A list of research publications. Two more articles are currently under redaction which will highlight work done in the context of my Master's thesis in Biological and Biomedical Engineering at McGill University. So, if you're into multimodal fusion of brain signals, large-scale whole-brain simulations and tensor factorization methods you may want to stay tuned for more! Also, feel free to reach out to discuss about science and research :)
Updated Feb. 11, 2021
DW Mann-Krzisnik and GD Mitsis., Modeling BOLD-fMRI Hemodynamics via Multidimensional Decomposition of Electrophysiology Data: A Simulation Study, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine Biology Society (EMBC), Montreal, QC, Canada, 2020, pp. 398-401
Abstract: We propose a framework for studying the electrophysiological correlates of BOLD-fMRI. This framework relies on structured coupled matrix-tensor factorization (sCMTF), a joint multidimensional decomposition which reveals dynamical interactions between LFP/EEG oscillatory features and BOLD-fMRI data. We test whether LFP/EEG-BOLD co-fluctuations and regional hemodynamic response functions can be estimated by sCMTF using whole-brain modelling of resting state activity. We produce permuted datasets to show that our framework extracts EEG/LFP temporal patterns that correlate significantly with BOLD signal fluctuations. Our framework is also capable of estimating HRFs that accurately embodies simulated hemodynamics, with a word of caution regarding initialization of the sCMTF algorithm.
M. Xiong et al., A Low-Cost, Semi-Autonomous Wheelchair Controlled by Motor Imagery and Jaw Muscle Activation, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Bari, Italy, 2019, pp. 2180-2185
Abstract: Wheelchairs controlled using electroencephalography (EEG) have been proposed to facilitate independent mobility for people with motor disabilities. To date, the majority of these systems have relied on distracting external stimuli such as flashing lights and expensive, medical-grade EEG amplifiers. We propose a wheelchair prototype that uses hand motor imagery (MI) and jaw clench data collected with a consumer-grade EEG system to generate left, right, forward, and stop commands. The signal is classified with logistic regression, and using only two scalp electrodes and a two-second window size, we obtained a mean subject accuracy of 60 ± 5% and a peak subject accuracy of 82 ± 3%. We introduce a novel control-flow paradigm relying on an intermediate control state, engaged by jaw clenching, to reduce the complexity of our classification problem, as well as real-time spectrograms for neurofeedback training. Additionally, we supplement our system with automated driving features, a location tracker, and a heart-rate monitor to increase usability and safety.
DW Mann-Krzisnik, F Verhaegen and SA Enger. The influence of tissue composition uncertainty on dose distributions in brachytherapy. Radiotherapy and Oncology, Volume 126, Issue 3, 2018, pp. 394 - 410
Abstract: Model-based dose calculation algorithms (MBDCAs) have evolved from serving as a research tool into clinical practice in brachytherapy. This study investigates primary sources of tissue elemental compositions used as input to MBDCAs and the impact of their variability on MBDCA-based dosimetry. Relevant studies were retrieved through PubMed. Minimum dose delivered to 90% of the target (D90), minimum dose delivered to the hottest specified volume for organs at risk (OAR) and mass energy-absorption coefficients (μen/ρ) generated by using EGSnrc "g" user-code were compared to assess the impact of compositional variability. Elemental composition for hydrogen, carbon, oxygen and nitrogen are derived from the gross contents of fats, proteins and carbohydrates for any given tissue, the compositions of which are taken from literature dating back to 1940-1950. Heavier elements are derived from studies performed in the 1950-1960. Variability in elemental composition impacts greatly D90 for target tissues and doses to OAR for brachytherapy with low energy sources and less for 192Ir-based brachytherapy. Discrepancies in μen/ρ are also indicative of dose differences. Updated elemental compositions are needed to optimize MBDCA-based dosimetry. Until then, tissue compositions based on gross simplifications in early studies will dominate the uncertainties in tissue heterogeneity.