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Keyword: Discrete Wavelet TransformEEG Feature Extraction based on Fast Fourier Transform and Wavelet Analysis for Classification of Mental Stress Levels using Machine Learning
Mental stress assessment remains riddled with biases caused by subjective reports and individual differences across societal backgrounds. To objectively determine the presence or absence of mental stress, there is a need to move away from the traditional subjective methods of self-report questionnaires and interviews. Previously, it has been evidence that EEG Oscillations can discriminate mental…
Read MoreA Psychovisual Optimization of Wavelet Foveation-Based Image Coding and Quality Assessment Based on Human Quality Criterions
In the present article, we introduce a foveation-based optimized embedded and its optimized version image coders thereafter called VOEFIC/MOEFIC and its related foveation wavelet visible difference predictor FWVDP coding quality metric. It advances a visually advanced foveal weighting mask that regulates the wavelet-based image spectrum before its encoding by the SPIHT encoder. It intends to…
Read MoreDevelopment of Wavelet-Based Tools for Event Related Potentials’ N400 Detection: Application to Visual and Auditory Vowelling and Semantic Priming in Arabic Language
Neurological signals are generally very weak in amplitude and strongly noisy. As a result, one of the major challenges in neuroscience is to be able to eliminate noise and thus exploit the maximum amount of information contained in neurological signals (EEG…). In this paper, we aimed at studying the N400 wave of the Event-Related Potentials…
Read MoreA Perceptually Optimized Embedded Image Coder and Quality Assessor Based Both on Visual Tools
In this paper, we propose a new Perceptually Optimized Embedded Zero Tree Image Coder EVIC and its improved version MEVIC. The coder presents a new perceptual model to weight wavelet coefficients to enhance SPIHT embedded coding. The new visual coder aims to improve the visual quality obtained by the reference SPIHT coder for a given…
Read MoreClassification of patient by analyzing EEG signal using DWT and least square support vector machine
Epilepsy is a neurological disorder which is most widespread in human beings after stroke. Approximately 70% of epilepsy cases can be cured if diagnosed and medicated properly. Electro-encephalogram (EEG) signals are recording of brain electrical activity that provides insight information and understanding of the mechanisms inside the brain. Since epileptic seizures occur erratically, it is…
Read MoreMulticlass Myoelectric Identification of Five Fingers Motion using Artificial Neural Network and Support Vector Machine
The research in Neuro-Prosthetics is gaining more significance and popularity as the advancement in prosthetics control allows amputees to perform even more tasks. Indeed, the improvement of classification accuracy is a challenge in prosthetics control. In this research, a system is developed in order to improve the multiclass classification rate. Two classifiers namely Artificial Neural…
Read MoreA Comparative Study For Color Systems Used In The DCT-DWT Watermarking Algorithm
This paper presents a comparative study of using different color systems on watermarking algorithms. This comparison aim is to determining the robustness and the stability of the color systems used in the watermarking scheme. The watermarking algorithm that is used in this paper is a hybrid scheme using the Discrete Wavelet Transform (DWT) in the…
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