An EEG Device for Monitoring Seizure Discharges

Neonatal seizures are a distinct and not uncommon sign of neurological disease in the newborn, most often occurring in association with hypoxic-ischaemic encephalopathy at term. The diagnosis and monitoring of seizures in the newborn is a considerable challenge, with many suspected clinical seizures having no electrographic correlates, while many electrographic seizures have no clinical correlate. Continuous video-EEG is the gold standard for seizure monitoring, but few centres have the resources or expertise required. Amplitude-integrated EEG can be a helpful monitoring tool in experienced hands, but has potential for error when used by inexperienced staff. Automated seizure detection algorithms show much promise and some cotside systems are already available. The efficiency and accuracy of these systems is likely to improve.

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“…Typically, an electrographic seizure will bring about a rise in the lower and upper margins of the aEEG (figure 2). 18…”

Section: The Use Of Amplitude-integrated Eeg To Monitor Seizuresmentioning

confidence: 99%

Monitoring of seizures in the newborn

Shah¹,

Boylan

Rennie

2010

Arch Dis Child Fetal Neonatal Ed

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“…Research in automated seizure detection began in the 1970s and various algorithms addressing this problem [ 5 – 7 ] have been presented. Methods for automatic detection of seizures may rely on the identification of various patterns such as an increase in amplitude [ 8 ], sustained rhythmic activity [ 9 , 10 ], or EEG flattening [ 11 ]. Several algorithms have been developed based on spectral [ 12 – 18 ] or wavelet features [ 19 – 23 ], amplitude relative to background activity [ 12 , 24 ] and spatial context [ 24 – 27 ].…”

Section: Introductionmentioning

confidence: 99%

Automatic Seizure Detection Based on Time-Frequency Analysis and Artificial Neural Networks

Tzallas

Tsipouras

Fotiadis

2007

Computational Intelligence and Neuroscience

393

196

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The recording of seizures is of primary interest in the evaluation of epileptic patients. Seizure is the phenomenon of rhythmicity discharge from either a local area or the whole brain and the individual behavior usually lasts from seconds to minutes. Since seizures, in general, occur infrequently and unpredictably, automatic detection of seizures during long-term electroencephalograph (EEG) recordings is highly recommended. As EEG signals are nonstationary, the conventional methods of frequency analysis are not successful for diagnostic purposes. This paper presents a method of analysis of EEG signals, which is based on time-frequency analysis. Initially, selected segments of the EEG signals are analyzed using time-frequency methods and several features are extracted for each segment, representing the energy distribution in the time-frequency plane. Then, those features are used as an input in an artificial neural network (ANN), which provides the final classification of the EEG segments concerning the existence of seizures or not. We used a publicly available dataset in order to evaluate our method and the evaluation results are very promising indicating overall accuracy from 97.72% to 100%.

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“…However not all NICUs have access to conventional EEG. In 1973, Prior et al [11] described the use of single channel amplitudeintegrated EEG as a simpler means of monitoring for electrographic seizure activity in adult patients. The "raw" EEG signal is processed so that frequencies below 2 Hz and greater than 15 Hz are attenuated.…”

Section: Methodsmentioning

confidence: 99%

Automated seizure detection systems in the newborn

2015

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Electrographic seizures are an important manifestation of cerebral pathology in the newborn. Over the last few decades, automated seizure detection systems have been devised in order to assist the clinician's review. Basic principles and approaches of systems applied to the newborn, using multiple channels are compared. The application of a system using two channels of electroencephalography with amplitude-integrated electroencephalography monitoring in the newborn is also described. Newer and novel approaches to automated seizure detection are also discussed.

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An EEG Device for Monitoring Seizure Discharges

Cited by 38 publications

References 8 publications

Monitoring of seizures in the newborn

Monitoring of seizures in the newborn

Automatic Seizure Detection Based on Time-Frequency Analysis and Artificial Neural Networks

Automated seizure detection systems in the newborn

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