Electrical and Electronic Engineering - Research Publications
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ItemINFERRING PATIENT-SPECIFIC PHYSIOLOGICAL PARAMETERS FROM INTRACRANIAL EEG: APPLICATION TO CLINICAL DATA(WILEY-BLACKWELL, 2012-09-01)Purpose: Intracranial EEG (iEEG) provides information regarding where and when seizures occur, whilst the underlying mechanisms are hidden. However physiologically plausible mechanisms for seizure generation and termination are explained by neural mass models, which describe the macroscopic neural dynamics. Fusion of models with patient-specific data allows estimation and tracking of the normally hidden physiological parameters. By monitoring changes in physiology, a new understanding of seizures can be achieved. This work addresses model-data fusion for iEEG for application in a clinical setting. Method: Data was recorded from three patients undergoing evaluation for epilepsy-related surgery at St. Vincent's Hospital, Melbourne. Using this data, we created patient-specific neural mass mathematical models based on the formulation of Jansen and Rit (1995). The parameters that were estimated include the synaptic gains, time constants, and the firing threshold. The estimation algorithm utilized the Unscented Kalman Filter (Julier and Uhlmann, 1997). Result: We demonstrate how parameters changed in relation to seizure initiation, evolution and termination. We also show within-patient (across different seizures) and between-patient specificity of the parameter estimates. Conclusion: The fusion of clinical data and mathematical models can be used to infer valuable information about the underlying mechanisms of epileptic seizure generation. This information could be used to develop novel therapeutic strategies
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ItemINFERRING PATIENT-SPECIFIC PHYSIOLOGICAL PARAMETERS FROM INTRACRANIAL EEG: THEORETICAL STUDIES(WILEY-BLACKWELL, 2012-09)
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ItemIdentification of a Neural Mass Model of Burst Suppression(IEEE, 2019)Burst suppression includes alternating patterns of silent and fast spike activities in neuronal activities observable in micro to macro scale recordings. Biological models of burst suppression are given as dynamical systems with slow and fast states. The aim of this paper is to give a method to identify parameters of a mesoscopic model of burst suppression that can provide insights into study underlying generators of intracranial electroencephalogram (iEEG) data. An optimisation technique based upon a genetic algorithm (GA) is employed to find feasible model parameters to replicate burst patterns in the iEEG data with paroxysmal transitions. Then, a continuous discrete unscented Kalman filter (CD-UKF) is used to infer hidden states of the model and to enhance the identification results from the GA. The results show promise in finding the model parameters of a partially observed mesoscopic model of burst suppression.
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ItemLongwave Infrared Photoresponse in Copper 7, 7, 8, 8-tetracyano-2, 3, 5, 6-tetraflouroquinodimethane (CuTCNQF)(OSA & IEEE, 2021-06-01)The detection of light in the longwave infrared (LWIR) region is crucial for many applications such as environmental monitoring, thermal imaging and surveillance. Many commercial LWIR photodetectors involve complex fabrication processes, require cryogenic temperatures or exhibit slow photoresponse. Hence, there is a continuous pursuit of developing room-temperature, on-chip LWIR photodetectors, using simple fabrication processes [1]. Metal-organic charge transfer complexes typically have a narrow bandgap, which allows them to absorb LWIR wavelengths [2]. Here, we report room temperature LWIR photoresponse in one such charge transfer complex, ie. copper 7, 7, 8, 8-tetracyano-2, 3, 5, 6-tetraflouroquinodimethane (CuTCNQF 4 ), achieved via simple synthesis and fabrication processes.
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ItemMulticolor hologram based on plasmonic nanohole arrays and detour phase: design and simulation(IEEE, 2021)Multicolor holograms have numerous applications, including in art, data storage, security, and advanced displays. In recent years, there has been much interest concerning multicolor holograms based on metasurfaces [1]. Wen et al [2] demonstrated multicolor holograms using dielectric nanoparticles, with the nanoparticle size defining its resonant wavelength and its position defining its phase via the detour phase concept [3]. While this approach worked, it required good control over nanoparticle size and shape, achieved using inductively coupled reactive ion etching (ICP-RIE). This motivates the development of multicolor metasurface holograms that are also based on detour phase, but using other nanostructure types. Here we show that arrays of nanoholes in aluminum films enable the realization of multicolor holograms. We design nanohole arrays that serve as color (i.e. red/green/blue) filters with high transmission and low cross-talk. We then design two multicolor holograms based on these filters and simulate their performance, demonstrating that they show good fidelity to the desired holographic images. Our device is based on aluminum and silicon dioxide, giving it the advantage of CMOS compatibility.