REAL-TIME STRESS ASSESSMENT USING SLIDING WINDOW BASED CONVOLUTIONAL NEURAL NETWORK
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,...
| Main Author: | NAQVI, SYED FARAZ |
|---|---|
| Format: | Thesis |
| Language: | English |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-utpedia.20695 / |
| Published: |
2021
|
| Subjects: | |
| Online Access: |
http://utpedia.utp.edu.my/20695/1/Syed%20Faraz%20Naqvi_17007464.pdf http://utpedia.utp.edu.my/20695/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: |
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. |
|---|