Literature DB >> 10359498

Automatic detection of seizures and spikes.

J Gotman1.   

Abstract

The recording of seizures and spikes is of primary importance in the evaluation of epileptic patients. This is not always an easy process because these events can be rare and are usually unpredictable. Since the earliest days of computer analysis of the EEG, researchers have developed methods for the automatic detection of spikes and, more recently, of seizures. The problems are complex because spikes and seizures are not clearly defined and have extremely varied morphologies. Nevertheless, it has been possible to develop automatic detection methods that can be of great assistance during long-term monitoring of epileptic patients. No method is absolutely fail-safe and all require human validation, but they save a considerable amount of time in the interpretation of long recordings. Recent developments include detection of the patterns specific to newborns, and the possibility of warning a patient or observer that a seizure is starting.

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Year:  1999        PMID: 10359498     DOI: 10.1097/00004691-199903000-00005

Source DB:  PubMed          Journal:  J Clin Neurophysiol        ISSN: 0736-0258            Impact factor:   2.177


  22 in total

1.  Depth-time interpolation of feature trends extracted from mobile microelectrode data with kernel functions.

Authors:  Stephen Wong; Eric L Hargreaves; Gordon H Baltuch; Jurg L Jaggi; Shabbar F Danish
Journal:  Stereotact Funct Neurosurg       Date:  2012-01-19       Impact factor: 1.875

2.  Automatic seizure detection in SEEG using high frequency activities in wavelet domain.

Authors:  L Ayoubian; H Lacoma; J Gotman
Journal:  Med Eng Phys       Date:  2012-05-29       Impact factor: 2.242

3.  Toward a noninvasive automatic seizure control system in rats with transcranial focal stimulations via tripolar concentric ring electrodes.

Authors:  Oleksandr Makeyev; Xiang Liu; Hiram Luna-Munguía; Gabriela Rogel-Salazar; Samuel Mucio-Ramirez; Yuhong Liu; Yan L Sun; Steven M Kay; Walter G Besio
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2012-07       Impact factor: 3.802

4.  Feature extraction and recognition of epileptiform activity in EEG by combining PCA with ApEn.

Authors:  Chunmei Wang; Junzhong Zou; Jian Zhang; Min Wang; Rubin Wang
Journal:  Cogn Neurodyn       Date:  2010-06-26       Impact factor: 5.082

5.  Optimal features for online seizure detection.

Authors:  Lojini Logesparan; Alexander J Casson; Esther Rodriguez-Villegas
Journal:  Med Biol Eng Comput       Date:  2012-04-03       Impact factor: 2.602

6.  Role of subdural electrocorticography in prediction of long-term seizure outcome in epilepsy surgery.

Authors:  Eishi Asano; Csaba Juhász; Aashit Shah; Sandeep Sood; Harry T Chugani
Journal:  Brain       Date:  2009-03-13       Impact factor: 13.501

Review 7.  Toward rational design of electrical stimulation strategies for epilepsy control.

Authors:  Sridhar Sunderam; Bruce Gluckman; Davide Reato; Marom Bikson
Journal:  Epilepsy Behav       Date:  2009-11-17       Impact factor: 2.937

8.  Analysis of intracerebral EEG recordings of epileptic spikes: insights from a neural network model.

Authors:  Sophie Demont-Guignard; Pascal Benquet; Urs Gerber; Fabrice Wendling
Journal:  IEEE Trans Biomed Eng       Date:  2009-07-31       Impact factor: 4.538

9.  Interictal networks in magnetoencephalography.

Authors:  Urszula Malinowska; Jean-Michel Badier; Martine Gavaret; Fabrice Bartolomei; Patrick Chauvel; Christian-George Bénar
Journal:  Hum Brain Mapp       Date:  2013-09-18       Impact factor: 5.038

Review 10.  Spatial analysis of intracerebral electroencephalographic signals in the time and frequency domain: identification of epileptogenic networks in partial epilepsy.

Authors:  Fabrice Wendling; Fabrice Bartolomei; Lotfi Senhadji
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2009-01-28       Impact factor: 4.226

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