Drago Torkar

Research areas
  • Computer vision
  • Pattern recognition
  • Image processing
  • Machine vision

  • Projects
  • Distributed Artificial Intelligent Systems (2021-2024)
  • Computer structures and systems (2019-2024)
  • Intelligent Secure Trustable Things (2020-2023)
  • Supporting Active Ageing through Multimodal coaching (2017-2021)
  • Advanced recognition (2020)
  • Machine vision quality control of molded plastic parts (2019-2020)
  • Resource Efficient Food and dRink for the Entire Supply cHain (2015-2019)
  • iNet - The Impact of Net Height in Table Tennis (2017-2018)
  • Computer structures and systems (2015-2018)
  • Computer structures and systems (2009-2014)
  • Mobile application for food ingredients informing (2009-2010)
  • Development and implementation of a new PIM binder system using advanced methods (2008-2010)
  • The role of Luka Koper in logistic support of the Slovenian Armed Forces and allies (2006-2008)
  • Adaptive Robots for Flexible Manufacturing Systems (2005-2008)
  • Computing structures and systems (2004-2008)
  • Upgrade of light armoured wheeled vehicles VALUK 6x6 (2006-2007)
  • Vision interface for ABB robots (2006)
  • Secure data storage unit based on new ferroelectric semiconductor memory devices (2004-2006)
  • 2D and 3D digital map system for land, aerial and sea orientation (2004-2005)
  • Modeling rheological properties of ceramic-paraffine suspensions for low-pressure injection-moulding (2003-2004)
  • Computing structures and systems (1999-2003)
  • High performance evolutionary techniques in hardware-software codesign (1999-2001)
  • PEMCAS: personal monitor for capability supervision (1997-1998)
  • Architectural synthesis of computer systems with testability issues (1995-1998)
  • Publications
    Journal articles
  • Biomarkers of pre-existing risk of torsade de pointes under Sotalol treatment, J. ELECTROCARDIOL. (2020)
  • Dynamic features of cardiac vector as alternative markers of drug-induced spatial dispersion, J PHARMACOL TOX MET (2020)

  •  
    Dynamic features of cardiac vector as alternative markers of drug-induced spatial dispersion[X]
    • P.D. Cruces, D. Torkar, P. Arini
    • Journal of Pharmacological and Toxicological Methods, 2020, Vol. , No.
      pages:
    • abstract:
      The abnormal amplification of ventricular repolarization dispersion (VRD) has long been linked to proarrhythmia risk. Recently, the measure of VRD through electrocardiogram intervals has been strongly questioned. The search for an efficient and non-invasive surrogate marker of drug-induced dispersion effects constitute an urgent research challenge. Herein, drug-induced ventricular dispersion is generated by d-Sotalol supply in an In-vitro rabbit heart model. A cilindrical chamber simulates the thorax and a multi-electrode net is used to obtain spatial electrocardiographic signals. Cardiac vector dynamics is captured by novel velocity cardiomarkers obtained by quaternion methods. Through statistical analysis and machine learning technics, we compute potential dispersion markers that could define proarrhythmic risk. The cardiomarkers with the greatest statistical significance, both obtained from the electrical cardiac vector, were: the QTω, which is the difference between first and last maxima of angular velocity and λ21vT, the roundness of linear velocity. When comparing with the performance of the current standards (89%), this pair was able to correctly separate 21 out of 22 experiments achieving a performance of 95%. Moreover, the QTω computes in a much more robust basis the QT interval, the current index for drug regulation. These velocity markers circumvent the problems of accuratelly finding the fiducial points such as the always tricky T-wave end. Given the high performance they achieved, it is provided a promising outcome for future applications to the detection of anomalous changes of heterogeneity that may be useful for the purposes of torsadogenic toxicity studies.

  • Knee stiffness and viscosity of human cadaver - Wartenberg test, BJBMS (2017)
  • Cell counting tool parameters optimization approach for electroporation efficiency determination of attached cells in phase contrast images, J.Microsc. (2011)
  • Identification of radon anomalies in soil gas using decision trees and neural networks, Nukleonika (2010)
  • Application of artificial neural networks in simulating radon levels in soil gas, ChemGe (2010)
  • Visual control of an industrial robot manipulator: Accuracy Estimation, Stroj. vestn. (2009)
  • Robot Vision Accuracy Estimation, Elektroteh. vest. (2009)
  • Apparent viscosity prediction of alumina-paraffin suspensions using artificial neural networks, J. mater. process. technol. (2008)
  • Evaluation of accuracy in a 3D reconstruction system, WSEAS Trans. Syst. Control (2007)
  • Control of a robotic manipulator by visual and speech information, Eng. rev. (2002)
  • An uncalibrated robot system for reaching and grasping objects in unpredictable physical environment, J. Electr. Eng. (2001)
  • GPS positioning and digital map processing in 2D and 3D terrain environment, J. Comput. Inf. Technol. (1994)
  • Computer processing of hard-copy maps and their application in satelite positioning, J. Commun. (1994)
  • Reflection on light distribution measurement, Sens. Rev. (1992)
  • Conference papers
  • Food Waste Ontology: A Formal Description of Knowledge from the Domain of Food Waste, BFNDMA 2019 at IEEE BigData 2019
  • Analysis of an Electrocardiographic Multilead System using Artificial Neural Networks - A Study of the Dispersion during Premature Ventricular Stimulation, Biosignals 2016
  • Accuracy of a 3D reconstruction system, ISPRA 2007
  • Robot TCP positioning with vision : accuracy estimation of a robot visual control system, ICINCO 2007
  • Estimation of accuracy for robot vision control, SHR2007
  • Radon in soil gas : application of neuron networks to identify anomalies caused by earthquakes, Hazards 2006
  • Dynamic viscosity prediction of alumina-paraffin suspensions using artificial neural networks, AERC 2005
  • The use of numerical simulation for the study of low-pressure injection moulding of alumina-paraffin suspensions, AERC 2003
  • Books & Chapters in Books
  • Optimal lead selection for evaluation ventricular premature beats using machine learning approach, (2017)
  • Radon as Earthquake Precursor - Methods for Detecting Anomalies, InTech - Open Access Publisher (2011)