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Chapter and Conference Paper
Fractional Elzaki Variational Iteration Method for Solving Nonlinear Biological Population Model
The approximate solutions for the two dimensional nonlinear PDEs with Liouville-Caputo fractional derivative are determined and presented in this paper. Comparative numerical simulations obtained from alternat...
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Chapter and Conference Paper
A Hybrid Computational Scheme for Solving Local Fractional Partial Differential Equations
A new type of methodology termed the local fractional natural homotopy perturbation method (LFNHPM) with the local fractional derivative operator (LFDO) was implemented in this study. The hybrid methodology co...
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Chapter and Conference Paper
Fast Fourier Transform Coupled with Machine Learning Algorithm for K-Complexes Detection
This paper proposes a novel K-complexes (KCs) detection approach using sleep electroencephalogram (EEG) recordings. A segmentation technique is used to partition an EEG signal into intervals. Then, fast Fourie...
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Article
Open AccessDevelo** a robust model to predict depth of anesthesia from single channel EEG signal
Monitoring depth of anaesthesia (DoA) from electroencephalograph (EEG) signals is an ongoing challenge for anaesthesiologists. In this study, we propose an intelligence model that predicts the DoA from a singl...
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Chapter and Conference Paper
An Intelligence Approach for Blood Pressure Estimation from Photoplethysmography Signal
Commercial cuff-based Blood pressure (BP) devices are mainly not suitable or portable. To ease the measurement of BP devices, we proposed a new model for BP estimation based on photoplethysmography (PPG) signa...
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Chapter and Conference Paper
A Novel Alcoholic EEG Signals Classification Approach Based on AdaBoost k-means Coupled with Statistical Model
Identification of alcoholism is an important task because it affects the operation of the brain. Alcohol consumption, particularly heavier drinking is identified as an essential factor to develop health issues...
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Chapter
A Structural Graph-Coupled Advanced Machine Learning Ensemble Model for Disease Risk Prediction in a Telehealthcare Environment
The use of intelligent and sophistic technologies in evidence-based clinical decision making support have been playing an important role in improving the quality of patients’ life and hel** to reduce cost an...
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Article
Open AccessClassification of epileptic EEG signals based on simple random sampling and sequential feature selection
Electroencephalogram (EEG) signals are used broadly in the medical fields. The main applications of EEG signals are the diagnosis and treatment of diseases such as epilepsy, Alzheimer, sleep problems and so on...
