Sun, QiaoSutherland, GarnetteJiao, Shanlin2018-02-222018-02-222018-02http://hdl.handle.net/1880/106400Modeling of brain tissues is essential to better patient outcome. This research aims at modeling brain tissues based on their electrical impedance and viscoelasticity. Fractional order models can accurately model the two properties with few parameters in a wide spectral range. The Cole parameters extracted from step current response was applied to characterize the grey and white matter. Experimental results show that the Cole model fits well to experimental data and proposed Cole parameter extraction method is more effective in identifying Cole parameters. A fractional order viscoelastic model is employed to model the viscoelasticity of brain tissue. The predicted results are compared with the known experimental data and also that of integer order models, indicating the fractional order viscoelastic model can adequately fit all the experimental data with only two parameters.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Fractional CalculusCole impedance modelFractional order viscoelastic modelBrain tissueRobot-assisted neurosurgeryFractional order modelEducation--Tests and MeasurementsNeuroscienceComputer ScienceEngineering--BiomedicalEngineering--Electronics and ElectricalEngineering--MechanicalRoboticsPsychology--Experimentalmaster thesis10.11575/PRISM/5474