https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 Alcoholic index using non-linear features extracted from different frequency bands https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:33827 six levels of Wavelet Packet Decomposition (WPD) to obtain seven wavebands (delta (d), theta (t), lower alpha (la), upper alpha (ua), lower beta (lb), upper beta (ub), lower gamma (lg)). From each wavebands (activity bands), 19 non-linear features such as Recurrence Quantification Analysis (RQA) (xy), Approximate Entropy (xap), Energy (Ωx), Fractal Dimension (FD) (FxD), Permutation Entropy (Exp), Detrended Fluctuation Analysis (αxy), Hurst Exponent (ExH), Largest Lyapunov Exponent (ExLLLE), Sample Entropy (Exs), Shannon's Entropy (Exsh), Renyi's entropy (Exr), Tsalli's entropy (Exts), Fuzzy entropy (Exf), Wavelet entropy (Exw), Kolmogorov-Sinai entropy (Exks), Modified Multiscale Entropy (Exmmsy), Hjorth's parameters (activity (Sxa), mobility (Hxm), and complexity (Hxc)) are extracted. The extracted features are then ranked using Bhattacharyya, Entropy, Fuzzy entropy-based Max-Relevancy and Min-Redundancy (mRMR), Receiver Operating Characteristic (ROC), -test, and Wilcoxon. These ranked features are given to train Support Vector Machine (SVM) classifier. The SVM classifier with radial basis function (RBF) achieved 95.41% accuracy, 93.33% sensitivity and 97.50% specificity using four non-linear features ranked by Wilcoxon method. In addition, an integrated index called Alcoholic Index ( ALCOHOLI) is developed using highly ranked two features for identification of normal and alcoholic EEG signals using a single number. This system is rapid, efficient, and inexpensive and can be employed as an EEG analysis assisting system by clinicians in the detection of alcoholism. In addition, the proposed system can be used in rehabilitation centers to evaluate person with alcoholism over time and observe the outcome of treatment provided for reducing or reversing the impact of the condition on the brain.]]> Thu 28 Oct 2021 13:05:10 AEDT ]]> Performance evaluation of dry eye detection system using higher-order spectra features for different noise levels in IR thermal images https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:33829 Thu 17 Jan 2019 13:58:10 AEDT ]]> An integrated index for identification of fatty liver disease using radon transform and discrete cosine transform features in ultrasound images https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29741 Sat 24 Mar 2018 07:27:42 AEDT ]]>