Academic stress level detection using EEG signals: a thesis
Date of Publication
2013
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Electronics Engineering
Subject Categories
Electrical and Electronics
College
Gokongwei College of Engineering
Department/Unit
Electronics and Communications Engineering
Thesis Adviser
Engr. Roy Francis R. Navea
Defense Panel Chair
Eng. Voltaire Dupo
Defense Panel Member
Engr. Melvin K. Cabatuan
Engr. Mark Lorenz R. Torregoza
Abstract/Summary
Being stressed are common with the students. Being stressed at some point may be okay, but excessive level of stress can affect the student's performance in different ways. It can even provoke negative health problems to them. If the stress level of a student becomes too much, it may require the attention and supervision of their school teacher or parents for them to be able to handle their stress. It is hard to recognize by parents or teacher if a student is stressed or measure a student's stress level. Various studies have shown different ways to measure stress by means of EEG (electroencephalogram) devices.
To address this problem, the researchers have developed a system that can detect academic stress level of a student through eye blinks, self-reported emotions such as frustration, confusion and difficulty which are mainly related to stress. The entropy of the signal is also measured to add a feature in assessing the stress level. They selected an optimal electrode pair to represent eye blinks and implemented a modified algorithm for eye blinks detection for the system to automatically count the number of eye blinks in a given signal signal. To measure stress, the researchers identified the relationship of self-reports and entropy with eye blinks. The relationship between them is used to determine the stress level of a student. The system can help a student to cope with stress, by doing the necessary actions once their stress level of a certain task is known. By applying the actions needed on dealing with stress, a student can prevent the negative effects of stress.
Abstract Format
html
Language
English
Format
Accession Number
TU18393
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
xi, 87 leaves; illustrations (some colored); 28 cm. + 1 disc ; 4 3/4 in.
Keywords
Electroencephalography; Entropy; Infrared testing; STRESS (Computer program language); Thermoelastic stress analysis
Recommended Citation
Angulo, C. R., De Leon, J. T., & Go, S. M. (2013). Academic stress level detection using EEG signals: a thesis. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/7181