REAL-TIME STRESS ASSESSMENT USING SLIDING WINDOW BASED CONVOLUTIONAL NEURAL NETWORK

NAQVI, SYED FARAZ (2021) REAL-TIME STRESS ASSESSMENT USING SLIDING WINDOW BASED CONVOLUTIONAL NEURAL NETWORK. Masters thesis, Universiti Teknologi PETRONAS.

[thumbnail of Syed Faraz Naqvi_17007464.pdf] PDF
Syed Faraz Naqvi_17007464.pdf
Restricted to Registered users only

Download (7MB)

Abstract

Mental stress has been identified as a significant cause of several bodily disorders, such
as depression, hypertension, neural and cardiovascular abnormalities. Early stress assessment
is critical in order to address and avoid further health abnormalities. Conventional
stress assessment methods, i.e. one-to-one interview sessions, questionnaires
and self-reporting, are highly subjective, tedious, and tend to lack accuracy. Therefore,
an automatic computer-aided diagnosis (CAD) method is required for accurate
and timely stress assessment. Machine-learning (ML)-based computer-aided diagnosis
systems can be used to assess the mental state with reasonable accuracy.

Item Type: Thesis (Masters)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE: Engineering > Electrical and Electronic
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 08 Sep 2021 10:09
Last Modified: 08 Sep 2021 10:09
URI: http://utpedia.utp.edu.my/id/eprint/20695

Actions (login required)

View Item
View Item