Nedime Karakullukcu, MSc, PhD
Postdoc
nedime.karakullukcu@lfmotol.cuni.cz
Experimental Neurophysiology Group
Department of Physiology, Second Faculty of Medicine, Charles University
Scientific background
I hold two bachelor’s degrees from Erciyes University in Kayseri, TURKEY: one in Biomedical Engineering (2016) and another in Mechatronic Engineering (2017). My academic journey has been enriched by interdisciplinary projects combining neurobiology, biomechanics, and advanced robotics, such as using EEG signals for real-time robotic control. I completed my PhD in Electrical and Computer Engineering at Abdullah Gül University in Kayseri, TURKEY, where I focused on neural signal analysis and motor imagery applications. The combination of this experiences is detailed on my dissertation ”Perception estimation and torque control for hand prostheses using EEG and EMG signals”.
My research has been featured in journals like IEEE Access and the International Journal of Neural Systems. Notable contributions include the development of Fourier-based synchrosqueezing transform methods for weight perception in motor imagery and movement intention detection in brain-computer interfaces. Additionally, I have been awarded The Scientific and Technological Research Council of Turkey (TÜBİTAK) scholarships and contributed to national research projects, including innovations in prosthetic technologies and human-robot interaction.
Research interests
Brain Computer Interface, Biomedical Signal Processing, Machine Learning, Deep Learning
Selected publications
N. Karakullukcu, F. Altindış and B. Yilmaz, “Object Weight Perception in Motor Imagery Using Fourier-Based Synchrosqueezing Transform and Regularized Common Spatial Patterns,” in IEEE ACCESS, vol. 12, pp. 52978-52989, 2024, doi: 10.1109/ACCESS.2024.3386554.
N. Karakullukcu & B. Yilmaz, “Detection of Movement Intention in EEG-Based
Brain-Computer Interfaces Using Fourier-Based Synchrosqueezing Transform”, in
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2022, 0129-0657, 32, 01, 15, doi:10.1142/S0129065721500593.