Advanced driver assistance systems using EEG

Organisatsiooni nimi
Software Engineering and Information Systems
Establishing of a state of the art on use of brain signals for advanced driver assistance systems (ADAS), and devising such a system using EEG.

Context: Advanced driver assistance systems (ADAS) have been investigates by researchers and industry alike, for a variety of applications ranging from assisted breaking to drowsiness detection.

Details: The project aims to:
1.\tEstablish a state of the art for brain-signal based ADAS.
2.\tDevise an ADAS system using EEG brain signals for applications such as (but not limited to) drowsiness detection, alertness etc.

Some relevant literature:
[1] Adnan Shaout, Dominic Colella, S. Awad, “Advanced Driver Assistance Systems – Past, Present and Future” (
[2] Arun Sahayadhas, Kenneth Sundaraj and Murugappan Murugappan, “Detecting Driver Drowsiness Based on Sensors: A Review”, Journal: sensors, MDPI, 2012 ( )
[3] Jain, A.; Koppula, H.S.; Raghavan, B.; Soh, S.; Saxena, A., "Car that Knows Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models". In Proceedings of the IEEE International Conference on Computer Vision, Santiago, Chile, 13–16 December 2015.
[4] Yar M. Mughal, “A Parametric Framework for Modelling of Bioelectrical Signals”, Book, ISBN 978-981-287-969-1, Springer, 2015
[5] Ziebinski,Adam and Cupek,Rafal and Grzechca,Damian and Chruszczyk,Lukas, “Review of advanced driver assistance systems (ADAS)”, AIP Conference Proceedings, 2017.
Lõputöö kaitsmise aasta
Yar Muhammad
inglise keel
Nõuded kandideerijale
Bakalaureus, Magister
#ADAS, EEG, signal classification, machine learning

Kandideerimise kontakt

Yar Muhammad