Search Results - (( evolution optimization method algorithm ) OR ( seizure detection method algorithm ))

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  1. 1
    Epileptic Seizure Detection Using Singular Values And Classical Features Of EEG Signals

    Epileptic Seizure Detection Using Singular Values And Classical Features Of EEG Signals by Ahmed, Ahmed Elsayed Elmahdy

    Published 2014
    “…This project aims at developing an automated epileptic seizure event detection algorithm. The proposed algorithm depends on using five features which are singular values, total power, delta band power, variance and mean. …”
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  2. 2
    Focal and non-focal epilepsy localization: a review

    Focal and non-focal epilepsy localization: a review by Hussein, Ahmed Faeq, N., Arunkumar, Gomes, Gorakanage Arosha Chandima, Alzubaidi, Abbas K., Habash, Qais Ahmed, Granados, Luz Santamaria, Moreno, Juan Francisco Mendoza, Gonzalez, Gustavo Ramirez

    Published 2018
    “…This study reviews many recently-proposed algorithms for detecting the focal epileptic seizures. …”
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  3. 3
    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems

    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems by Shakir, Mohamed, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…This can be observed and the algorithm with the detection structure can produce cautioning signals for epileptic seizure.…”
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  4. 4
    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems

    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This can be observed and the algorithm with the detection structure can produce cautioning signals for epileptic seizure. …”
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  5. 5
    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data

    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data by Qidwai, U., Malik, A.S., Shakir, M.

    Published 2014
    “…However, the common clinical methods are insufficient when it comes to design an automated module to detect and predict partial seizure for epileptic patients. …”
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  6. 6
    Fuzzy Platform for Embedded Wearable EEG Seizure Detection in Ambulatory State

    Fuzzy Platform for Embedded Wearable EEG Seizure Detection in Ambulatory State by Shakir, Mohamed, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…This paper describes a classification method is presented using an Fuzzy System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  7. 7
    Rule-base wearable embedded platform for seizure detection from real EEG data in ambulatory state

    Rule-base wearable embedded platform for seizure detection from real EEG data in ambulatory state by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This paper describes a classification method is presented using an empirical Rule-base System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  8. 8
    Embedded wearable EEG seizure detection in ambulatory state

    Embedded wearable EEG seizure detection in ambulatory state by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This paper describes a classification method is presented using a Fuzzy System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  9. 9
    Detection of Epileptic EEG Signal Using Wavelet Transform and Adaptive Neuro-Fuzzy Inference System

    Detection of Epileptic EEG Signal Using Wavelet Transform and Adaptive Neuro-Fuzzy Inference System by Khosropanah, Pegah

    Published 2011
    “…Such algorithms use brain electrical activity signals called electro encephalography (EEG) and have 2 methods of detection: visual (by specialist inspection) and automatic (by using signal processing knowledge). …”
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  10. 10
    Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data

    Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed

    Published 2013
    “…However, the common clinical methods are insufficient when it comes to design an automated module to detect and predict partial seizure for epileptic patients. …”
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  11. 11
    Rule-Base Wearable Embedded Platform for Seizure Detection from Real EEG Data in Ambulatory State

    Rule-Base Wearable Embedded Platform for Seizure Detection from Real EEG Data in Ambulatory State by Mohamed, Shakir, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…This paper describes a classification method is presented using an empirical Rule-base System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  12. 12
    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data

    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data by Shakir, Mohamed, Malik, Aamir Saeed, Kamel, Nidal S., Qidwai, Uvais

    Published 2014
    “…In this paper, a classification method is presented using an Fuzzy Inference Engine to detect the incidences of preseizures in real/raw Epilepsy data. …”
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  13. 13
    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data

    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…In this paper, a classification method is presented using an Fuzzy Inference Engine to detect the incidences of pre-seizures in real/raw Epilepsy data. …”
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  14. 14
    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification

    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

    Published 2020
    “…Compared to state-of-the-art algorithms and other common methods, our method outperformed them in terms of sensitivity, specificity, and accuracy. …”
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  15. 15
    Swarm negative selection algorithm for electroencephalogram signals classification

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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  16. 16
    Fuzzification of epileptic data: an application for prediction and identification of partial seizure

    Fuzzification of epileptic data: an application for prediction and identification of partial seizure by Malik, Aamir Saeed, Nasif, Mohammad Shakir, Kamel , Nidal, Qidwai, U.

    Published 2013
    “…However, these approaches fall short when attempting to design an automated system to detect and predict partial seizure for epileptic patients. …”
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  17. 17
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
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  18. 18
    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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  19. 19
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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  20. 20
    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
    “…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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