Epilepsy

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Epilepsy (from the Ancient Greek ἐπιληψία — "seizure") is a common chronic neurological disorder characterized by seizures. (Wikipedia.org)






Conferences related to Epilepsy

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2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2018 will be the 15th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2018 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2017 will be the 14th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2017 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forumfor the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2016 willbe the thirteenth meeting in this series. The previous meetings have played a leading role in facilitatinginteraction between researchers in medical and biological imaging. The 2016 meeting will continue thistradition of fostering crossfertilization among different imaging communities and contributing to an integrativeapproach to biomedical imaging across all scales of observation.

  • 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2015 will be the 12th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2014 will be the eleventh meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013)

    To serve the biological, biomedical, bioengineering, bioimaging and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2010 IEEE 7th International Symposium on Biomedical Imaging (ISBI 2010)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2009 IEEE 6th International Symposium on Biomedical Imaging (ISBI 2009)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2008 IEEE 5th International Symposium on Biomedical Imaging (ISBI 2008)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2007 IEEE 4th International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2007)

  • 2006 IEEE 3rd International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2006)

  • 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2004)

  • 2002 1st IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2002)


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


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Periodicals related to Epilepsy

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Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Biomedical Engineering, IEEE Reviews in

The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Electron Devices, IEEE Transactions on

Publishes original and significant contributions relating to the theory, design, performance and reliability of electron devices, including optoelectronics devices, nanoscale devices, solid-state devices, integrated electronic devices, energy sources, power devices, displays, sensors, electro-mechanical devices, quantum devices and electron tubes.


Engineering in Medicine and Biology Magazine, IEEE

Both general and technical articles on current technologies and methods used in biomedical and clinical engineering; societal implications of medical technologies; current news items; book reviews; patent descriptions; and correspondence. Special interest departments, students, law, clinical engineering, ethics, new products, society news, historical features and government.


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Most published Xplore authors for Epilepsy

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Xplore Articles related to Epilepsy

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An evaluation of single dipole solutions to extended sources in EEG and MEG

2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism, 2011

Interictal spikes as observed in epilepsy patients are assumed to be generated by relatively large patches of activated cortex. In order to check the validity of single dipole solutions to such spikes in EEG and MEG a simulation study is performed in a realistically shaped cortical model. It is shown that both in EEG and MEG the center of activated ...


GMM better than SRC for classifying epilepsy risk levels from EEG signals

2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS), 2015

EEG is the most commonly used technique for the monitoring of the brain activities in the case of epilepsy. Generally, the visual encephalographers and the expert neurologists analyze the EEG records and it is quite time consuming. In the EEG recordings, several noisy characteristics are present making it difficult for the experts to differentiate between an artifact and seizure in ...


Automatic detection of epileptiform activity using wavelet and expert rule base

Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286), 1998

We present a new method to detect epileptiform activity based on wavelet transform (WT), an artificial neural network and an expert rule system. The method consists of three steps. First, we extract features of spike events on the wavelet subspace. It appears technically feasible to reduce computational complexity. Then, the features are trained and tested to decide epileptic events with ...


Adaptive separation of background activity and transient phenomenon in epileptic EEG using mathematical morphology and wavelet transforms

Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143), 2000

Epileptic EEG data contains transient activities, such as spikes, muscle activities, eye movements and artifacts. The transients are complex in shape, occurring randomly and with short duration. The background EEG often appears as a slow wave in contrast with transients. In the past, many methods have been investigated to separate the two components of background activity and transients. These methods ...


Phase space analysis of EEG in temporal lobe epilepsy

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1988

The electrocorticograms of human epileptic patients are analyzed by phase- space methods. The presence of an attractor is demonstrated as well as its low dimension during the preictal, ictal, and postictal period. The evaluation of the corresponding dimension of the phase space gives the minimum number of the necessary parameters. The integral correlation function provides insight into the dynamics of ...


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Educational Resources on Epilepsy

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IEEE-USA E-Books

  • An evaluation of single dipole solutions to extended sources in EEG and MEG

    Interictal spikes as observed in epilepsy patients are assumed to be generated by relatively large patches of activated cortex. In order to check the validity of single dipole solutions to such spikes in EEG and MEG a simulation study is performed in a realistically shaped cortical model. It is shown that both in EEG and MEG the center of activated cortex can be misrepresented by single dipole solutions by more then 1 cm. The geometry of sulci and gyri determines where, for which modality, this effect is larger.

  • GMM better than SRC for classifying epilepsy risk levels from EEG signals

    EEG is the most commonly used technique for the monitoring of the brain activities in the case of epilepsy. Generally, the visual encephalographers and the expert neurologists analyze the EEG records and it is quite time consuming. In the EEG recordings, several noisy characteristics are present making it difficult for the experts to differentiate between an artifact and seizure in raw EEG signals. The detection and classification of epileptic activity is quite a high demanding process. Therefore automatic prediction and detection algorithms are in need to predict the epileptic seizures in the EEG signals. The technique used here is by the employment of Approximate Entropy as a Feature Extraction technique and then Gaussian Mixture Model (GMM) and Sparse Representation Classifier (SRC) are used as Post Classifiers for the classification of epilepsy risk levels from EEG signals. The bench mark parameters analyzed here are Performance Index (PI), Quality Value (QV), Specificity, Sensitivity, Time Delay (TD) and Accuracy.

  • Automatic detection of epileptiform activity using wavelet and expert rule base

    We present a new method to detect epileptiform activity based on wavelet transform (WT), an artificial neural network and an expert rule system. The method consists of three steps. First, we extract features of spike events on the wavelet subspace. It appears technically feasible to reduce computational complexity. Then, the features are trained and tested to decide epileptic events with three layer feedforward networks employing the backpropagation (BP) learning algorithm. Finally, to confirm and validate epileptiform activity, we apply an expert system based on rule base. The result shows that the wavelet transform reduced data input size and the preprocessed artificial neural network (ANN) are more accurate than those of ANN with the same input size of raw data. In clinical tests, our expert system was capable of rejecting artifacts commonly found in EEG recordings.

  • Adaptive separation of background activity and transient phenomenon in epileptic EEG using mathematical morphology and wavelet transforms

    Epileptic EEG data contains transient activities, such as spikes, muscle activities, eye movements and artifacts. The transients are complex in shape, occurring randomly and with short duration. The background EEG often appears as a slow wave in contrast with transients. In the past, many methods have been investigated to separate the two components of background activity and transients. These methods detect background activity or localize the transients by using linear signal processing techniques, which are not effective for detecting sharp waves and patterns. This paper presents a new approach to signal separation by directly judging the differences between the components' shapes using morphological analysis. Morphological analysis utilizes analytic operations based on a pre-defined structuring element (SE). These operations, implemented by a filter, can detect and extract specific signal features determined by the SE. In our case, the SE is defined as a circle to measure the degree of smoothness between the two signal components. A discrete wavelet transform is applied to construct the processed signal. The multi-resolution property of the wavelet transform adapts well to the time- invariant nature of the signal. Combining mathematical morphology and wavelet transforms, this method has successfully separates the background activity and transient phenomenon from an epileptic EEG signal.

  • Phase space analysis of EEG in temporal lobe epilepsy

    The electrocorticograms of human epileptic patients are analyzed by phase- space methods. The presence of an attractor is demonstrated as well as its low dimension during the preictal, ictal, and postictal period. The evaluation of the corresponding dimension of the phase space gives the minimum number of the necessary parameters. The integral correlation function provides insight into the dynamics of the neural networks involved in the three different stages of the phenomenon. The temporal change of the largest Lyapunov exponent is followed throughout the seizure giving a measure of the unpredictability inside the attractor. All of the above measures can be used for better mathematical modeling of the underlying process.<<ETX>>

  • Detection of epileptiform activity using wavelet and neural network

    This paper describes a multichannel epileptic seizure detection algorithm based on wavelet transform (WT), artificial neural network (ANN) and the expert system. First, a small set of wavelet coefficients is used to represent the characteristics of a single channel epileptic spike. The purpose of this WT is to reduce the number of inputs to the ANN. Next, three layer feedforward network employing the error backpropagation algorithm is trained and tested using parameters obtained by the WT. Finally, 16 channel expert system based on the context information of adjacent channels is introduced to reject artifacts and produce reliable results. In this study, epileptic spike and normal activities were selected from 32 patient's EEGs (seizure disorder: 12, normal: 20) in consensus among experts. The result was that the WT reduced data input size and the preprocessed ANN had 97% sensitivity and 89.5% selectivity, which were more accurate than that of ANN with the same input size of raw data. Our expert rule system was capable of rejecting a wide variety of artifacts commonly found in EEG recordings. It's average false detection rate was 5.5/h for ANN's threshold=0.65 and false detection was also a little decreased by high thresholds.

  • Visualization in medicine: VIRTUAL reality or ACTUAL reality ?

    Discusses and debates the role played by 3D visualization in medicine as a set of methods and techniques for displaying 3D spatial information related to the anatomy and the physiology of the human body.<<ETX>>

  • Individual features of the dynamics of coupling from Time Series of Intracranial EEGs of Cortex of WAG/Rij’s Rats before and after of the drug.

    In this study, the intracranial EEG recordings are investigated with a mutual information function in the six intervals. Each rats was considered individually, the results are averaged across all categories. The results of the control group of rats and rats after administration of the drug - agonist of endocannabinoid receptors are compared.

  • The stability of behavioral synchronization in a network of bursting neurons: a new explanation for epileptogenesis

    In this paper, we explored a new category of synchronization, namely the "behavioral synchronization". Instead of describing the signal, this category refers to the behavior. Two systems can be, each of them, in function mode A or B. If both of them are simultaneously in the same mode A or B, they are in synchronized behavior state. However, the outputs of the systems can be uncorrelated. The model proposed for investigation is a network of neurons that generate bursting (firing) behavior. The individual neuron displays characteristic firing patterns determined by the number and kind of ion channels in its membrane. One of the neuroscience problems is to explain how the system's dynamics depend on the properties of individual neurons, the synaptic architecture by which they are connected, and the strength and time course of the synaptic connections. In our model proposed for investigation, the output signals are chaotic and uncorrelated, although the systems are behaviorally synchronized. We proposed a new explanation for the appearance of the epileptic seizures that uses the concept of behavioral synchronization and is included in the family of hypothesis that state that the epilepsy is a network disorder. We proved mathematically and by simulations that, for a large range of values for the control parameters, the network is unstable and has chaotic behavior

  • Metric multidimensional scaling and aggregation operators for classifying epilepsy from EEG signals

    As a result of sudden and excessive electrical discharges in a specific group of brain cells called neurons, epilepsy occurs and is usually for a brief period. It can occur in various parts of the brain and the patient can experience different symptoms depending on the occurrence of the excessive discharges. So the electrical impulses generated due to the nerve firing in the brain can be measured easily with the help of Electroencephalogram (EEG) by placing the electrodes on the scalp of the patient. As the recordings are too long, the data to be processed is large and hence Metric Multidimensional Scaling (MDS) is used to reduce the dimensions of the EEG data. The dimensionally reduced values are then fed inside the Aggregation Operator Classifiers to classify the epilepsy from EEG signals. Results show that an average accuracy of 92.36% along with an average time delay of 2.44 seconds is found out.



Standards related to Epilepsy

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Jobs related to Epilepsy

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