Back
  1. Home
  2. Profile of Pouyan Ebrahimbabaie Varnosfaderani (ULiège)
Profil

Ebrahimbabaie Varnosfaderani Pouyan

See author's contact details
Main Referenced Co-authors
Verly, Jacques  (18)
Kermi, Sofia (2)
Agnello, Armélinda  (1)
Bertrand, François  (1)
Charlier, Robert  (1)
Main Referenced Keywords
GBM (5); Driving (4); Drowsiness (3); Geometric Brownian motion (3); Sleep (3);
Main Referenced Unit & Research Centers
Laboratory for Signal and Image Exploitation (INTELSIG), Department of Electrical Engineering and Computer Science, University of Liège, Liège, Belgium (2)
IFRES (1)
Laboratory for Signal and Image Exploitation (INTELSIG), Department of Electrical Engineering and Computer Science, University of Liège (1)
Main Referenced Disciplines
Electrical & electronics engineering (17)
Engineering, computing & technology: Multidisciplinary, general & others (4)
Education & instruction (1)

Publications (total 22)

The most downloaded
171 downloads
Ebrahimbabaie Varnosfaderani, P., & Verly, J. (11 October 2017). Prediction of level of drowsiness using an adaptive Geometric Brownian Motion model, with application to drowsy driving accident prevention [Paper presentation]. A Joint Congress of Association of Sleep Medicine and World Sleep Federation (World Sleep), Prague, Czechia. https://hdl.handle.net/2268/214720

The most cited

1 citations (Scopus®)

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (2018). Excellent Potential of Geometric Brownian Motion (GBM) as a Random Process Model for Level of Drowsiness Signals. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies. SciTePress. doi:10.5220/0006545101050112 https://hdl.handle.net/2268/220320

Ebrahimbabaie Varnosfaderani, P. (2021). Drowsiness: modeling, prediction, and early detection systems. Amazon (Kindle Direct Publishing).

Ebrahimbabaie Varnosfaderani, P. (2020). Prediction of risk of an event using sensor signals, with application to the prevention of driving accidents due to drowsiness [Doctoral thesis, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/250646

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (2020). Real time prediction device. Japan: Japan Patent Office.

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (2020). A real time prediction device. Australia: Australian Government: IP Australia.

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (2018). Excellent Potential of Geometric Brownian Motion (GBM) as a Random Process Model for Level of Drowsiness Signals. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies. SciTePress. doi:10.5220/0006545101050112
Peer reviewed

Kermi, S., Ebrahimbabaie Varnosfaderani, P., & Verly, J. (December 2017). Preliminary investigation of the applicability of Geometric Brownian motion (GBM) to model the evolution with time of the level of drowsiness of narcoleptic subjects. Sleep Medicine, 40 (1), 156. doi:10.1016/j.sleep.2017.11.457
Peer Reviewed verified by ORBi

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (01 December 2017). Geometric Brownian Motion (GBM) as a promising random process model of the time evolution of the level of drowsiness [Poster presentation]. Annual Meeting of the IEEE-EMBS Benelux Chapter, jointly with 16th Belgian National Day on Biomedical Engineering, Brussels, Belgium.

Ebrahimbabaie Varnosfaderani, P., Kermi, S., & Verly, J. (01 December 2017). Effectiveness of Geometric Brownian Motion (GBM) random process model for modelling the PERCLOS signals of narcoleptic subjects [Poster presentation]. Annual Meeting of the IEEE-EMBS Benelux Chapter, jointly with 16th Belgian National Day on Biomedical Engineering, Brussels, Belgium.

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (2017). Prediction of level of drowsiness using an adaptive Geometric Brownian motion model, with application to drowsy driving accident prevention. Sleep Medicine. doi:10.1016/j.sleep.2017.11.247
Peer Reviewed verified by ORBi

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (December 2017). Geometric Brownian motion (GBM) random process model appears to be an excellent choice for modeling realizations of PERCLOS signals. Sleep Medicine, 40 (1), 86. doi:10.1016/j.sleep.2017.11.246
Peer Reviewed verified by ORBi

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (30 November 2017). Geometric Brownian Motion (GBM) as a promising random process model of the time evolution of the level of drowsiness [Paper presentation]. Annual Meeting of the IEEE-EMBS Benelux Chapter, jointly with 16th Belgian National Day on Biomedical Engineering, Brussels, Belgium.

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (11 October 2017). Geometric Brownian Motion (GBM) random process model appears to be an excellent choice for modeling realizations of PERCLOS signals [Poster presentation]. A Joint Congress of Association of Sleep Medicine and World Sleep Federation (World Sleep), Prague, Czechia.

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (11 October 2017). Prediction of level of drowsiness using an adaptive Geometric Brownian Motion model, with application to drowsy driving accident prevention [Paper presentation]. A Joint Congress of Association of Sleep Medicine and World Sleep Federation (World Sleep), Prague, Czechia.

Kermi, S., Ebrahimbabaie Varnosfaderani, P., & Verly, J. (10 October 2017). Preliminary investigation of the applicability of Geometric Brownian Motion (GBM) to model the evolution with time of the level of drowsiness of narcoleptic subjects [Poster presentation]. A Joint Congress of Association of Sleep Medicine and World Sleep Federation (World Sleep), Prague, Czechia.

Verpoorten, D., Devyver, J., Duchâteau, D., Mihaylov, B., Agnello, A., Ebrahimbabaie Varnosfaderani, P., Focant, J.-F., Charlier, R., Delfosse, A., Bertrand, F., Megherbi, S., & Detroz, P. (2017). Decoding the disciplines – A pilot study at the University of Liège (Belgium). In R. Andersson, K. Martensson, ... T. Roxa, Proceedings of the 2nd EuroSoTL Conference - Transforming patterns through the scholarship of teaching and learning (pp. 263-267). Lund, Sweden: Lund University Press.
Peer reviewed

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (22 March 2017). Discovery that a person's level of drowsiness appears to evolve in time according to a Geometric Brownian Motion (GBM) random process model [Paper presentation]. 10th International Conference on Managing Fatigue, San Diego, CA, United States.

Verly, J., & Ebrahimbabaie Varnosfaderani, P. (2017). A real time prediction device. World International Property Organization (WIPO).

Verly, J., & Ebrahimbabaie Varnosfaderani, P. (2017). A prediction device. European Patent Office.

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (February 2016). Prediction of future values of the eye PERCLOS based on its past values, with application to drowsiness monitoring [Paper presentation]. International Symposium on Somnolence, Vigilance, and Safety (SomnoSafe), Brussels, Belgium.

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (February 2016). Prediction of future values of a level of drowsiness derived from images of an eye based on its past values, with application to drowsy driving [Paper presentation]. International Symposium on Somnolence, Vigilance, and Safety (SomnoSafe), Brussels, Belgium.

Ebrahimbabaie Varnosfaderani, P., & Verly, J. (27 November 2015). Random process modeling of an optooculography-based level of drowsiness, with application to drowsy driving [Poster presentation]. The Joint Meeting of the IEEE-EMBS Benelux Chapter and the 14th Belgian National Day on Biomedical Engineering.

Ebrahimbabaie Varnosfaderani, P. (2014). Sensitivity Analysis in the Electromagnetic Modeling of Human Tissues [Master’s dissertation, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/241097

Contact ORBi