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