Stress detection for visually impaired people using EEG signals based on extracted features from time-frequency domain
This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022.
| Κύριος συγγραφέας: | Sultana, Samia |
|---|---|
| Άλλοι συγγραφείς: | Parvez, Mohammad Zavid |
| Μορφή: | Thesis |
| Γλώσσα: | English |
| Έκδοση: |
Brac University
2023
|
| Θέματα: | |
| Διαθέσιμο Online: | http://hdl.handle.net/10361/17699 |
Παρόμοια τεκμήρια
-
Classi fication of motor imagery tasks based on BCI paradigm
ανά: Hossain, Nahid, κ.ά.
Έκδοση: (2019) -
Detection of mind wandering using EEG signals
ανά: Tasika, Nadia Jebin, κ.ά.
Έκδοση: (2020) -
Applying tDCS over the dominant Hemisphere to observe event-related Desynchronization
ανά: Khan, Akif Ahmed, κ.ά.
Έκδοση: (2020) -
DWT based transformed domain feature extraction approach for epileptic seizure detection
ανά: Mostafa, Mahajabin, κ.ά.
Έκδοση: (2021) -
Epileptic seizure detection by exploiting EEG signals using different decomposition techniques and machine learning approaches
ανά: Karim, Rezwanul, κ.ά.
Έκδοση: (2019)