Peng Wen - Academia.edu (original) (raw)

Papers by Peng Wen

Brain Informatics, 2019

This numerical study pre-validated the impact of lateral head orientations on the current distrib... more This numerical study pre-validated the impact of lateral head orientations on the current distributions in the brain region during transcranial direct current stimulation (tDCS). A four-layer (scalp, skull, CSF, brain) real shape human head model was constructed with two electrodes configurations (C3-C4, C3-Fp2) and incremental downward displacement (0.5 mm) of the brain due to gravitational force. Sensitivity analysis was conducted on the influence of brain displacement during tDCS. Results of this preliminary study demonstrated that the cerebral current distribution was sensitive to the gravity-induced downward movement of the brain during tDCS, which suggested that lateral head orientations could be a new parameter to consider during tDCS and further research resources could be allocated in the realistic human head based studies to follow up this study. This finding should help both tDCS research and clinical trials to predict the stimulation result more precisely.

This paper reports a new method to identify the ADHD children using EEG signals and effective con... more This paper reports a new method to identify the ADHD children using EEG signals and effective connectivity techniques. In this study, the original EEG data is pre-filtered and divided into Delta, Theta, Alpha and Beta bands. And then, the effective connectivity graphs are constructed by applying independent component analysis, multivariate regression model and phase slope index. The measures of clustering coefficient, nodal efficiency and degree centrality in graph theory are used to extract features from these graphs. Statistical analysis based on the standard error of the mean are employed to evaluate the graph theory measures in each frequency band. The results show a decreased average clustering coefficient in delta band for ADHD subjects. Also, in delta band, the ADHD subjects have increased nodal efficiency and degree centrality in left forehead part and decreased in forehead middle.

Frontiers in Neuroinformatics, 2019

K-complexes identification is a challenging task in sleep research. The detection of k-complexes ... more K-complexes identification is a challenging task in sleep research. The detection of k-complexes in electroencephalogram (EEG) signals based on visual inspection is time consuming, prone to errors, and requires well-trained knowledge. Many existing methods for k-complexes detection rely mainly on analyzing EEG signals in time and frequency domains. In this study, an efficient method is proposed to detect k-complexes from EEG signals based on fractal dimension (FD) of time frequency (T-F) images coupled with undirected graph features. Firstly, an EEG signal is partitioned into smaller segments using a sliding window technique. Each EEG segment is passed through a spectrogram of short time Fourier transform (STFT) to obtain the T-F images. Secondly, the box counting method is applied to each T-F image to discover the FDs in EEG signals. A vector of FD features are extracted from each T-F image and then mapped into an undirected graph. The structural properties of the graphs are used as the representative features of the original EEG signals for the input of a least square support vector machine (LS-SVM) classifier. Key graphic features are extracted from the undirected graphs. The extracted graph features are forwarded to the LS-SVM for classification. To investigate the classification ability of the proposed feature extraction combined with the LS-SVM classifier, the extracted features are also forwarded to a k-means classifier for comparison. The proposed method is compared with several existing k-complexes detection methods in which the same datasets were used. The findings of this study shows that the proposed method yields better classification results than other existing methods in the literature. An average accuracy of 97% for the detection of the k-complexes is obtained using the proposed method. The proposed method could lead to an efficient tool for the scoring of automatic sleep stages which could be useful for doctors and neurologists in the diagnosis and treatment of sleep disorders and for sleep research.

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, Aug 1, 2016

A realistic human head model consisting of six tissue layers was modelled to investigate the beha... more A realistic human head model consisting of six tissue layers was modelled to investigate the behavior of temperature profile and magnitude when applying electroconvulsive therapy stimulation and different biological properties. The thermo-electrical model was constructed with the use of bio-heat transfer equation and Laplace equation. Three different electrode montages were analyzed as well as the influence of blood perfusion, metabolic heat and electric and thermal conductivity in the scalp. Also, the effect of including the fat layer was investigated. The results showed that temperature increase is inversely proportional to electrical and thermal conductivity increase. Furthermore, the inclusion of blood perfusion slightly drops the peak temperature. Finally, the inclusion of fat is highly recommended in order to acquire more realistic results from the thermo-electrical models.

IEEE Transactions on Biomedical Engineering, 2016

This study constructed a series of high resolution realistic human head models with brain tumors ... more This study constructed a series of high resolution realistic human head models with brain tumors and numerically investigated the influence of brain tumor's location and grade on the current distributions under different electrode montages during tDCS. The threshold area and the peak current density were also derived and analyzed in the region of interest. The simulation result showed that it is safe to apply tDCS on the patients with brain tumors to treat their neuropsychiatric conditions and cancer pain caused by the tumor, though considerable changes of the current distributions are induced by the present of a brain tumor. In addition, several observations on the global and local influences of tumor grade and possible edema have been made as well. These findings should be helpful for researchers and clinical doctors to treat patients with brain tumors. This study is also the first numerical study to fill in the gap of tDCS applications on the patients with brain tumors.

Brain Informatics, 2018

Transcranial Doppler ultrasound (TCD) is a non-invasive ultrasound method used to examine blood c... more Transcranial Doppler ultrasound (TCD) is a non-invasive ultrasound method used to examine blood circulation within the brain. During TCD, ultrasound waves are transmitted through the tissues including skull. These sound waves reflect off blood cells moving within the blood vessels, allowing the radiologist to interpret their speed and direction. In this paper, an auto TCD probe is developed to control the 2D deflection angles of the probe. The techniques of Magnetic Resonance Angiography (MRA) and Magnetic Resource Imagine (MRI) have been used to build the 3D human head model and generate the structure of cerebral arteries. The K-Nearest Neighbors (KNN) algorithm as a non-parametric method has been used for signal classification and regression of corresponding arteries. Finally, a global search and local search algorithms are used to locate the ultrasound focal zone and obtain a stronger signal efficient and more accurate result.

Australian Journal of Electrical and Electronics Engineering, 2009

Abstract Traffic surveying systems using pneumatic road sensors are currently widely used in Aust... more Abstract Traffic surveying systems using pneumatic road sensors are currently widely used in Australia for counting and classifying vehicles. However, these intrusive sensors disrupt traffic and expose technicians to significant road dangers. We propose a non-intrusive automated vehicle classification system for the AUSTROADS classification standard based upon laser sensor technology. The proposed system is capable of classifying vehicles in multi-lane, high-speed environments. Conventional Fourier-based denoising techniques are, however, unable to meet the design challenge due to a considerable amount of noise presented in measurement data that is induced by both the laser sensing device and high volume traffic in carriageways. This paper proposes an advanced wavelet-based denoising technique to greatly enhance the noise reduction performance of the proposed automated vehicle classification system.

IEEE/ICME International Conference on Complex Medical Engineering, 2010

ABSTRACT Rough Set theory is an effective tool to deal with vagueness and uncertainty information... more ABSTRACT Rough Set theory is an effective tool to deal with vagueness and uncertainty information to select the most relevant attributes for a decision system. However, to find the minimum attributes is a NP-hard problem. In this paper, we describe a method to decrease the scale of the problem by filtering core attributes, and then employ the checking tree to test the rest attributes from bottom to top by using peer-to-peer technique. Furthermore, we utilize pruning method to enhance the speed and discard the node when one of its child node superset of certain attribute reduction found before. Experimental results show that our parallel algorithm has the high speed-up ratio while the attribute reductions are distributed in the bottom of the tree. In a peer-to-peer network, our algorithm will amortize the required memory on client computers. Accordingly, this algorithm can be applied to deal with larger data set in a distributed environment.

Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. No.99CH37015)

Two issues relating to the modelling of human heads are addressed in this paper. First, the elect... more Two issues relating to the modelling of human heads are addressed in this paper. First, the electrical properties of head tissues are studied. The inhomogeneity inherited in each tissue, which has so far been ignored in the literature, is discussed. A head model comprising tissue inhomogeneity is constructed using the so-called pseudo conductivity method. Second, in order to study the relationship between the model and the computed solution, a set of simulations are carried out based on the above model. The result shows that there is no significant difference in the statistic parameters between models that are constructed using a variety of pseudo conductivity assignments based on a common normal distribution function. This observation is promising as it means that it is not necessary to find out the exact head model from the statistic aspect in EEG forward computation.

IEEE EMBS Asian-Pacific Conference on Biomedical Engineering, 2003.

Absrracr-The paper suggested a new method in human head modelling by directly considering and stu... more Absrracr-The paper suggested a new method in human head modelling by directly considering and studying the head as a inhomogeneous subject consisting o f many small homogeneous meshes. Therefore the inherent head tissue inhomogeneity which is widely ignored in lhe existing models is included. An approach is deriwd to handle the resulting complexity. The simulation results have shown promising applications in EEG.

Australasian physical & engineering sciences in medicine / supported by the Australasian College of Physical Scientists in Medicine and the Australasian Association of Physical Sciences in Medicine, Jan 5, 2016

The alcoholism can be detected by analyzing electroencephalogram (EEG) signals. However, analyzin... more The alcoholism can be detected by analyzing electroencephalogram (EEG) signals. However, analyzing multi-channel EEG signals is a challenging task, which often requires complicated calculations and long execution time. This paper proposes three data selection methods to extract representative data from the EEG signals of alcoholics. The methods are the principal component analysis based on graph entropy (PCA-GE), the channel selection based on graph entropy (GE) difference, and the mathematic combinations channel selection, respectively. For comparison purposes, the selected data from the three methods are then classified by three classifiers: the J48 decision tree, the K-nearest neighbor and the Kstar, separately. The experimental results show that the proposed methods are successful in selecting data without compromising the classification accuracy in discriminating the EEG signals from alcoholics and non-alcoholics. Among them, the proposed PCA-GE method uses only 29.69 % of the ...

IET Science, Measurement & Technology, 2012

An anatomically accurate high-resolution finite-element head model and its derivatives have been ... more An anatomically accurate high-resolution finite-element head model and its derivatives have been employed to examine the influence of subcutaneous fat and muscle tissues on cortical modulation. The effects of skull, muscle and white matter (WM) directional conductivity have also been investigated. Results indicate that the inclusion of additional tissues in the head model have a profound effect on the magnitude and distribution pattern of induced current density. Similarly, anisotropic tissue conductivity caused a significant deterioration in spatial focality of cortical currents along with a more distorted and diffused distribution pattern across the cortex.

2007 IEEE International Conference on Integration Technology, 2007

In this study, two methods, Auditory Evoked Potential (AEP) and bispectrum, based on EEG signal p... more In this study, two methods, Auditory Evoked Potential (AEP) and bispectrum, based on EEG signal processing are employed in monitoring depth of anaesthesia. Auditory evoked potential is obtained using wavelet analysis in order to achieve a fast extraction. Both AEP and bispectrum methods show good relativity with the depth of anaesthesia. Besides, both methods are integrated in a software developed on a personal computer to help those non-specialists to apply the results easily.

Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics

Rough Sets and Knowledge Technology

HKIE Transactions

Australia’s recent mining boom has mainly been created by China’s need for minerals. A large numb... more Australia’s recent mining boom has mainly been created by China’s need for minerals. A large number of migrant engineers move to Australia from China, Australia’s largest trading partner, if China’s Special Administration Region, Hong Kong is taken into account. Education is Australia’s third largest export and China is the largest source of Australian international students (the number in 2008 was 12,770). Higher education including engineering education is an important source of income to Australians. On account of the above ground, international students from China, particularly engineering ones, are important to Australia. It can be argued that comparing and contrasting engineering education in China and Australia is critical in determining the extent that engineers from China can help reduce the skill shortages in the engineering workforce in Australia.

Journal of Advanced Computational Intelligence and Intelligent Informatics

EEG-based applications have faced the challenge of multi-modal integrated analysis problems. In t... more EEG-based applications have faced the challenge of multi-modal integrated analysis problems. In this paper, a greedy maximal weight matching approach is used to measure the functional connectivity in alcoholics datasets with EEG and EOG signals. The major discovery is that the processing of the repeated and unrepeated stimuli in the γ band in control drinkers is significantly more different than that in alcoholic subjects. However, the EOGs are always stable in the case of visual tasks, except for a weakly wave when subjects make an error response to the stimuli.

Computer methods and programs in biomedicine, 2016

This paper focuses on electroconvulsive therapy (ECT) and head models to investigate temperature ... more This paper focuses on electroconvulsive therapy (ECT) and head models to investigate temperature profiles arising when anisotropic thermal and electrical conductivities are considered in the skull layer. The aim was to numerically investigate the threshold for which this therapy operates safely to the brain, from the thermal point of view. A six-layer spherical head model consisting of scalp, fat, skull, cerebro-spinal fluid, grey matter and white matter was developed. Later on, a realistic human head model was also implemented. These models were built up using the packages from COMSOL Inc. and Simpleware Ltd. In these models, three of the most common electrode montages used in ECT were applied. Anisotropic conductivities were derived using volume constraint and included in both spherical and realistic head models. The bio-heat transferring problem governed by Laplace equation was solved numerically. The results show that both the tensor eigenvalues of electrical conductivity and th...

Australasian Physical & Engineering Sciences in Medicine, 2016

This paper presents a new method to apply timing characteristics of electroencephalograph (EEG) b... more This paper presents a new method to apply timing characteristics of electroencephalograph (EEG) beta frequency bands to assess the depth of anaesthesia (DoA). Firstly, the measured EEG signals are denoised and decomposed into 20 different frequency bands. The Mobility (M), permutation entropy (PE) and Lempel-Ziv complexity (LCZ) of each frequency band are calculated. The M, PE and LCZ values of beta frequency bands (21.5-30 Hz) are selected to derive a new index. The new index is evaluated and compared with measured bispectral (BIS). The results show that there is a very close correlation between the proposed index and the BIS during different anaesthetic states. The new index also shows a 25-264 s earlier time response than BIS during the transient period of anaesthetic states. In addition, the proposed index is able to continuously assess the DoA when the quality of signal is poor and the BIS does not have any valid outputs.

The demand for non-invasive vehicle counting and classifying devices has grown significantly in p... more The demand for non-invasive vehicle counting and classifying devices has grown significantly in past decades due to contributing factors from occupational health and safety standards developed by state road authorities. In this paper, we present an automated vehicle classification system based upon the laser sensor technology. The system is capable of classifying vehicles in multi-lane, high speed environments, and requires no apparatus be placed on the carriageway. As opposed to the conventional Fourier-based filtering method, this paper also proposes a novel wavelet-based noise reduction technique to enhance performance.

Brain Informatics, 2019

This numerical study pre-validated the impact of lateral head orientations on the current distrib... more This numerical study pre-validated the impact of lateral head orientations on the current distributions in the brain region during transcranial direct current stimulation (tDCS). A four-layer (scalp, skull, CSF, brain) real shape human head model was constructed with two electrodes configurations (C3-C4, C3-Fp2) and incremental downward displacement (0.5 mm) of the brain due to gravitational force. Sensitivity analysis was conducted on the influence of brain displacement during tDCS. Results of this preliminary study demonstrated that the cerebral current distribution was sensitive to the gravity-induced downward movement of the brain during tDCS, which suggested that lateral head orientations could be a new parameter to consider during tDCS and further research resources could be allocated in the realistic human head based studies to follow up this study. This finding should help both tDCS research and clinical trials to predict the stimulation result more precisely.

This paper reports a new method to identify the ADHD children using EEG signals and effective con... more This paper reports a new method to identify the ADHD children using EEG signals and effective connectivity techniques. In this study, the original EEG data is pre-filtered and divided into Delta, Theta, Alpha and Beta bands. And then, the effective connectivity graphs are constructed by applying independent component analysis, multivariate regression model and phase slope index. The measures of clustering coefficient, nodal efficiency and degree centrality in graph theory are used to extract features from these graphs. Statistical analysis based on the standard error of the mean are employed to evaluate the graph theory measures in each frequency band. The results show a decreased average clustering coefficient in delta band for ADHD subjects. Also, in delta band, the ADHD subjects have increased nodal efficiency and degree centrality in left forehead part and decreased in forehead middle.

Frontiers in Neuroinformatics, 2019

K-complexes identification is a challenging task in sleep research. The detection of k-complexes ... more K-complexes identification is a challenging task in sleep research. The detection of k-complexes in electroencephalogram (EEG) signals based on visual inspection is time consuming, prone to errors, and requires well-trained knowledge. Many existing methods for k-complexes detection rely mainly on analyzing EEG signals in time and frequency domains. In this study, an efficient method is proposed to detect k-complexes from EEG signals based on fractal dimension (FD) of time frequency (T-F) images coupled with undirected graph features. Firstly, an EEG signal is partitioned into smaller segments using a sliding window technique. Each EEG segment is passed through a spectrogram of short time Fourier transform (STFT) to obtain the T-F images. Secondly, the box counting method is applied to each T-F image to discover the FDs in EEG signals. A vector of FD features are extracted from each T-F image and then mapped into an undirected graph. The structural properties of the graphs are used as the representative features of the original EEG signals for the input of a least square support vector machine (LS-SVM) classifier. Key graphic features are extracted from the undirected graphs. The extracted graph features are forwarded to the LS-SVM for classification. To investigate the classification ability of the proposed feature extraction combined with the LS-SVM classifier, the extracted features are also forwarded to a k-means classifier for comparison. The proposed method is compared with several existing k-complexes detection methods in which the same datasets were used. The findings of this study shows that the proposed method yields better classification results than other existing methods in the literature. An average accuracy of 97% for the detection of the k-complexes is obtained using the proposed method. The proposed method could lead to an efficient tool for the scoring of automatic sleep stages which could be useful for doctors and neurologists in the diagnosis and treatment of sleep disorders and for sleep research.

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, Aug 1, 2016

A realistic human head model consisting of six tissue layers was modelled to investigate the beha... more A realistic human head model consisting of six tissue layers was modelled to investigate the behavior of temperature profile and magnitude when applying electroconvulsive therapy stimulation and different biological properties. The thermo-electrical model was constructed with the use of bio-heat transfer equation and Laplace equation. Three different electrode montages were analyzed as well as the influence of blood perfusion, metabolic heat and electric and thermal conductivity in the scalp. Also, the effect of including the fat layer was investigated. The results showed that temperature increase is inversely proportional to electrical and thermal conductivity increase. Furthermore, the inclusion of blood perfusion slightly drops the peak temperature. Finally, the inclusion of fat is highly recommended in order to acquire more realistic results from the thermo-electrical models.

IEEE Transactions on Biomedical Engineering, 2016

This study constructed a series of high resolution realistic human head models with brain tumors ... more This study constructed a series of high resolution realistic human head models with brain tumors and numerically investigated the influence of brain tumor's location and grade on the current distributions under different electrode montages during tDCS. The threshold area and the peak current density were also derived and analyzed in the region of interest. The simulation result showed that it is safe to apply tDCS on the patients with brain tumors to treat their neuropsychiatric conditions and cancer pain caused by the tumor, though considerable changes of the current distributions are induced by the present of a brain tumor. In addition, several observations on the global and local influences of tumor grade and possible edema have been made as well. These findings should be helpful for researchers and clinical doctors to treat patients with brain tumors. This study is also the first numerical study to fill in the gap of tDCS applications on the patients with brain tumors.

Brain Informatics, 2018

Transcranial Doppler ultrasound (TCD) is a non-invasive ultrasound method used to examine blood c... more Transcranial Doppler ultrasound (TCD) is a non-invasive ultrasound method used to examine blood circulation within the brain. During TCD, ultrasound waves are transmitted through the tissues including skull. These sound waves reflect off blood cells moving within the blood vessels, allowing the radiologist to interpret their speed and direction. In this paper, an auto TCD probe is developed to control the 2D deflection angles of the probe. The techniques of Magnetic Resonance Angiography (MRA) and Magnetic Resource Imagine (MRI) have been used to build the 3D human head model and generate the structure of cerebral arteries. The K-Nearest Neighbors (KNN) algorithm as a non-parametric method has been used for signal classification and regression of corresponding arteries. Finally, a global search and local search algorithms are used to locate the ultrasound focal zone and obtain a stronger signal efficient and more accurate result.

Australian Journal of Electrical and Electronics Engineering, 2009

Abstract Traffic surveying systems using pneumatic road sensors are currently widely used in Aust... more Abstract Traffic surveying systems using pneumatic road sensors are currently widely used in Australia for counting and classifying vehicles. However, these intrusive sensors disrupt traffic and expose technicians to significant road dangers. We propose a non-intrusive automated vehicle classification system for the AUSTROADS classification standard based upon laser sensor technology. The proposed system is capable of classifying vehicles in multi-lane, high-speed environments. Conventional Fourier-based denoising techniques are, however, unable to meet the design challenge due to a considerable amount of noise presented in measurement data that is induced by both the laser sensing device and high volume traffic in carriageways. This paper proposes an advanced wavelet-based denoising technique to greatly enhance the noise reduction performance of the proposed automated vehicle classification system.

IEEE/ICME International Conference on Complex Medical Engineering, 2010

ABSTRACT Rough Set theory is an effective tool to deal with vagueness and uncertainty information... more ABSTRACT Rough Set theory is an effective tool to deal with vagueness and uncertainty information to select the most relevant attributes for a decision system. However, to find the minimum attributes is a NP-hard problem. In this paper, we describe a method to decrease the scale of the problem by filtering core attributes, and then employ the checking tree to test the rest attributes from bottom to top by using peer-to-peer technique. Furthermore, we utilize pruning method to enhance the speed and discard the node when one of its child node superset of certain attribute reduction found before. Experimental results show that our parallel algorithm has the high speed-up ratio while the attribute reductions are distributed in the bottom of the tree. In a peer-to-peer network, our algorithm will amortize the required memory on client computers. Accordingly, this algorithm can be applied to deal with larger data set in a distributed environment.

Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. No.99CH37015)

Two issues relating to the modelling of human heads are addressed in this paper. First, the elect... more Two issues relating to the modelling of human heads are addressed in this paper. First, the electrical properties of head tissues are studied. The inhomogeneity inherited in each tissue, which has so far been ignored in the literature, is discussed. A head model comprising tissue inhomogeneity is constructed using the so-called pseudo conductivity method. Second, in order to study the relationship between the model and the computed solution, a set of simulations are carried out based on the above model. The result shows that there is no significant difference in the statistic parameters between models that are constructed using a variety of pseudo conductivity assignments based on a common normal distribution function. This observation is promising as it means that it is not necessary to find out the exact head model from the statistic aspect in EEG forward computation.

IEEE EMBS Asian-Pacific Conference on Biomedical Engineering, 2003.

Absrracr-The paper suggested a new method in human head modelling by directly considering and stu... more Absrracr-The paper suggested a new method in human head modelling by directly considering and studying the head as a inhomogeneous subject consisting o f many small homogeneous meshes. Therefore the inherent head tissue inhomogeneity which is widely ignored in lhe existing models is included. An approach is deriwd to handle the resulting complexity. The simulation results have shown promising applications in EEG.

Australasian physical & engineering sciences in medicine / supported by the Australasian College of Physical Scientists in Medicine and the Australasian Association of Physical Sciences in Medicine, Jan 5, 2016

The alcoholism can be detected by analyzing electroencephalogram (EEG) signals. However, analyzin... more The alcoholism can be detected by analyzing electroencephalogram (EEG) signals. However, analyzing multi-channel EEG signals is a challenging task, which often requires complicated calculations and long execution time. This paper proposes three data selection methods to extract representative data from the EEG signals of alcoholics. The methods are the principal component analysis based on graph entropy (PCA-GE), the channel selection based on graph entropy (GE) difference, and the mathematic combinations channel selection, respectively. For comparison purposes, the selected data from the three methods are then classified by three classifiers: the J48 decision tree, the K-nearest neighbor and the Kstar, separately. The experimental results show that the proposed methods are successful in selecting data without compromising the classification accuracy in discriminating the EEG signals from alcoholics and non-alcoholics. Among them, the proposed PCA-GE method uses only 29.69 % of the ...

IET Science, Measurement & Technology, 2012

An anatomically accurate high-resolution finite-element head model and its derivatives have been ... more An anatomically accurate high-resolution finite-element head model and its derivatives have been employed to examine the influence of subcutaneous fat and muscle tissues on cortical modulation. The effects of skull, muscle and white matter (WM) directional conductivity have also been investigated. Results indicate that the inclusion of additional tissues in the head model have a profound effect on the magnitude and distribution pattern of induced current density. Similarly, anisotropic tissue conductivity caused a significant deterioration in spatial focality of cortical currents along with a more distorted and diffused distribution pattern across the cortex.

2007 IEEE International Conference on Integration Technology, 2007

In this study, two methods, Auditory Evoked Potential (AEP) and bispectrum, based on EEG signal p... more In this study, two methods, Auditory Evoked Potential (AEP) and bispectrum, based on EEG signal processing are employed in monitoring depth of anaesthesia. Auditory evoked potential is obtained using wavelet analysis in order to achieve a fast extraction. Both AEP and bispectrum methods show good relativity with the depth of anaesthesia. Besides, both methods are integrated in a software developed on a personal computer to help those non-specialists to apply the results easily.

Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics

Rough Sets and Knowledge Technology

HKIE Transactions

Australia’s recent mining boom has mainly been created by China’s need for minerals. A large numb... more Australia’s recent mining boom has mainly been created by China’s need for minerals. A large number of migrant engineers move to Australia from China, Australia’s largest trading partner, if China’s Special Administration Region, Hong Kong is taken into account. Education is Australia’s third largest export and China is the largest source of Australian international students (the number in 2008 was 12,770). Higher education including engineering education is an important source of income to Australians. On account of the above ground, international students from China, particularly engineering ones, are important to Australia. It can be argued that comparing and contrasting engineering education in China and Australia is critical in determining the extent that engineers from China can help reduce the skill shortages in the engineering workforce in Australia.

Journal of Advanced Computational Intelligence and Intelligent Informatics

EEG-based applications have faced the challenge of multi-modal integrated analysis problems. In t... more EEG-based applications have faced the challenge of multi-modal integrated analysis problems. In this paper, a greedy maximal weight matching approach is used to measure the functional connectivity in alcoholics datasets with EEG and EOG signals. The major discovery is that the processing of the repeated and unrepeated stimuli in the γ band in control drinkers is significantly more different than that in alcoholic subjects. However, the EOGs are always stable in the case of visual tasks, except for a weakly wave when subjects make an error response to the stimuli.

Computer methods and programs in biomedicine, 2016

This paper focuses on electroconvulsive therapy (ECT) and head models to investigate temperature ... more This paper focuses on electroconvulsive therapy (ECT) and head models to investigate temperature profiles arising when anisotropic thermal and electrical conductivities are considered in the skull layer. The aim was to numerically investigate the threshold for which this therapy operates safely to the brain, from the thermal point of view. A six-layer spherical head model consisting of scalp, fat, skull, cerebro-spinal fluid, grey matter and white matter was developed. Later on, a realistic human head model was also implemented. These models were built up using the packages from COMSOL Inc. and Simpleware Ltd. In these models, three of the most common electrode montages used in ECT were applied. Anisotropic conductivities were derived using volume constraint and included in both spherical and realistic head models. The bio-heat transferring problem governed by Laplace equation was solved numerically. The results show that both the tensor eigenvalues of electrical conductivity and th...

Australasian Physical & Engineering Sciences in Medicine, 2016

This paper presents a new method to apply timing characteristics of electroencephalograph (EEG) b... more This paper presents a new method to apply timing characteristics of electroencephalograph (EEG) beta frequency bands to assess the depth of anaesthesia (DoA). Firstly, the measured EEG signals are denoised and decomposed into 20 different frequency bands. The Mobility (M), permutation entropy (PE) and Lempel-Ziv complexity (LCZ) of each frequency band are calculated. The M, PE and LCZ values of beta frequency bands (21.5-30 Hz) are selected to derive a new index. The new index is evaluated and compared with measured bispectral (BIS). The results show that there is a very close correlation between the proposed index and the BIS during different anaesthetic states. The new index also shows a 25-264 s earlier time response than BIS during the transient period of anaesthetic states. In addition, the proposed index is able to continuously assess the DoA when the quality of signal is poor and the BIS does not have any valid outputs.

The demand for non-invasive vehicle counting and classifying devices has grown significantly in p... more The demand for non-invasive vehicle counting and classifying devices has grown significantly in past decades due to contributing factors from occupational health and safety standards developed by state road authorities. In this paper, we present an automated vehicle classification system based upon the laser sensor technology. The system is capable of classifying vehicles in multi-lane, high speed environments, and requires no apparatus be placed on the carriageway. As opposed to the conventional Fourier-based filtering method, this paper also proposes a novel wavelet-based noise reduction technique to enhance performance.