, and an audio
detection, each weighted at 33% and used to determine
the user’s level of depression. The findings are also used
to suggest treatment alternatives. In order to combat the
condition sooner, computer vision and machine learning
havebeen employed to diagnose depression.
The majority of people deal with depression
on a daily basis, which is a prevalent and seriousmental
illness. Depression has an impact on a person's physical,
psychological, and mental health in addition to their
emotional state. In contrast to other illnesses, depression
cannot be diagnosed through laboratory testing, goes
unnoticed due to a lack of knowledge and awareness,
and can deteriorate to the point of suicide. Physicians
are currently using self-reported questionnaires and inperson interactions as part of their diagnostic process for
identifying depression. A psychiatricevaluation of social
interactions and human behaviour is required for the
diagnosis of depression. The patient's audio and video
recordings show how people with depression behave
differently than average people do. The user and the
admin are the two different user categories that can
interact with the application. The user has two choices:
the PHQ-9 exam or an evaluation that consists of three
components-a questionnaire, a video, and an audio
detection, each weighted at 33% and used to determine
the user’s level of depression. The findings are also used
to suggest treatment alternatives. In order to combat the
condition sooner, computer vision and machine learning
havebeen employed to diagnose depression.