Analysis of Electroencephalographic Signals to Study the Behavior of Brain Frequencies for the Study of Academic Stress
- Resource Type
- Conference
- Authors
- Moyeenudin, H.M.; Hannah, S.; Anuradha, T.; Muthalagu, R.; Devi, V. Seedha; Anand, A. Jose
- Source
- 2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS) Automation, Computing and Renewable Systems (ICACRS), 2023 2nd International Conference on. :137-144 Dec, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Databases
Music
Electroencephalography
Behavioral sciences
Multiple signal classification
Task analysis
Stress
EEG (Electroencephalography)
Brain Frequencies
Academic Stress
Stress Response
Brainwave Patterns
- Language
The current study perform an analysis of electroencephalographic signals to study the behavior of brain frequencies in subjects who are under academic stress generated by a cognitive task, while listening to music or being silent. Creation of a corpus of more than 10 subjects under different sound stimuli is created. Characterization of brain signals are characterized for the identification of academic stress. Protocol is designed and brain signals are collected to observe the relationship between music listening and academic stress. EEG signal classifiers are used to identify differences between different sessions. Analysis of brain frequencies are analysed obtained in the sessions for each participant.